Dapsone (4,4′ -diaminodiphenyl sulfone; DDS, **Figure 1**) has been chosen in this study as a model compound for evaluating the value of computational chemistry in solid form screening and characterization of a pharmaceutical hydrate. The compound itself has been synthesized for the first time over 100 years ago (Fromm and Wittmann, 1908) and its microbial activity and therapeutic use for leprosy has already been studied in the 1940s. DDS has reinvented itself as a drug many times and has been in use for numerous indications, treatment of leprosy, dermatitis herpetiformis, malaria, prophylaxis of pneumocytosis etc. (Wolf and Orni-Wasserlauf, 2000; Wozel and Blasum, 2014).

dapsone) hydrate.

Today, it is mainly used as first-line drug in the treatment of leprosy in combination with rifampicin and clofazimine. As such, it is listed in the WHO's List of Essential Medicines (medications satisfying the priority health care needs in humans) (World Health Organization, 2017). The compound is known to be polymorphic (anhydrate forms **I**–**IV**), with form **III** being reported to be the most stable form (Brandstaetter-Kuhnert et al., 1963; Kuhnert-Brandstatter and Moser, 1979). Single crystal structures are known for anhydrate forms **III** (Dickinson et al., 1970; Deo et al., 1980; Bocelli and Cantoni, 1990; Su et al., 1992; Bertolasi et al., 1993) and **II** (Braun et al., 2017). It is also known that DDS forms solvates with dichloromethane, 1,4-dioxane and tetrahydrofuran (Babashkina et al., 2012; Lemmer et al., 2012). Furthermore, several crystal structure determinations of a hydrate with the unusual DDS:water stoichiometry of 3:1 (0.33 hydrate) have been reported (Kuz'mina et al., 1981; Bel'skii et al., 1983; Yathirajan et al., 2014). Apart from these structure reports no other information about the hydrate can be found in the literature.

The aim of this study was to unravel the molecular/structural reasons for hydrate formation in DDS, the structural and thermodynamic relationship between the **0.33-Hy** and waterfree DDS forms and their interconversion pathways as a function of temperature and humidity/water activity through a combination of computational and experimental methods. A range of experimental techniques (crystallization, slurry experiments, thermal analysis and X-ray diffraction), along with CSP and pair-wise intermolecular energy calculations were applied to explore the solid forms at an atomistic level. The applied method for estimating the intermolecular interaction energies (CE-B3LYP), best described as a hybrid method, did perform surprisingly well compared to B3LYP-D2/6- 31G(d,p) counterpoise-corrected energies, but in considerable less computation time (Turner et al., 2014). However, calculating water interactions in organic (drug) hydrates represents a big challenge as the balance of host (organic molecule)-host, host-water, and water-water intermolecular interactions has to be modeled accurately. Most simple water potentials have been parametrized against a wide range of liquid properties (Guillot, 2002). A potential for studying ices and amorphous water, which reparametrized the TIP4P potential to reproduce the density of several forms of ice, has been developed by Abascal et al. (2005). Very recently it has been demonstrated (in lead optimization), that accurately modeling intermolecular interactions involving water requires the incorporation of three-body terms and nanoscale treatment of the dielectric response of confined frustrated water molecules (Fernández, 2016, 2017; Fernandez and Scott, 2017). Nevertheless, in our study we decided to test the applicability of the readily available and transferable CE-B3LYP method, which was not explicitly developed for hydrate structures. We address the role of CSP in hydrate screening and modeling and investigate whether it is possible to derive information about hydrate stability and dehydration mechanism based on structural classifications and simple intermolecular interaction energy estimations (i.e., estimating the strengths of host-host, water-host and water-water interactions).

# MATERIALS AND METHODS

## Computational Generation of the Monohydrate Crystal Energy Landscape

The global energy minimum of DDS, obtained using Gaussian09 (Frisch et al., 2009), was used in the CSP searches. 350,000 Z ′ = 1 monohydrate structures were generated using CrystalPredictor2.0 (Karamertzanis and Pantelides, 2005, 2007; Habgood et al., 2015) in 48 common space groups for organic molecules (Supplementary Material). The molecules were held rigid and the lattice energy was evaluated by an exp-6 potential with atomic charges derived using the CHELPG scheme (Breneman and Wiberg, 1990) and minimized. The 10,000 lowest energy crystal structures were used as starting points for optimizing the intermolecular lattice energy (Uinter), with an improved model for the intermolecular forces. This was calculated using the FIT exp-6 potential parameters (Coombes et al., 1996), the sulfur potential derived by Scheraga (Day et al., 2009) and the distributed multipoles (Stone, 2005) derived from the PBE0/6-31G(d,p) charge density using GDMA2 (Stone, 2010).

The optimal proton positions of the amino group and orientation of the phenyl groups, in all crystal structures within 15 kJ mol−1 of the global minimum (116 structures), were determined using the CrystalOptimizer database method (Kazantsev et al., 2011). This was done by minimizing the lattice energy (Elatt), calculated as the sum of the intermolecular contributions (Uinter) and the conformational energy penalty paid for distortion of the molecular geometry to improve the hydrogen bonding geometries. Conformational energy penalties (1Eintra, with respect to the pyramidal global conformational energy minimum) and isolated molecule charge densities were computed at the PBE0/6-31G(d,p) level, for each conformation considered in the minimization of Elatt. All isolated-molecule wave function calculations were performed using Gaussian09 (Frisch et al., 2009) and intermolecular lattice energies using DMACRYS (Price et al., 2010).

The 100 most stable structures (within 30 kJ mol−1 of the global minimum) were used as starting points for periodic electronic structure calculations. The DFT-D calculations were carried out with the CASTEP plane wave code (Clark et al., 2005) using the Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation (GGA) exchange-correlation density functional (Perdew et al., 1996) and ultrasoft pseudopotentials (Vanderbilt, 1990), with the addition of a semi-empirical dispersion correction developed by Tkatchenko and Scheffler (TS) (Tkatchenko Scheffler and Scheffler, 2009). Brillouin zone integrations were performed on a symmetrized Monkhorst–Pack k-point grid with the number of k-points chosen to provide a maximum spacing of 0.07 Å−1 and a basis set cut-off of 780 eV. The self-consistent field convergence on total energy was set to 1x10−5 eV. Energy minimizations were performed using the Broyden–Fletcher–Goldfarb–Shanno optimization scheme within the space group constraints. The optimizations were considered complete when energies were converged to better than 2 × 10−5 eV per atom, atomic displacements converged to 1 × 10−3 Å, maximum forces to 5 × 10−2 eV Å−1 , and maximum stresses were converged to 1 × 10−1 GPa. Isolated molecule minimizations to compute the isolated DDS and water energy (Ugas) were performed by placing a single molecule in a fixed cubic 35 × 35 × 35 Å3 unit cell and optimized with the same settings as used for the crystal calculations.

The experimental hydrate, lower hydrates and forms **II** and **III** of DDS, as well as other selected hydrates (Supplementary Material), were minimized with CASTEP and the same settings were used as described for generating the monohydrate crystal energy landscape.

#### Crystal Explorer Calculations

The pair-wise energy contributions to **0.33-Hy** and other wellcharacterized hydrate structures, have been calculated using CrystalExplorer V17 (Turner et al., 2014, 2015; Mackenzie et al., 2017). The optimized atomic positions (PBE-TS) have been used in all subsequent intermolecular interaction energy calculations. The model energies have been calculated between all unique nearest neighbor molecular pairs. The used model (termed CE-B3LYP) uses B3LYP/6-31G(d,p) molecular wave functions calculated by applying the molecular geometries extracted from the crystal structures. This approach uses electron densities of unperturbed monomers to obtain four separate energy components: electrostatic (EE), polarization (EP), dispersion (ED), and exchange-repulsion (ER). Each energy term was scaled independently to fit a large training set of B3LYP-D2/6-31G(d,p) counterpoise-corrected energies from both organic and inorganic crystals. The CE-B3LYP energies reproduced the training set energies with a mean absolute deviation of ∼1 kJ mol−1 (Turner et al., 2014).

# Conformational Analysis

Conformational energy scans were performed at the B3LYP/6- 31G(d,p) level of theory using Gaussian09 (Frisch et al., 2009), allowing the two torsion angles defining the position of the phenyl rings, C–C–S–C, to rotate by 360◦ in 20◦ steps.

# Materials and Preparation of DDS Hydrate

Dapsone form **III** (purity 97%) was purchased from Aldrich. The obtained sample was recrystallized from a hot-saturated methanol solution. The solid product was isolated by filtration and consisted of form **III**. The organic solvents used were all of analytical grade and purchased from Aldrich or Fluka.

DDS **0.33-Hy** was prepared as follows: (i) a slurry of DDS form **III** in water was stirred in the temperature range from 10 to 30◦C for 1 week. The suspension was filtered and the solid was stored at ambient conditions. (ii) A hot saturated solution of form **III** in water (close to the boiling point) was cooled to room temperature (RT). Within 2 days large elongated **0.33-Hy** crystals were obtained.

# Thermal Analysis

For hot-stage thermomicroscopic (HSM) investigations a Reichert Thermovar polarization microscope, equipped with a Kofler hot-stage (Reichert, A), was used. Photographs were taken with an Olympus DP71 digital camera (Olympus, A).

Differential Scanning Calorimetry (DSC) thermograms were recorded on a Diamond DSC (Perkin-Elmer Norwalk, Ct., USA) controlled by the Pyris 7.0 software. Using a UM3 ultramicrobalance (Mettler, Greifensee, CH), samples of ∼5– 7 mg were weighed into perforated or sealed aluminum pans. The samples were heated using rates in between 1 and 20◦C min−1 and cooled using a rate of 5 or 10◦C min−1 with dry nitrogen as the purge gas (purge: 20 mL min−1 ). The instrument was calibrated for temperature with pure benzophenone (mp 48.0◦C) and caffeine (236.2◦C), and the energy calibration was performed with indium (mp 156.6◦C, heat of fusion 28.45 J g−1 ). The errors on the stated temperatures (extrapolated onset temperatures) and enthalpy values were calculated at the 95% confidence interval (CI) and are based on at least five measurements.

Thermogravimetric Analysis (TGA) was carried out with a TGA7 system (Perkin-Elmer, Norwalk, CT, USA) using the Pyris 2.0 Software. Approximately 7–10 mg of sample was weighed into a platinum pan. Two-point calibration of the temperature was performed with ferromagnetic materials (Alumel and Ni, Curiepoint standards, Perkin-Elmer). Heating rates of 5 and 10◦C min−1 were applied and dry nitrogen was used as a purge gas (sample purge: 20 mL min−1 , balance purge: 40 mL min−1 ).

# Powder X-Ray Diffraction (PXRD)

PXRD patterns were obtained using an X'Pert PRO diffractometer (PANalytical, Almelo, NL) equipped with a θ/θ coupled goniometer in transmission geometry, programmable XYZ stage with well plate holder, Cu-Kα1,2 radiation source with a focusing mirror, a 0.5◦ divergence slit, a 0.02◦ Soller slit collimator on the incident beam side, a 2 mm antiscattering slit, a 0.02◦ Soller slit collimator on the diffracted beam side and a solid state PIXcel detector. The patterns were recorded at a tube voltage of 40 kV and tube current of 40 mA, applying a step size of 2θ = 0.013◦ with 200 s per step in the 2θ range between 2◦ and 40◦ . For non-ambient RH measurements, a VGI stage (VGI 2000M, Middlesex, UK) was used.

The diffraction patterns were indexed using the first 20 peaks with DICVOL04 and the space group was determined based on a statistical assessment of systematic absences (Markvardsen et al., 2001) as implemented in the DASH structure solution package (David et al., 2006). Pawley fits (Pawley, 1981) and Rietveld refinements (Rietveld, 1969) were performed with Topas Academic V5 (Coelho, 2012). The background was modeled with Chebyshev polynomials and the modified Thompson-Cox-Hastings pseudo-Voigt function was used for peak shape fitting. For the Rietveld refinements the DDS and water molecules were treated as rigid body molecules using the PBE-TS optimized conformations of the **0.33-Hy** structure.

# Gravimetric Moisture Sorption/Desorption Experiments

Moisture sorption and desorption studies were performed with the automatic multisample gravimetric moisture sorption analyser SPS23-10µ (ProUmid, Ulm, D). Approximately 500– 750 mg of sample was used for each analysis. The measurement cycles were started at 60% with an initial stepwise desorption (decreasing humidity) to 0%, followed by a sorption cycle (increasing humidity) up to 90% relative humidity (RH), a desorption cycle to 0% RH and a final sorption cycle to 90% RH. The RH changes were set to 2% and the equilibrium condition for each step was set to a mass constancy of ± 0.001% over 60 min and a maximum time limit of 48 h per step.

# Water Activity Measurements (Slurry Method)

DDS form **III** was stirred (500 r.p.m.) in 1.5–2.5 mL of each methanol and water mixture [each containing a different mole fraction of water corresponding to a defined water activity Zhu et al., 1996, Supplementary Material] at 25.0 ± 0.1◦C for 21 days. Samples were withdrawn, filtered and the resulting phase was determined using PXRD.

#### RESULTS AND DISCUSSION

### Computational Screening for DDS Monohydrates

The fact that the asymmetric unit of **0.33-Hy** (Kuz'mina et al., 1981; Bel'skii et al., 1983; Yathirajan et al., 2014) consists of four crystallographically distinct molecules (three DDS and one water) makes CSP studies for the experimental stoichiometry too time-consuming. Therefore, we decided to generate the monohydrate crystal energy landscape (one DDS and one water molecule) with the aim to estimate whether water molecules can compete against the DDS-DDS intermolecular interactions and form strong DDS-water contacts. In **Figure 2** the computed monohydrate structures are plotted according to lattice energy, which equals the energy that would be required to separate the molecules to infinity, against packing index.

To estimate whether any of the hypothetical monohydrate structure is competitive in energy with form **III**, we compared the lattice energy of the hydrate (Elatt-Hy) to the lattice energies of the anhydrate (Elatt-III) and ice (Elatt-ICE). If Elatt-Hy < Elatt-III + Elatt-ICE (we assume that hydrate formation is

FIGURE 2 | Summary of crystal structure prediction for DDS monohydrate (Z′ = 1), with each symbol denoting a crystal structure by its lattice energy and packing index. The vertical red dotted line separates the monohydrate structure that was calculated to be more stable than form III and ice from other computed hydrate structures that are less stable.

thermodynamically driven), then the hydrate is more stable than the anhydrate. Using the lattice energies of **0.33-Hy**, form **III** (**Table 1**) and a value of −59 kJ mol−1 (Whalley, 1957, 1976) for ice, as the used functional is known to overbind the ice crystal structures (Thierfelder et al., 2006; Beran and Nanda, 2010), then only one structure, 01\_1963, was calculated to be more stable than **III**. The most stable hypothetical monohydrate was estimated to be 12.38 kJ mol−1 more stable than form **III**, which is a respectable potential energy differences (1trsU) for a monohydrate with respect to an anhydrate. Thus, the CSP study clearly indicates hydrate formation.

Furthermore, 1trsU for the **0.33-Hy** to form **III** was calculated to be 15.37 kJ mol−1 , indicating that the experimental hydrate is 3 kJ mol−1 more stable than the computed lowest energy monohydrate structure and rationalizing why the stable 0.33 hydrate and not a monohydrate is formed experimentally.

#### Experimental Screening for DDS Hydrate(s)

To confirm that **0.33-Hy** is indeed the stable DDS hydrate form and that 01\_1963 is not a yet undiscovered monohydrate we subjected DDS to an experimental hydrate screening program. Evaporative crystallization experiments of DDS from a saturated (20◦C) aqueous solution, as well as cooling crystallization experiments from hot (boiling) saturated solutions in water at 5 ◦ , 25◦ , 50◦ , and 75◦C resulted in **0.33-Hy** crystals in the form of elongated plates. In contrast, evaporation experiments of a hot-saturated solution of DDS in water resulted in a mixture of **0.33-Hy** and form **III**. Slurry experiments in water, isothermal or cycling between 5◦ and 50◦C, always yielded the **0.33-Hy**.

Another successful way to produce hydrates are moisture sorption experiments. Therefore, form **III** and **V** (see section Moisture Dependent Stability of the Hydrate) were subjected to automated and manual water vapor sorption experiments. Neither form **III**, nor form **V** showed a transformation in the RH range up to 90%. Furthermore, no transformation was observed in long-time storage experiments of the two anhydrous DDS forms over saturated KOAc (24% RH), K2CO3 (43% RH), NaCl (75% RH), KNO3 solutions (92% RH) or water (100% RH) within 3 months (end of experiments) at RT and 8◦C. Similarly, also **0.33-Hy** did not dehydrate or transform to another hydrate if stored under the same conditions over the same time period.

TABLE 1 | Lattice energy calculations (Elatt) of 0.33-Hy, 01\_1963, forms II and III and the isomorphic dehydrate structure (0.33-Hy without water molecules, Hydehy) and potential energy differences (1trsU) with respect to form III.

aCalculated according to: –1trsUx−III = Elatt-x – (Elatt-III + Elatt-ICE). b –1trsUx−III = Elattx– Elatt-III.

#### Characterization of the DDS Hydrate DDS Hydrate Structure and Intermolecular Interaction Energies

To identify the key interactions in the DDS hydrate the pair-wise CE-B3LYP intermolecular energies were estimated starting from the PBE-TS optimized hydrate with the CSD Refcode ANSFON02 (Yathirajan et al., 2014). The intermolecular energies are subdivided into classical electrostatic (EE), polarization (EP), dispersion (ED) and exchange-repulsion energies (ER) and can be graphically represented by their "energy frameworks" (Turner et al., 2014, 2015; Mackenzie et al., 2017).

The hydrate crystallizes in the monoclinic space group C2/c with three DDS and one water molecule in the asymmetric unit, rationalizing the 3:1 stoichiometry (Kuz'mina et al., 1981; Bel'skii et al., 1983; Yathirajan et al., 2014). The three crystallographically independent DDS molecules (color coded in the packing diagram shown in **Figure 3A**) exhibit very similar conformations. The first DDS molecule (mol A, shown in red in **Figure 3A**) does not show any interaction with the hydrate water (**Table 1**), but forms two strong intermolecular interactions with itself, denoted with 2 and 4, mediated by inversion and 2-fold symmetry, respectively (**Figure 3B**). Furthermore, mol A forms classical hydrogen bonded interactions with neighboring DDS molecules

(interactions 5, 7, and 11; **Table 2**). In contrast to interactions 2 and 4, which have dispersion as the strongest contributor to the energy (π···π stacks), Coulomb interactions are the reason for the stability of the latter three (also true for 3, 6, 8, 9, 14, 15, 16, and 21). Molecule B (green) and C (blue) form the strongest pair-wise interaction (1, **Figure 3B**), which can be related to interaction 4. The third most stable interaction (3) involves mol C and is formed of four C–H···O close contacts. The strongest classical hydrogen bonded interaction (5, **Table 2**), N–H···O, is significantly less stable than interactions 1–4.

The water molecule, interacting only with mol B and mol C, forms three hydrogen bonds, two N–H···Owater and one Owater – H···O. Thus, the water molecule shows the water environment type DAA (Infantes et al., 2007), with A corresponding to hydrogen bonding acceptor and D to hydrogen bonding donor. According to Morris and Rodriguez-Hornedo (Morris and Rodriguez-Hornedo, 1993; Brittain et al., 2009) the DDS hydrate can be classified as an isolated-site hydrate, which retains water in segregated pockets in the crystal structure. The strongest pairwise water-DDS interaction was calculated to be −22.5 kJ mol−1 , which is distinctly weaker than the strongest pair-wise DDS-DDS interaction (−53.9 kJ mol−1 ).

The presence of an isolated-site hydrate could be confirmed by calculating the total energy of the hydrate and lower hydrate structures thereof, i.e., structures which were generated by systematically removing water molecules from the packing presented in **Figure 3** (using the P1 cell). **Figure 4** shows that a plot of the energy contributions from the water molecules to the hydrate structure vs. the water content gives a linear relationship. This clearly indicates that the water molecule interacts solely with DDS molecules in the **0.33-Hy**, which is a characteristic feature of an isolated-site hydrate.

#### Temperature Dependent Stability of the Hydrate

Key information for handling and storing hydrates is knowledge about temperature- and moisture-dependent stability. The dehydration process of **0.33-Hy** was monitored with HSM (**Figure 5**), DSC and TGA (**Figure 6**). To investigate the impact of the atmospheric conditions on the dehydration behavior and associated processes, different experimental conditions were applied: dry and silicon oil preparations (HSM), heating of the sample in perforated or sealed DSC crucibles and using different heating rates. The obtained thermodynamic data are summarized in **Table 3**.

The dehydration of **0.33-Hy** occurs in the temperature range from 40 to 90◦C. With HSM (dry preparation, **Figure 5**) hardly any change is observed during the dehydration process of the **0.33-Hy** to the isostructural dehydrate (**Hy**dehy). However, with TGA and DSC the dehydration is well observable. Under N2 purge (TGA) the dehydration process starts immediately and a mass loss of ∼0.3 mol of water per mol DDS was determined. In DSC investigations (1a, 2a), the dehydration appears as a broad endothermic event which partly overlaps with a second endothermic process at a heating rate of 10◦C min−1 . Using lower heating rates (not shown) the two thermal events can be separated and the heat of dehydration, 1dehyHHy−dehy of 10.60 kJ mol−1 (sample contained 0.18 mol water per mol DDS)

aElectrostatic (EE ), polarization (EP), dispersion (ED) and exchange-repulsion energy (ER) contributions. Etot = kE EE + kP EP + kD ED + kR ER, with k being scale factors (Mackenzie et al., 2017) b Interaction ID; cmolecule according to Figure 3A; dN – number of times interaction is present. eCentroid distances.

was determined. The known enthalpy value for the vaporization of water at the dehydration temperature (Tdehy ≈ 60◦C, 1vapH H2O = 42.482 kJ mol−1 (Riddick and Bunger, 1986) can be subtracted from the measured heat of dehydration (1dehyH), according to Equation (1), resulting in an estimation of the heat change (1trsH) upon hydrate to anhydrate transformation. The enthalpy of this reaction was calculated to be 2.95 ± 0.09 kJ mol−1 (**Table 3**).

FIGURE 4 | Energetic contribution (1Elatt, see Supplementary Table 5) of the water to the DDS hydrate structure in dependency of water occupancy (mol ratio water/DDS) in 0.33-Hy.

$$
\Delta\_{\rm trs}H\_{\rm Hy-delay} = \Delta\_{\rm defly}H\_{\rm Hy-delay} - 0.18 \cdot \Delta\_{\rm vap}H\_{\rm H2O} \tag{1}
$$

The second endotherm of the DSC traces (perforated crucibles) with an onset temperature of 103.6◦C corresponds to the solidsolid phase transformation of **Hy**dehy to form **II** (1.08 kJ mol−1 ). In HSM investigations an increase in birefringence is observable during the transformation process. Upon further heating, form **II** melts at 177.2◦C (1a) and concomitantly form **I** crystalizes, which then melts at 179◦C. Upon cooling the melt of DDS (1b) spontaneous crystallization of form **II** occurs around 110◦C. The presence of form **II** is confirmed by the occurrence of the exothermic event at 75◦C (cooling curve), indicating the transformation of form **II** to form **III**. The measured enthalpy value of −2.02 kJ mol−1 agrees with the enthalpy value of the transformation **III** → **II** (2.06 kJ mol−1 ), which can be determined on reheating. A more detailed study of this transformation has been reported just recently by us (Braun et al., 2017). In a separate experiment, the DSC heating run of **0.33- Hy** was stopped above the **Hy**dehy → **II** transition peak (2a) and the subsequent cooling curve shows the exothermic **II** → **III** transition (2b). The temperature range and enthalpy of this spontaneous transition confirm unambiguously that mainly form **II** is present after the hydrate is heated to about 150◦C. Form **III** transforms back to form **II** at 81◦C (1c and 2c) just about 6◦C

FIGURE 5 | Photomicrographs of DDS 0.33-Hy. Dehydration in the temperature range 40◦ -100◦C, Hydehy to form II transformation in the temperature range 110◦ -114◦C, and peritectic dissociation (crystals embedded in high-viscosity silicon oil) of 0.33-Hy to form II in the temperature range 115◦−132◦C.

above the **II** → **III** transition peak highlighting the weak kinetic control of this reversible solid-solid transformation.

By embedding the hydrate crystals into high viscosity silicon oil (HSM, **Figure 5**) or using hermetically sealed DSC crucibles (3, **Figure 6**) the peritectic dissociation process of **0.33-Hy** to form **II** can be observed or recorded around 125◦C, respectively. A fast nucleation and growth process of form **II** occurs, thus no clear melting process is observable by HSM and the phase transition is mainly indicated by an increase in birefringence (**Figure 5**). The measured heat of ∼5 kJ mol−1 can be related to the **0.33-Hy** to form **II** transformation, but also includes an unknown contribution from the enthalpy of solution of a fraction of the dehydration product in the liberated water. Due to the low water solubility of DDS and the low water stoichiometry of the hydrate the measured **0.33-Hy** to form **II** enthalpy is only slightly higher than the sum of the heats of **0.33-Hy** to **Hy**dehy and **Hy**dehy to form **II** transformations of ∼4 kJ mol−1 . Thus for DDS, it is possible to estimate the **0.33-Hy** to form **II** transition enthalpy directly in a hermetically sealed DSC crucible.

#### Moisture Dependent Stability of the Hydrate

The moisture sorption/desorption experiments of **0.33- Hy** (**Figure 7**) clearly indicate a non-stoichiometric hydration/dehydration behavior. The isotherm shows a continuous course and the water content of the hydrate adjusts quickly to a specific value if the RH is altered. It is particularly striking that the sorption and desorption isotherms are superimposable, i.e., that there is no hysteresis between the sorption and desorption curve. This fact and the short time to reach the equilibrium water content on changing RH suggests that the diffusion of water molecules into or out of the structure occurs without special constraints and without significant changes of the DDS framework. This observation is even more surprising because the water molecules are located at isolated-sites in the **0.33-Hy** structure (**Figure 3A**) and not in open structure voids (channels, layers), which is the commonly expected feature for hydrates with a non-stoichiometric dehydration behavior.

aReferred to a hydrate with 0.18 mol water/mol DDS.

bEstimated form 0.18-Hy.

c13.85 kJ mol-1–10.87 kJ mol-1 .

The automated gravimetric moisture sorption/desorption analysis of **0.33-Hy** was complemented with longer-term drying experiments at 0% RH (storage over P2O5) at 25◦ , 50◦ , and 75◦C to investigate whether **Hy**dehy transforms to another DDS anhydrate polymorph. **Hy**dehy is stable for at least 3 weeks at 25◦C and for at least 10 days at 50◦C. At 75◦C the transformation to form **III** starts within 1 week at 0%. No new polymorph emerged in the drying studies.

The changes seen in the gravimetric moisture sorption/desorption studies (**Figure 7**) were correlated with structural changes to **0.33-Hy** using variable-humidity PXRD at 25◦C (**Figure 8**, Supplementary Material for the PXRD patterns). In the case of the DDS hydrate only slight changes in peak positions and peak intensities can be observed with varying RH. Changes in lattice parameters were quantified by indexation and Rietveld refinement of the **0.33-Hy** PXRD patterns recorded at different RH values. The lattice parameters changed by max. 0.2% in the range 90% to 1%, and the cell volume by only 0.66%. Such small changes are in the range one would expect from a non-stoichiometric hydrate and they are for example of similar magnitude as measured for the non-stoichiometric hydrate HyA of brucine (Braun and Griesser, 2016a). Plotting the **0.33-Hy** cell volume in dependence of the RH (**Figure 8A**) perfectly reproduces the course of the sorption/desorption isotherms in **Figure 7**.

Using the optimized (PBE-TS) experimental structure as starting model, Rietveld refinements were performed with PXRD patterns of samples recorded in 10% RH steps during a desorption and sorption cycle. The aim of this study was to unravel whether the water position in the **0.33-Hy** varies depending on the RH conditions. **Figure 8C** exemplarily shows an overlay of the hydrate structures at 90 and 1% RH. The DDS molecules are superimposable and also the water shows hardly any positional variation with RH. The structures solved at different RH values differ solely in the fractional occupancy

factor to which the water molecule refined to (**Figure 8B**). It is surprising that this method works so well even though the water is only a very minor contributor to the overall electron density of the hydrate structure. The lowest water content observed for **0.33-Hy** in the RH dependent PXRD experiments was 0.005(12) mol of water per three moles of DDS, which is in reasonable agreement with the value determined in the automatic gravimetric sorption/desorption measurements (0.02 mol water per mol DDS) determined at the same RH. No phase change was observed in the moisture dependent PXRD experiments.

The question remains why the water egress/ingress in the **0.33-Hy** is fast, which is not expected from a hydrate where the water molecules are located at isolated-sites. **Figure 9A** illustrates a possible escape route of water molecules parallel to [011]. However, this route requires cooperative movement of the diaminophenyl moieties of the DDS molecules to temporarily open up diffusion pathways, similar to that seen in hydrates of βcyclodextrin (β-CD) (Steiner and Koellner, 1994), ciprofloxacin (Mafra et al., 2012) or DB7 (Braun et al., 2015). The potential energy surface scans of DDS reveal (**Figure 9B**) that considerable movement of the diaminophenyl moieties is possible with low energy cost (1Eintra), which we assume enables the local formation of the required diffusion pathways.

Sorption/desorption studies based on exposure of the solid material to various moisture conditions are controlled by kinetic parameters, which must be minimized in order to assess the thermodynamic equilibrium between the hydrate and a dehydrated state. This can be achieved for example by slurring the substance in solvents with different water activities, as has been demonstrated in previous studies (Ahlqvist and Taylor, 2002a,b; Braun et al., 2013; Braun and Griesser, 2016a). The most obvious indicator for the kinetic barrier is the hysteresis between the sorption and desorption curve observed in moisture sorption/desorption isotherms. The hysteresis can be extreme in stoichiometric hydrates and is usually small in hydrates with nonstoichiometric behavior. The isotherm of DDS **0.33-Hy** shows no hysteresis indicating that there is practically no kinetic barrier

between the ingress or release processes of the water molecules to/from the crystal structure but also that the phase is maintained and no transformation to another form with different structural features occurs. To test the phase behavior under different "moisture conditions" (water activities) in solvent systems, we subjected DDS to a slurry study in methanol/water mixtures of various compositions, covering the water activity (aw) range from 0 to 1.0 (corresponding to 0 to 100% RH) in 0.01 steps and the range 0.6 to 0.7 in 0.001 steps using form **III** as the starting form (**Figure 10**). Surprisingly, we obtained a new anhydrous form, named form **V** hereafter, which emerged as the only stable solid phase below a water activity of 0.64. At an aw > 0.66, **0.33-Hy** was obtained, suggesting that this hydrate is the stable form at high water activities and that the equilibrium between the DDS form **V** and the **0.33-Hy**, lies at an aw value of ∼0.655 at 25◦C.

Thermal analysis and PXRD characterization confirmed that the new form **V** does not correspond to any of the four known polymorphs (Brandstaetter-Kuhnert et al., 1963; Kuhnert-Brandstatter and Moser, 1979). A thorough characterization of the new form, which is obviously the thermodynamically most stable anhydrate form at RT, and phase interrelations to the known polymorphs will be addressed elsewhere.

# Estimation of Host-Host, Host-Water, and Water-Water Interaction Energies in Organic Hydrates

To understand the nature and stability of a hydrate it is important to consider the location and interaction energies of the water molecules in the framework of the host structure. If water molecules are located in open structural voids (tunnels or connected pockets) the term channel hydrate (Brittain et al., 2009) is commonly used. In such hydrates the water molecules may be mobile and may readily escape through these tunnels on modest increase in temperature or decrease in relative humidity (RH). In contrast, if the water molecules are located at isolatedsites (Brittain et al., 2009), it is assumed that water egress is not as facile and requires a considerable rearrangement of the hydrate packing to allow the release of water molecules. This rearrangement results mostly in the formation of a different packing arrangement or in a partial or total collapse of the structure yielding a disordered or amorphous state upon dehydration. The non-stoichiometric behavior of hydrates, where the water content in the structure depends on the water vapor pressure of the surrounding medium (atmosphere), is normally observed in channel hydrates and not in isolated-site hydrates. However, as demonstrated above, DDS **0.33-Hy** shows clearly the typical features of an isolated-site hydrate (**Figure 3A**) but on the other hand shows a non-stoichiometric (de)hydration behavior (see **Figure 7**) which is a contradiction and questions the common relation between structural features and the stability of hydrates.

To further clarify why the hydrate water can escape easily from the "isolated sites" in the **0.33-Hy**, without disrupting the structure, we estimated the pair-wise interaction energies for DDS and water molecules in the **0.33-Hy** structure (**Table 2**). The use of the CE-B3LYP energies and not a specific water potential, not considering specific effects (nanoscale dielectric responses of water) and three-body energy terms were justified by the fact that the contribution of the water to **0.33-Hy** was found to be in reasonable agreement with the experiment (**Table 3**). The water interactions contribute −13.85 kJ mol−1 to the **0.33-Hy** lattice. The CE-B3LYP energies of **0.33- Hy** (−142.87 kJ mol−1 **)** and **Hy**dehy (−132.00 kJ mol−1 , optimized RT structures) differ by 10.87 kJ mol−1 , ignoring the conformational changes which are expected to account for < 0.2 kJ mol−1 in the case of DDS. Thus, the sum of the interaction energies (Ecluster) roughly corresponds to the lattice energy. Furthermore, we calculated the intermolecular energies for water-host, water-water and host-host molecules for a series of well characterized organic hydrate systems (pharmaceuticals and model compounds) and contrasted the values to the DDS **0.33-Hy** (**Figure 11**, Supplementary Material). The chosen test set consists of stoichiometric and non-stoichiometric hydrates, as well as of channel and isolated-site hydrates. This analysis should indicate, whether it is possible to assess hydrate stability and/or the dehydration mechanism from general features of the hydrate structure and not the location of the water molecules in the structure alone.

In **Figure 11** the calculated interaction energies are grouped into contributions arising from host-host interactions and the incteractions including water molecules (host-water and water-water). Furthermore, the ratio between the host-host and water interactions has been calculated. The hydrates are ranked according to the compound:water ratio. For three of the chosen hydrates (dapsone, indinavir, and brucine) it is possible to remove the water molecules under maintaining the crystal structure, which is characteristic for a non-stoichiometric dehydration behavior. A grouping into channel and isolated-site hydrates is not always straight forward, in particular if more than one water molecule is present (di-, tri-hydrate, etc.,). However, based on the energetic contributions, host-water vs. waterwater, such a classification is facilitated as it can be expected that in isolated-site hydrates the host-water and in channel hydrates the water-water interactions predominate, respectively. Furthermore, the sum of host-host interactions are stronger in isolated-site hydrates than in channel hydrates.

A requirement for maintaining the crystal lattice upon dehydration is that the hydrate structure exhibits strong and/or a predominance of host-host interactions. Indeed, the three non-stoichiometric hydrates of the test set show the highest percentage of host-host interactions, i.e., ∼90% of the interaction energies for the DDS and indinavir hydrates. This value is lower for brucine (61.5%) but compared to dihydrates showing a stoichiometric behavior, brucine exhibits the most/strongest host-host interactions. The fact that the DDS and indinavir hydrates are isolated-site hydrates and brucine is a channel hydrate highlights that it is not possible to deduce whether a stoichiometic or non-stoichiometric dehydration mechanism

occurs from the location of the water molecules in the hydrate structure alone. Though, it is possible to rationalize a non-stoichiometric dehydration behavior from the energy contributions of the intermolecular interactions considering the compound:water ratios. On the other hand, the analysis shows that the moisture- or temperature dependent stability of hydrates cannot be derived from the interaction energy calculations. For example, the 5-flucytosine monohydrate (I) already dehydrates at RH values < 40%, whereas 4-aminoquinaldine monohydrate (Hy1A) dehydrates only at RH values below 10% (RT), but exhibits less energetic contributions from the host-host interactions than the 5-flucytosine monohydrate (I).

In the case of **0.33-Hy** the latter analysis (**Figure 10**) strongly indicates that water is only weakly bound and rationalizes the facile moisture- and temperature dependent dehydration behavior.

#### DISCUSSION

# Molecular Level Understanding of the Dehydration Mechanism Derived from the Hydrate Structure

Knowledge of how water vapor is sorbed by a hygroscopic material and how moisture affects the physical and chemical stability of a (pharmaceutical) product is a crucial question in developing drug products or preparations produced from other fine chemicals. Failures and time delays in product developments can be minimized or avoided with knowledge compiled in thorough solid state investigations. Hydrates require a thorough evaluation of their composition and stability under production relevant conditions and additionally the transformation pathways between different solid state forms of a compound, as well as their stability ranges, should be elucidated. This is mandatory to select the ideal solid state form that guarantees an optimal product performance and stability. In general, non-stoichiometric hydrates are undesired solid forms because any change in water vapor pressure of the surrounding medium causes a change in the water content of the substance, which can be critical for weighing and dosing operations and may thus lead to errors in any analyses, which require exact sample amounts. Such variations in the water content are often difficult to avoid as it requires special efforts to precisely control temperature and humidity conditions during processing and storage. Furthermore, the water molecules which have been released from such a hydrate may interact with other excipients in a drug formulation. Gravimetric moisture sorption/desorption studies (**Figure 7**), combined with environmental PXRD experiments (Supplementary Material) are the preferred analytical techniques for unraveling this nonstoichiometric behavior of a hydrate.

DDS **0.33-Hy** is a prime example for an isolated site hydrate with non-stoichiometric dehydration behavior. The latter behavior may be expected for hydrates where the water is located in open voids such as channels or layers. Thus, this study highlights that the popular structural classification of hydrates into isolated-site hydrates (water molecules are isolated from direct contact), channel hydrates (chains of water molecules) and ion-associated hydrates (metal ions are coordinated with water) cannot be directly related to the dehydration behavior or dehydration mechanism of a hydrate. However, by complementing the structural features with intermolecular energy calculations the observed dehydration behavior can be rationalized. As shown for DDS **0.33-Hy** the water molecules are only weakly bound (**Figure 11**), allowing a facile water egress/ingress with changing environmental conditions. Furthermore, the energy difference between the isomorphic dehydrate structure and anhydrate polymorphs is small. The lattice energy difference between **Hy**dehy and form **II** was calculated as 1.6 kJ mol−1 (PBE-TS, at −273◦C) and the transition enthalpy between **Hy**dehy and form **II** determined to be 1.08 ± 0.05 kJ mol−1 (experimentally measured at ∼100◦C). Thus, the calculations rationalize and indicate the non-stoichiometric dehydration mechanism.

# Computational Modeling of Pharmaceutical Hydrates

Modeling and predicting hydrate structures of pharmaceuticals still represent a big challenge in computational chemistry. Numerous potentials have been developed for modeling water (Guillot, 2002), however, there exists no method that can sufficiently model all its abnormalities. In organic hydrates the water molecules may be described as confined at nanoscales, implying frustration in their hydrogen-bonding coordination. Consequently, accurately modeling the water molecules in a hydrate lattice requires modeling efforts which go well beyond the methods applied for modeling the organic solid state (Reilly et al., 2016). In lead optimization is has been demonstrated that incorporating the three-body energy terms, and modeling frustration and frustration-related dielectric responses, significantly improves the results (Fernández, 2016, 2017; Fernandez and Scott, 2017). Considering and modeling the latter can be expected to significantly increase the accuracy of lattice and intermolecular energy calculations of water containing species, albeit at the expense of computational cost.

A major difficulty with using CSP in hydrate solid form screening is the computational expense in time and resources to generate the crystal energy landscape for all possible hydrate stoichiometries (mono-, di-, etc.,). However, solid form modeling at the electronic and atomistic level can provide vital support for unraveling the solid state for a compound which may not be achieved with experiments alone. A CSP study answers the question what types of crystal packings are favorable for a specific molecule, unraveling the compromises between close packing efficiency, conformational preferences and the different types of intermolecular interactions that can lead to feasible structures for a molecule (polymorph) or multi-component system (salt, solvate, hydrate, co-crystal). It should be stressed that CSP aids the interpretation of the experimental data (Price et al., 2014) and can guide experimentalists to find new solid forms (Arlin et al., 2011; Braun et al., 2014b, 2016; Neumann et al., 2015; Srirambhatla et al., 2016).

To significantly reduce the computational cost, and to make the calculations feasible, we did not attempt to computationally screen for different hydrate stoichiometries (Braun et al., 2011b) for the chosen model compound DDS, but used the crystal energy landscape of the 1:1 stoichiometry (monohydrate) as a guidance for hydrate formation. The monohydrate crystal energy landscape (**Figure 2**) shows only one hydrate structure that is more stable than the non-solvated form **III** and thus indicates hydrate formation.

# CONCLUSIONS

4,4′ -Diaminodiphenyl sulfone (DDS) forms a non-stoichiometric hydrate, with a water content of 0–0.33 mol of water per mol of DDS. The upper limit of this ratio is obvious from the features of the crystal structure, but it is surprising that the structurally isolated and hydrogen bonded water molecules can easily leave and enter the structure, which is indicated by the continuous change in water content when the hydrate is exposed to different RH values. This observation highlights that it is not advisable to make assumptions about the dehydration behavior based on the location of the water molecules in the structure alone. However, supported by intermolecular energy interaction calculations (host-host, water-host and water-water) and by comparing the lattice energies of the isomorphic dehydrate (hydrate without water) and anhydrate polymorph(s) of the same compound it is possible to rationalize and to potentially predict a non-stoichiometric dehydration behavior. Furthermore, this study shows that even though CSP has been performed with only one hydrate stoichiometry (here monohydrate) the outcome may be sufficient to get insight into the hydrate formation potential of a compound. However, such a limited approach requires a thorough analysis of the computed structures.

In our opinion, a sound understanding of hydrates and their often complex behavior can only be achieved by a full multidisciplinary investigation, including structural, moisture- and temperature dependent studies combined with modeling. Such an understanding may be mandatory to avoid complications during processing, storing and handling of a hydrate.

# AUTHOR CONTRIBUTIONS

DB conceived and designed the research and headed, wrote and revised the manuscript, while UG contributed to the writing and the revision of the article.

### FUNDING

DB gratefully acknowledges funding by the Elise Richter program of the Austrian Science Fund (FWF, project V436-N34). The computational results presented have been achieved using the HPC infrastructure LEO of the University of Innsbruck.

#### ACKNOWLEDGMENTS

The authors are grateful to Profs. C. C. Pantelides and C. S. Adjiman (Imperial College London) for the use of the CrystalPredictor and CrystalOptimizer programs, Prof. S. L.

#### REFERENCES

Bernstein, J. (2002). Polymorphism in Molecular Crystals. Oxford: Clarendon Press.

Price (University College London) for the use of the DMACRYS program and Elisabeth Achammer for support in few of the calculations.

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fchem. 2018.00031/full#supplementary-material

kinetic relationship between pyrogallol and its tetarto-hydrate. Cryst. Growth Des. 13, 4071–4083. doi: 10.1021/cg4009015

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2018 Braun and Griesser. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Structure-Activity Relationship Analysis of 3-Phenylcoumarin-Based Monoamine Oxidase B Inhibitors

Sanna Rauhamäki 1 , Pekka A. Postila1 , Sanna Niinivehmas 1 , Sami Kortet 1,2 , Emmi Schildt 1,2, Mira Pasanen1 , Elangovan Manivannan1,3, Mira Ahinko1 , Pasi Koskimies 4 , Niina Nyberg5 , Pasi Huuskonen5 , Elina Multamäki 1 , Markku Pasanen5 , Risto O. Juvonen5 , Hannu Raunio5 , Juhani Huuskonen2 \* and Olli T. Pentikäinen1,6 \*

#### Edited by:

Daniela Schuster, Paracelsus Private Medical University of Salzburg, Austria

#### Reviewed by:

Outi Maija Helena Salo-Ahen, Åbo Akademi University, Finland Justin W. Hicks, Lawson Health Research Institute, Canada Julian Fuchs, University of Innsbruck, Austria

#### \*Correspondence:

Juhani Huuskonen<EMAIL_ADDRESS>Olli T. Pentikäinen<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Medicinal and Pharmaceutical Chemistry, a section of the journal Frontiers in Chemistry

Received: 10 January 2018 Accepted: 14 February 2018 Published: 02 March 2018

#### Citation:

Rauhamäki S, Postila PA, Niinivehmas S, Kortet S, Schildt E, Pasanen M, Manivannan E, Ahinko M, Koskimies P, Nyberg N, Huuskonen P, Multamäki E, Pasanen M, Juvonen RO, Raunio H, Huuskonen J and Pentikäinen OT (2018) Structure-Activity Relationship Analysis of 3-Phenylcoumarin-Based Monoamine Oxidase B Inhibitors. Front. Chem. 6:41. doi: 10.3389/fchem.2018.00041

Frontiers in Chemistry | www.frontiersin.org 1 March 2018 | Volume 6 | Article 41

1 Computational Bioscience Laboratory, Department of Biological and Environmental Science & Nanoscience Center, University of Jyväskylä, Jyväskylä, Finland, 2 Department of Chemistry & Nanoscience Center, University of Jyväskylä, Jyväskylä, Finland, 3 School of Pharmacy, Devi Ahilya University, Madhya Pradesh, India, 4 Forendo Pharma Ltd., Turku, Finland, 5 School of Pharmacy, University of Eastern Finland, Kuopio, Finland, 6 MedChem.fi, Institute of Biomedicine, University of Turku, Turku, Finland

Monoamine oxidase B (MAO-B) catalyzes deamination of monoamines such as neurotransmitters dopamine and norepinephrine. Accordingly, small-molecule MAO-B inhibitors potentially alleviate the symptoms of dopamine-linked neuropathologies such as depression or Parkinson's disease. Coumarin with a functionalized 3-phenyl ring system is a promising scaffold for building potent MAO-B inhibitors. Here, a vast set of 3-phenylcoumarin derivatives was designed using virtual combinatorial chemistry or rationally de novo and synthesized using microwave chemistry. The derivatives inhibited the MAO-B at 100 nM−1µM. The IC50 value of the most potent derivative 1 was 56 nM. A docking-based structure-activity relationship analysis summarizes the atom-level determinants of the MAO-B inhibition by the derivatives. Finally, the cross-reactivity of the derivatives was tested against monoamine oxidase A and a specific subset of enzymes linked to estradiol metabolism, known to have coumarin-based inhibitors. Overall, the results indicate that the 3-phenylcoumarins, especially derivative 1, present unique pharmacological features worth considering in future drug development.

Keywords: 3-phenylcoumarin, monoamine oxidase B (MAO-B), structure-activity relationship (SAR), virtual drug design, Parkinson's disease

# INTRODUCTION

During neuronal signaling, neurotransmitters are released from the presynaptic cell into the synaptic cleft, from where they bind into their specific receptors embedded on the postsynaptic membrane. The membrane lipid bilayer, especially its anionic phospholipid constituents, has been suggested to play a role in the small-molecule entry processes with the receptors (Orłowski et al., 2012; Postila et al., 2016; Mokkila et al., 2017). Moreover, to assure that the neurotransmission remains transient, the neurotransmitters are removed quickly from the synaptic cleft via enzymatic degradation and cellular uptake.

When inside the neuron, monoamine neurotransmitters such as norepinephrine and dopamine are either recycled or destined for deactivation through oxidative deamination (RCH2NHR' + H2O + O2 = RCHO + R'NH2 + H2O2) by monoamine oxidases A (MAO-A; E.C. <IP_ADDRESS>) and B (MAO-B; E.C. <IP_ADDRESS>). These enzymes are integral monotopic proteins that anchor themselves as dimers onto the mitochondrial outer membrane surface by protruding their α-helical C-termini into the lipid bilayer (**Figure 1A**). Moreover, both subtypes A and B deaminate preferentially their respective substrates to aldehydes: MAO-A catalyzes serotonin, norepinephrine, and to some extent dopamine; and MAO-B catalyzes dopamine, phenethylamine, benzylamine and to a lesser extent norepinephrine (Shih et al., 1999; Edmondson et al., 2005; Gaweska and Fitzpatrick, 2011).

The MAO-B, which is the target of this study, is connected to neurodegenerative disorders such as Alzheimer's disease but also mental disorders such as schizophrenia, anorexia nervosa, depression and attention deficit disorder. In all of these conditions, the involvement of MAO-B in the metabolism of dopamine and other amines is in a key role (Youdim et al., 2006; Carradori and Silvestri, 2015). For instance, due to gliosis associated with Parkinson's disease, increased levels of MAO-B speed up degradation of dopamine in the motor neurons. MAO-B inhibitors decrease the degradation and boost dopamine concentration in the synapse. Thus, instead of introducing more dopamine, the neurotransmitter levels are elevated by inhibiting MAO-B. As a result, MAO-B inhibitors such as selegiline are used in treatment of Parkinson's disease, moreover, their neuroprotective effects can benefit Alzheimer's disease patients (Youdim et al., 2006). Due to these hepatotoxic effects of irreversibly binding MAO inhibitors, reversible inhibitors such as moclobemide were developed (Youdim et al., 2006; Finberg and Rabey, 2016). The MAO inhibitors can exhibit selectivity toward MAO-A (moclobemide) or MAO-B (pargyline, selegiline) or be non-selective (phenelzine, tranylcypromine). The selectivity, which can be lost in high dosages, is important for avoiding MAO-A inhibition related cheese effect (Youdim et al., 2006; Finberg and Rabey, 2016).

A vast amount of different types of MAO inhibitors are described in the literature and for example the ChEMBL database lists inhibition data for thousands of compounds. The specific problem in the development of MAO-specific ligands is that the promising compounds have potential to become active on other amine oxidases such as vascular adhesion protein 1 (Nurminen et al., 2010, 2011). Here, the aim was to probe the MAO-B activity and selectivity effects of different substitutions on the coumarin core by focusing, especially, on the 3-phenylcoumarin (or 3-arylcoumarin). Notably, there exist two X-ray crystal structures with structurally related coumarin analogs in which 3-chlorobenzyloxy groups are attached at the C7-position (**Figures 1B–D**). The studied set of 3-phenylcoumarin derivatives with different R1-R7 groups (**Figure 1E**) introduced in this study make an important addition to the earlier studies in which the potential of coumarin core, including 61 3-phenylcoumarin derivatives (Matos et al., 2009b, 2010, 2011a,b; Santana et al., 2010; Serra et al., 2012; Viña et al., 2012a,b), to block MAO-A and MAO-B has been explored (Borges et al., 2005; Catto et al., 2006; Matos et al., 2009a, 2010, 2011a; Serra et al., 2012; Ferino et al., 2013; Joao Matos et al., 2013; Patil et al., 2013). The compounds were designed using virtual combinatorial chemistry or rationally de novo and binding were probed via molecular docking prior to synthesis or in vitro testing.

Initially, 52 derivatives of the 3-phenylcoumarin core were synthesized and tested here for the first time for MAO-B inhibition using a specifically tailored spectrophotometric assay (Supplementary Table S1) (Holt et al., 1997). Next, 24 of the derivatives (**Figure 2**, **Table 1**), producing >70% inhibition at 10µM, were selected for further analysis. These derivatives inhibited MAO-B at a ∼100 nM to ∼1µM range, while the most potent derivative **1** produces ∼50–60 nM inhibition (**Table 1**, **Figure 2**). Finally, the potency of the derivatives for inhibiting estrogen receptor (ER), 17-β-hydroxysteroid dehydrogenase 1 (HSD1), aromatase (CYP19A1), and cytochrome P450 1A2 (CYP1A2), the topics of both our prior (Niinivehmas et al., 2016) and ongoing studies, was also considered. A dockingbased structure-activity relationship (SAR) analysis (**Figure 2**) was performed with all of the synthetized 3-phenylcoumarins focusing mainly on the 24 most potent compounds.

In short, this study explores thoroughly the pharmacological potential of 3-phenylcoumarin (**Figure 1E**) for blocking the MAO-B activity (**Table 1**, Supplementary Table S1) and, furthermore, explains the basis of the inhibitory effect on the atom level.

### MATERIALS AND METHODS

### Virtual Combinatorial Chemistry

The 3-phenylcoumarin was chosen as the scaffold of interest for building new MAO-B-specific inhibitors (see section The Alignment of the 3-Phenylcoumarin Scaffold at the Active Site). The analogs were designed using virtual combinatorial chemistry or virtual synthesis. In the initial stages, methoxy group was included at the R1 or R2 position (**Figure 1E**) in the coumarin core due to its predicted favorability at the active site. The R4-R7 substituents of the 3-phenyl ring (**Figure 1E**) were designed by combining phenylacetic acid with either 6-methoxycoumarin or 7-methoxycoumarin. The preliminary combinatorial compound library was generated using MAESTRO version 9.3 CombiGlide (CombiGlide, version 2.8, Schrödinger, LLC, New York, NY, USA) and Combinatorial Screening module. The compounds were docked with GLIDE and scored using GlideScore. Some of these derivatives with promising potency and selectivity profile in this study (**8**, **10**, **25**, **37**) were eventually synthesized, albeit using different chemistry (see section Chemical Procedure), and tested in vitro. Majority of the final derivatives were designed de novo after performing the initial docking simulations with the virtual synthesis products.

**Abbreviations:** MAO-A, monoamine oxidase A; MAO-B, monoamine oxidase B; HSD1 or 17-β-HSD1, 17-β-hydroxysteroid dehydrogenase 1; ER, estrogen receptor; CYP1A2, cytochrome P450 1A2; CYP19A1, aromatase; SAR, structureactivity relationship.

established inhibitors in comparison to the docking-based pose of the scaffold. Moreover, the phenyl rings of C17 and C18 are attached via ether bonds to the coumarin's C7-position instead of C3-position used with the inhibitors introduced in this study. (E) The 2D structure of the 3-phenylcoumarin scaffold indicating the positions of the functional R1-R7 groups.

# Chemical Procedure

All reactions were carried out using commercial materials (Sigma-Aldrich, Mannheim, Germany) and reagents without further purification unless otherwise noted. Reaction mixtures were heated by the CEM Discover microwave apparatus. All reactions were monitored by thin layer chromatography (TLC) on silica gel plates. 1H NMR and 13C NMR data was recorded on a Bruker Avance 400 MHz spectrometer or Bruker Avance III 300 MHz spectrometer. Chemical shifts are expressed in parts per million values (ppm) and are designated as s (singlet), br s (broad singlet), d (doublet), dd (double doublet), and t (triplet). Coupling constants (J) are expressed as values in hertz (Hz). The mass spectra were recorded using Micromass LCT ESI-TOF equipment. Elemental analyses were done with Elementar Vario EL III elemental analyzer. The coumarin derivatives were synthesized using Perkin-Oglialor condensation reaction. The method was developed from the earlier published procedures and transferred to microwave reactor and it was published earlier by authors (Niinivehmas et al., 2016).

A typical procedure: A mixture of salicylaldehyde derivative (2 mmol) and phenyl acetic acid derivative (2.1 mmol), acetic acid anhydride (0.6 ml), and triethylamine (0.36 ml) were placed in a microwave reactor tube and this mixture was heated at 100– 170◦C with microwave apparatus (100–200 W) for 10–20 min. After cooling, 2 ml of 10% NaHCO3 solution was added and the precipitate was filtered, dried and recrystallized from EtOH/H2O or acetone/H2O mixture. The acetyl group(s) were removed by treating the compound with 2 M MeOH/NaOH(aq) (1:1) solution for 30–60 min at r.t. The solution was acidified with 2 M HCl(aq,) and the precipitate was filtered and recrystallized if needed.

Based on the elemental analysis and/or 1H-NMR the purity of compounds was >95%.

**6-methoxy-3-(4-(trifluoromethyl)phenyl)-2H-chromen-2-one (1).** Yield: 76%; 1H-NMR (400 MHz, CDCl3) δ: 3.86 (s, 3H, CH3O-), 6.99 (s, 1H, H-5), 7.14 (d, 1H, J 3 = 7.7 Hz, H-7), 7.29 (d, J 3 = 8.9 Hz, H-8), 7.69 (d, 2H, J 3 = 7.9 Hz, H-2', H-6'), 7.58 (m, 3H, H-4, H-3', H-5'); 13C-NMR (100.6 MHz, CDCl3) δ: 55.99, 110.24, 117.73, 119.78, 120.02, 125.51 (q, J C−F = 4 Hz), 127.37, 129.05, 130.85 (q, J C−F = 32 Hz), 138.41, 140.88, 148.33, 156.44, 160.42. HRMS(ESI): calc. for C17H11F3O3Na1 343.0558, found 343.0574; elemental anal. for C17H11F3O3, calc. C% 63.76, H% 3.46, found C% 63.25, H% 3.51.

the chemical similarity of the R1-R7 substituents (Figure 1E). See Table 1 for the detailed activity data.

TABLE 1 | The activity data on the 24 most potent 3-phenylcoumarin derivatives.

N/A = not available. Controls: (1)pargyline, (2)clorgyline, (3) kit control. The compounds are grouped (A–F) based on the chemical similarity of the R1–R7 substituents (Figure 1E).

**6-methoxy-3-(4-(trifluoromethyl)phenyl)-2H-chromen-2 one (2).** Yield: 80%; 1H-NMR (300 MHz, d6 -DSMO) δ: 3.88 (s, 3H, CH3O-), 6.99 (s, 1H, J 3 = 8.7 Hz, J 4 = 2.4 Hz, H-6), 7.03 (d, 1H, J 4 = 2.4 Hz, H-7), 7.71 (d, J 3 = 8.6 Hz, H-8), 7.79 (d, 2H, J 3 = 8.3 Hz, H-2', H-6'), 7.93 (d, 2H, H-3', H-5'), 8.32 (s, 1H, H-4); 13C-NMR (75.5 MHz, d6 -DMSO) δ: 55.97, 100.25, 112.80, 121.57, 122.38, 120.02, 124.97 (q, J C−F = 4 Hz), 128.29 (q, J C−F = 32 Hz), 128.97, 129.99, 139.01, 142.10, 155.09, 159.62, 162.82. HRMS(ESI) calc for C17H11F3O3Na1 [M + Na]+: 343.05525, found 343.05610.

#### **2-oxo-3-(4-(trifluoromethoxy)phenyl)-2H-chromen-7-yl**

**acetate (3).** (Dobelmann-Mara et al., 2017) Yield: 54%; %; 1H-NMR (400 MHz, d6 -DMSO) δ: 2.27 (s, 3H, CH3C(O)O-), 7.20 (dd, 1H, J 3 = Hz, J 4 = Hz, H-6), 7.33 (d, 1H, J 4 = Hz, H-8), 7.47 (d, 2H, J 3 = Hz, H-3', H-5'), 7.81 (d, 1H, J 3 = 8.4 Hz, H-5), 8.32 (s, 1H, H-4); 13C-NMR (100 MHz, d6 -DMSO) δ: 20.86 109.74, 117.23, 118.88, 120.75, 124.84, 129.42, 129.60, 130.52, 133.85, 140.73, 148.35, 152.90, 153.55, 159.40, 168.78; HRMS(ESI) calc. for C18H11F3O5Na1 [M + Na]+ 387.0457, found 387.0481.

#### **6-methoxy-3-(4-(trifluoromethoxy)phenyl)-2H-chromen-**

**2-one (4).** Yield: 52%; 1H-NMR (400 MHz, CDCl3) δ: 3.86 (s, 3H, CH3O-), 6.98 (d, 1H, J 4 = 3 Hz, H-5), 7.12 (dd, J 3 = 9.1 Hz, J 4 = 3 Hz, H-7), 7.27-7.30 (m, 3H, H-8, H-3', H-5'), 7.74 (d, 2H, J 3 = 8.9 Hz, H-2', H-6'); 7.77 (s, 1H, H-4); 13C-NMR (100 MHz, CDCl3) δ: 55.99, 110.16, 117.70, 119.68, 119.92, 120.97, 127.41, 130.26, 133.51, 140.20, 148.21, 149.67, 156.41, 160.65. HRMS(ESI) calc for C17H11F3O4Na1 [M + Na]+: 359.05071, found 359.05260. elemental anal. for C17H11F3O4·0.5H2O, calc. C% 59.14, H% 3.50, found C% 58.99, H% 3.25.

**6-methyl-3-(4-(trifluoromethyl)phenyl)-2H-chromen-2 one (5).** Yield: 54%; 1H-NMR (400 MHz, CDCl3) δ: 7.27 (d, 1H, J 4 = 2.2 Hz, H-5), 7.35-7.38 (m, 2H, H-7, H-8), 7.70 (d, J 3 = 8.2 Hz, H-2', H-6'), 7.82 (m, 3H, H-4, H-3', H-5'); 13C-NMR (100 MHz, CDCl3) δ: 20.92, 116.46, 119.22, 122.80, 125.53 (q, J C−F = 4 Hz), 126.98, 128.07, 129.05, 130.80 (q, J C−F = 33 Hz), 133.29, 134.62, 138.50, 141.08, 152.04 160.53; HRMS(ESI) calc for C17H12Cl2O4Na1 [M + Na]+: 373.0005, found 372.9998.

**2-fluoro-4-(7-methoxy-2-oxo-2H-chromen-3-yl)phenyl acetate (6).**  HRMS(ESI) calc for C18H13F1O5Na1 [M + Na]+: 351.06447, found 351.06240; elemental anal. for C18H13F1O5 C% 65.85, H% 3.99, found C% 65.28 H% 4.02.

**4-(6,8-dichloro-2-oxo-2H-chromen-3-yl)-2-fluorophenyl acetate (7).** Yield 58%; 1H-NMR (400 MHz, d6 -DMSO) δ: 2.36 (s, 3H, CH3C(O)O-), 7.43 (dd, J 3 = 9.3 Hz, J H−F = 8.3 Hz, H-5'), 7.67 (ddd, 1H, J 3 = 8.4 Hz, J 4 = 2.1 Hz, J H−F = 0.8 Hz, H-6'), 7.74 (dd, J H−F = 11.8 Hz, J 4 = 2.0 Hz, H-3'), 7.84 (d, 1H, J 4 = 2.4 Hz, H-7), 7.97 (d, 1H, J 4 = 2.4 Hz, H-5), 8.32 (s, 1H, H-4); 13C-NMR (100 MHz, d6 -DMSO) δ: 20.72, 117.23 (d, J C−F = 21 Hz), 121.13, 122.17, 124.65, 125.74 (d, J C−F = 3.3 Hz), 127.29, 128.80, 131.47, 133.70 (d, J C−F = 7.7 Hz), 138.50 (d, J C−F = 12.9 Hz), 140.12, 147.94, 152.30, 154.75. 158.73; HRMS(ESI): calc. for C17H9Cl2F1O4Na1 [M + Na]+: 388.9760, found 388. 9762.

**6-methoxy-3-(3-methoxyphenyl)-2H-chromen-2-one (8).** Yield 78%; 1H-NMR (400 MHz, CDCl3) δ: 3.85 (s, 3H, CH3O-Ph), 3.86 (s, 3H, CH3O-Ph), 6.93-6.97 (m, 2H, H-4', H-5), 7.10 (dd, 1H, J 3 = 9.0, Hz, J 4 = 1.9 Hz, H-7), 7.25-7.29 (m, 3H, H-8, H-2', H-6'), 7.35 (t, 1H, J 3 = 8.2 Hz, H-5'), 7.76 (s, 1H, H-4); 13C-NMR (100 MHz, CDCl3) δ: 55.69, 56.18, 110.28, 114.57, 114.88, 117.78, 119.55, 120.28, 121.26, 128.80, 129.79, 136.43, 140.13, 148.34, 156.47, 159.88, 160.91; HRMS(ESI): calc. for C17H14O4Na1 [M + Na]+: 305.07898, found 305.07950; elemental anal. for C14H14O4 calc. C% 72.33, H% 5.00, found C% 72.41, H% 4.88.

#### **3-(3,5-dimethoxyphenyl)-6-methoxy-2H-chromen-2-**

**one (9).** (Vilar et al., 2006) Yield 59%; 1H-NMR (400 MHz,

d 6 -DMSO) δ: 3.79 (s, 6H, CH3O-Ph), 3.82 (s, 3H, CH3O-Ph), 6.56 (t, 1H, J 4 = 2.3 Hz, H-4'), 6.89 (d, 2H, J 4 = 2.3 Hz, H-2', H-6'), 7.20 (dd, 1H, J 3 = 9.0 Hz, J 4 = 3.0 Hz, H-7), 7.31 (d, 1H, J 4 = 3.0 Hz, H-5), 7.36 (d, 1H, J 3 = 9.0 Hz, H-8), 8.23 (s, 1H, H-4); 13C-NMR (100 MHz, d6 -DMSO) δ: 55.30, 55.66, 100.48, 106.71, 110.69, 116.90, 119.36, 119.78, 126.75, 136.44, 140.66, 147.33, 155.62, 159.53, 160.16; HRMS(ESI): calc. for C18H16O5Na1 [M + Na]+: 335.08954, found 305.09010; elemental anal. for C14H14O4 calc. C% 69.22, H% 5.16, found C% 68.80, H% 5.14.

**6-methoxy-3-(4-methoxyphenyl)-2H-chromen-2-one (10).** (Prendergast, 2001; Ferino et al., 2013) Yield 79%; 1H-NMR (400 MHz, CDCl3) δ: 3.847 (s, 3H, CH3O-Ph), 3.852 (s, 3H, CH3O-Ph), 6.95-6.98 (m, 3H, H-5, H-3', H-5'), 7.07 (dd, 1H, J 3 = 9.0 Hz, J 4 = 2.9 Hz, H-7), 7.27 (d, 1H, J 4 = 8.8 Hz, H-5), 7.66 (d, 2H, J 3 = 8.9 Hz, H-2', H-6'), 7.70 (s, 1H, H-4); 13C-NMR (100 MHz, CDCl3) δ:55.69, 56.16, 110.11, 114.23, 117.69, 119.05, 120.51, 127.47, 128.49, 130.18, 138.63, 148.11, 156.44, 160.49, 161.24; HRMS(ESI): calc. for C17H14O4Na1 [M + Na]+: 305.07898, found 305.07910; elemental anal. for C17H14O4 calc. C% 72.33, H% 5.00, found C% 72.34, H% 4.86.

**3-(3-methoxyphenyl)-2H-chromen-2-one (11).** (Kirkiacharian et al., 1999) Yield 81%; 1H-NMR (400 MHz, CDCl3) δ: 3.86 (s, 3H, CH3O-Ph), 6.95 (ddd, 1H, J 3 = 8.2 Hz, J 4 = 2.3 Hz, J 4 = 2.5 Hz, H-4'), 7.26-7.37 (m, 5H, H-6, H-8, H-2', H-5', H-6'), 7.51-7.53 (m, 2H, H-5, H-7), 7.81 (s, 1H, H-4); 13C-NMR (100 MHz, CDCl3) δ: 55.69, 114.56, 114.86, 116.76, 119.94, 121.24, 124.81, 128.26, 128.49, 129.80, 131.76, 136.35, 140.28, 153.85, 159.88, 160.76; HRMS(ESI): calc. for C16H12O3Na1 [M + Na]+: 275.06841, found 275.06540; elemental anal. for C16H12O3 calc. C% 76.18, H% 4.79, found C% 75.94, H% 4.67.

**7-hydroxy-3-(4-methoxyphenyl)-2H-chromen-2-one (12).** (Prendergast, 2001) Yield 81%; 1H-NMR (400 MHz, d6 -DMSO) δ: 3.79 (s, 3H, CH3O-Ph), 6.74 (s, 1H, H-8), 6.81 (d, 1H, J 3 = 8.5 Hz, H-6), 6.99 (d, 2H, J 3 = 8.3 Hz, H-3', H-5'), 7.57 (d, 1H, J 3 = 8.4 Hz, H-5), 7.65 (d, 2H, J 3 = 8.3 Hz, H-2, H-6'), 8.08 (s, 1H, H-4), 10.54 (s, 1H, HO-Ph); 13C-NMR (100 MHz, d 6 -DMSO) δ: 55.18, 101.66, 112.10, 113.29, 113.61, 121.84, 127.30, 129.48, 129.70, 139.73, 154.63, 159.14, 160.20, 160.88; HRMS(ESI): calc. for C16H12O4Na1 [M + Na]+: 291.06333, found 291.06160.

**3-(4-methoxyphenyl)-2-oxo-2H-chromen-7-yl acetate (13).** (Bhandri et al., 1949) Yield 67%; 1H-NMR (400 MHz, d6 -DMSO) δ: 7.02 (d, 2H, J 3 = 7.8 Hz, H-3', H-5'), 7.17 (d, 1H, J 3 = 8.3 Hz, H-6), 7.29 (d, 1H, H-8), 7.69 (d, 2H, J 3 = 7.8 Hz, H-2', H-6'), 7.79 (d, 1H, J 3 = 8.2 Hz, H-5), 8.19 (s, 1H, H-4); 13C-NMR (100 MHz, d 6 -DMSO) δ: 20.85, 55.22, 109.57, 113.68, 117.49, 118.68, 125.69, 126.72, 129.19, 129.75, 138.62, 152.36, 153.15, 159.59, 168.81; HRMS (ESI): Calc for C18H14O5Na1 [M + Na]+: 333.07389, found 333.07220. Elemental analysis for C18H14O5 calc C% 69.67 H% 4.55, found C% 69.58 H% 4.52.

**3-(4-methoxyphenyl)-2-oxo-2H-chromen-6-yl acetate (14).** Yield 34%; 1H-NMR (300 MHz, d6-DMSO) δ: 2.31 (s, 3H, CH3C(O)O-), 3.81 (s, 3H, CH3O-), 7.03 (d, 2H, J3 = 8.7 Hz, H-3', H-5'), 7.37 (dd, 1H, J3 = 8.9 Hz, J4 = 2.5 Hz, H-7), 7.47 (d, 1H, J3 = 8.9 Hz, H-8), 7.54 (d, 1H, J4 = 2.5 Hz, H-5), 7.70 (d, 2H, J3 = 8.7 Hz, H-2', H-6'), 8.15 (s, 1H, H-5); 13C-NMR (75 MHz, d6-DMSO) δ: 20.73, 55.21, 113.68, 116.83, 120.07, 120.53, 125.00, 126.61, 127.03, 129.84, 138.30, 146.39, 150.18, 159.64, 159.71, 169.22. HRMS (ESI): Calc for C18H14O5 [M + H]+: 311.0914, found 311.0908.

**6-methoxy-3-(2,4,5-trifluorophenyl)-2H-chromen-2-one (15).** Yield 80%; 1H-NMR (400 MHz, d6 -DMSO) δ: 3.81 (s, 3H, CH3O-Ph), 7.26 (dd, 1H, J 3 = 9.0 Hz, J 4 = 3.0 Hz, H-7), 7.31 (d, 1H, J 4 = 3.0 Hz, H-5), 7.41 (d, 1H, J 3 = 9.0 Hz, H-8), 7.64-7.77 (m, 2H, H-2', H-6'), 8.18 (s, 1H, H-4); 13C-NMR (100 MHz, d 6 -DMSO) δ: 55.73, 106.31 (dd, J C−F = 21 Hz, J C−F = 22 Hz), 110.90, 117.25, 119.12, 119.39, 119.55, 120.07, 120.91, 143.74, 145.70 (d, J C−F = 242 Hz), 147.64, 149.34 (J C−F = 252 Hz), 155.13 (J C−F = 248 Hz), 155.79, 158.78. HRMS (ESI): Calc for C16H9F3O3Na1 [M + Na]+: 329.04015, found 329.04090. Elemental analysis for C16H9F3O3: calc C% 62.75 H% 2.96, found C% 62.62 H% 3.15.

**7-methoxy-3-(2,4,5-trifluorophenyl)-2H-chromen-2-one (16).** Yield 85 %; 1H-NMR (300 MHz, d6 -DMSO) δ: 3.88 (s, 3H, CH3O-Ph), 7.00 (dd, 1H, J 3 = 8.6 Hz, J 4 = 2.4 Hz, H-6), 7.06 (d, 1H, J 4 = 2.3 Hz, H-8), 7.61-7.6 (m, 3H, H-5, H-2', H-6'), 8.17 (s, 1H, H-4); 13C-NMR (75.5 MHz, d6 -DMSO) δ: 56.02, 100.49, 106.21 (dd, J C−F = 21 Hz, J C−F = 21 Hz), 112.24, 112.85, 116.85, 119.30, 119.57, 129.95, 144.06, 145.67 (d, J C−F = 242 Hz), 148.93 (d, J C−F = 250) Hz, 155.10 (d, J C−F = 245 Hz), 155.22, 158.89, 162.98; HRMS (ESI): Calc for C16H9F3O3Na1 [M + Na]+: 329.04015, found 329.03980.

**3-(4-(dimethylamino)phenyl)-7-hydroxy-2H-chromen-2-one (17).** (Kirkiacharian et al., 2003) In the first step 7-acetoxy-3-(4-(dimethylamino)phenyl)-2H-chromen-2one was obtained.  In the second step 7-hydroxy-3-(4-(dimethylamino)phenyl)-2H-chromen-2one was obtained. Yield: 85% yellow solid; 1H-NMR (400 MHz, d 6 -DMSO) δ: 2.94 (s, 6H, (CH3)2N-), 6.72 (d, J 4 = 2.3 Hz, 1H, H-8), 6.75 (d, J 3 = 9.0 Hz, 2H, H-2', H-6'), 6.79 (dd, J 3 = 8.4 Hz, J 4 = 2.3 Hz, 1H, H-5),), 7.55 (d, J 3 = 8.5 Hz, 1H, H-5), 7.58 (d, J 3 = 9.0 Hz, 2H, H-3', H-5'), 7.99 (s, 1H, H-4); 13C-NMR (100.6 MHz, d6 -DMSO) δ: 39.92, 101.59, 112.33, 113.16, 122.30, 122.32, 129.34, 137.83, 150.07, 154.27, 160.30, 160.41; HRMS (ESI): Calc for C17H15N1O3Na1 [M + Na]+: 304.09496, found 304.09480; elemental anal. for C17H15N1O3, calc. C% 72.58, H% 5.37, N% 4.98, found C% 72.45, H% 5.40, N% 5.15.

**3-(4-(dimethylamino)phenyl)-6-methoxy-2H-chromen-2 one (18).** Yield 55%; 1H-NMR (400 MHz, d6 -DMSO) δ: 2.96 (s, 6H, (CH3)2N-Ph), 3.81 (s, 3H, CH3O-Ph), 6.77 (d, 2H, J 3 = Hz, H-3', H-5'), 7.14 (dd, 1H, J 3 = 3.0 Hz, J 4 = 9.0 Hz, H-7), 7.28 (d, 1H, J 4 = 3.0 Hz, H-5), 7.33 (d, 1H, J 3 = 9.0 Hz, H-8), 7.63 (d, 2H, J 3 = 9.0 Hz, H-2', H-6'), 8.06 (s, 1H, H-4); 13C-NMR (100.6 MHz, d6 -DMSO) δ: 39.93, 110.27, 111.59, 116.68, 118.16, 120.35, 121.73, 126.96, 129.15, 136.79, 146.79, 150.46, 155.59, 160.06; HRMS (ESI): Calc for C18H17N1O3Na1 [M + Na]+: 318.11061, found 318.11050; elemental anal. for C18H17N1O3, calc. C% 73.20, H% 5.80, N% 4.74, found C% 72.75, H% 5.83, N% 4.45.

**3-(4-(dimethylamino)phenyl)-2-oxo-2H-chromen-7-yl acetate (19).** Yield 70%; 1H-NMR (400 MHz, d6 -DMSO) δ: 2.31 (s, 3H, CH3C(O)O-Ph), 2.95 (s, 6H, (CH3)2N-Ph), 6.77 (d, 2H, J 3 = 9.0 Hz, H-3', H-5'), 7.14 (dd, 1H, J 3 = 8.4 Hz, J 4 = 2.2 Hz, H-6), 7.26 (d, 1H, J 4 = 2.2 Hz, H-8), 7.63 (d, 2H, J 3 = 9.0 Hz, H-2', H-6'), 7.76 (d, 1H, J 3 = 8.5 Hz, H-5), 8.11 (s, 1H, H-4; 13C-NMR (100 MHz, d6 -DMSO) δ: 20.86, 39.84, 109.44, 111.58, 117.76, 118.57, 121.58, 126.00, 128.82, 129.11 136.46, 150.45, 151.90, 152.77, 159.74, 168.85; HRMS (ESI): Calc for C19H17N1O4Na1 [M + Na]+: 346.10553, found 346.10640.

**3-(3-fluoro-4-hydroxyphenyl)-7-methoxy-2H-chromen-2-one (20).** In the first step 2-fluoro-4-(7-methoxy-2-oxo-2Hchromen-3-yl)phenyl acetate was obtained.  In the second step 3-(3-fluoro-4 hydroxyphenyl)-7-methoxy-2H-chromen-2-one was obtained. Yield 70%; 1H-NMR (400 MHz, d6 -DMSO) δ: 3.87 (s, 3H, CH3O-Ph), 6.96-7.03 (m, 3H, H-6, H-8, H-5'), 7.41 (d, 1H, J 3 = 8.4, H-6'), 7.57 (dd, 1H, J H−F = 13.1 Hz, J 4 = 2.2 Hz (H-H), 1H, H-2'), 7.66 (d, 1H, J 3 = 8.4, H-5), 8.18 (s, 1H, H-4), 10.09 (s, 1H, Ph-OH). 13C-NMR (75.5 MHz, d6 -DMSO) δ: 55.91, 100.16, 112.61, 113.04, 115.95 (d, J C−F = 20 Hz), 117.37 (d, J C−F = 3.3 Hz), 121.78 (J C−F = 2.0 Hz), 124.54 (d, J C−F = 3.0 Hz), 126.08 (d, J C−F = 7.0 Hz), 129.49, 139.62, 145.0 (J C−F = 13 Hz), 150.46 (d, J C−F = 240 Hz), 154.52, 159.87, 162.19; HRMS (ESI): Calc for C16H11F1O4Na1 [M + Na]+: 309.0539, found 309.0553.

**3-(4-fluorophenyl)-6-methoxy-2H-chromen-2-one (21).** Yield 58%; 1H-NMR (400 MHz, d6 -acetone) δ: 3.87 (s, 3H, CH3O-Ph), 7.19-7.33 (m, 5H, H-5, H-7, H-8, H-3', H-5'), 7.83 (dd, 2H, J HF = 5.4 Hz, J H−H = 9.0 Hz, H-2', H6'), 8.12 (s, 1H, H-4); 13C-NMR (100 MHz, d6 -acetone) δ: 56.17, 111.34, 115.84 (d, J C−F = 22 Hz), 117.85, 120.04, 121.04, 127.79, 131.62 (d, J C−F = 8 Hz), 132.41 (d, J C−F = 3 Hz), 140.82, 148.82, 157.13, 160.64, 163.72 (d, J C−F = 247 Hz); HRMS (ESI): Calc for C16H11F1O3Na1 [M + Na]+: 293.05899, found 293.05850; elemental anal. for C16H11F1O3, calc C% 71.11, H% 4.10, found C% 71.10, H% 4.10.

**3-(3-fluoro-4-hydroxyphenyl)-6-methoxy-2H-chromen-2-one (22).** In the first step 2-fluoro-4-(6-methoxy-2-oxo-2Hchromen-3-yl)phenyl acetate was obtained. Yield 66%; 1H-NMR (400 MHz, d6 -DMSO) δ: 2.33 (s, 3H, CH3C(O)O-Ph), 3.82 (s, 3H, (CH3O-Ph), 7.23 (dd, 1H, J 3 = 9.0 Hz, J 4 = 3.0 Hz, H-7), 7.30 (d, 1H, J 4 = 3.0 Hz, H-5), 7.35 (d, 1H, J 3 = 9.2 Hz, H-8), 7.61 (d, 1H, J 3 = 8.5 Hz, H-5'), 7.75 (dd, 1H, J H−F = 12.0 Hz, J 4 = 1.7 Hz (H-H), 1H, H-3'), 8.30 (s, 1H, H-4); 13C-NMR (100.6 MHz, d 6 -DMSO) δ: 20.22, 55.69, 110.83, 116.67, 117.02, 119.66, 123.96, 125.10, 135.96, 141.18, 147.44, 151.78, 154.23, 155.70, 159.53, 168.21. In the second step 3-(3-fluoro-4-hydroxyphenyl)-6 methoxy-2H-chromen-2-one was obtained. Yield 71%; 1H-NMR (400 MHz, d6 -DMSO) δ: 3.81 (s, 3H, (CH3O-Ph), 7.02 (dd, 1H, J 3 = 9.2 Hz, H-6'), 7.18 (dd, 1H, J 3 = 9.0 Hz, J 4 = 3.0 Hz, H-7), 7.28 (d, 1H, J 4 = 2.9 Hz, H-5), 7.42 (d, 1H, J 3 = 8.4 Hz, H-5'), 7.57 (dd, 1H, J H−F = 13.0 Hz, J 4 = 2.2 Hz (H-H), 1H, H-2'), 8.17 (s, 1H, H-4), 10.19 (s, 1H, Ph-OH); 13C-NMR (100.6 MHz, d6 -DMSO) δ: 55.66, 110.59, 116.67, 117.02, 119.66, 123.96, 125.10, 135.96, 141.18, 147.44, 151.78, 154.23, 155.70, 159.53, 168.21. HRMS (ESI): Calc for C16H11F1O4Na1 [M + Na]+: 309.0539, found 309.0521.

**3-(4-fluorophenyl)-6-methyl-2H-chromen-2-one (23).** (Chauhan et al., 2016) Yield 74%; 1H-NMR (400 MHz, d6 - DMSO) δ: 2.38 (s, 3H, CH3-Ph), 7.27-7.35 (m, 3H, H-3', H-5', H-8), 7.43 (dd, 1H, J3 = 8.5 Hz, J4 = 2.1 Hz, H-7), 7.55 (d, 1H, J4 = 1.4 Hz, H-5), 7.77 (dd, 2H, J HF = 5.7 Hz, J H−H = 9.0 Hz, H-2', H6'), 8.18 (s, 1H, H-4); 13C-NMR (100.6 MHz, d6 -DMSO) δ: 20.26, 115.11 (d, J H−F = 21.5 Hz), 115.64, 119.16, 125.76, 128.20, 130.70 (d, J H−F = 8.4 Hz), 131.10 (d, J H−F = 3.2 Hz), 132,61, 133.80, 140.48, 151.10, 159.82, 162.17 (d, J H−F = 245 Hz); HRMS (ESI): Calc for C16H11F1O2Na1 [M + Na]+: 277.06408, found 277.06390; Elemental anal. for C16H11F1O2, calc C% 75.58, H% 4.36, found C% 75.42, H% 4.33.

**3-(4-fluorophenyl)-6-hydroxy-2H-chromen-2-one (24).** In the first step 3-(4-fluorophenyl)-2-oxo-2H-chromen-6-yl acetate was obtained and used as such for the next step. In the second step 3-(4-fluorophenyl)-6-hydroxy-2H-chromen-2-one was obtained. Yield 65%; 1H-NMR (300 MHz, d6 -DMSO) δ: 7.04 (dd, 1H, J 3 = 8.8 Hz, J 4 = 2.9 Hz, H-7), 7.09 (d, 1H, J 4 = 2.8 Hz, H-5), 7.24-7.29 (m, 3H, H-3', H-5', H-8), 7.75 (dd, 2H, J HF = 5.6 Hz, J H−H = 8.9 Hz, H-2', H6'), 8.13 (s, 1H, H-4), 9.72 (s, 1H, HO-Ph); 13C-NMR (75.5 MHz, d6 -DMSO) δ: 112.561, 115.03 (d, J H−F = 21.5 Hz), 116.71, 119.78, 119.93, 125.80, 130.70 (d, J H−F = 8.2 Hz), 131.18 (d, J H−F = 3.2 Hz), 140.50, 146.35, 159.92, 162.17 (d, J H−F = 246 Hz); HRMS (ESI): Calc for C15H9F1O3Na1 [M + Na]+: 279.04334, found 279.0444.

# Monoamine Oxidase A and B

Both monoamine oxidase A (MAO-A) and B (MAO-B) protein and the reagents for the chromogenic solution of vanillic acid (4-hydroxy-3-methoxylbenzoic acid, 97% purity), 4 aminoantipyrine (reagent grade), horseradish peroxidase and the substrate tyramine hydrochloride (minimum 99% purity) as well as the potassium phosphate buffer, which was prepared using potassium phosphate dibasic trihydrate (≥99% ReagentPlusTM) and potassium phosphate monobasic (minimum 98% purity, molecular biology tested), were purchased from Sigma-Aldrich (St. Louis, MO, USA) for the spectrophotometric assay.

The protocol for continuous spectrophotometric assay (Holt et al., 1997) was followed in the activity measurements. The assay was performed in 0.2 M potassium phosphate buffer pH 7.6 on 96-well plates (NuncTM 96F microwell plate without a lid, Nunc A/S, Roskilde, DK) in 200 µl total volume. The chromogenic solution containing 1 mM vanillic acid, 500µM 4 aminoantipyrine and 8 U/ml horseradish peroxidase in 0.2 M potassium phosphate buffer pH 7.6 was mixed anew for each measurement. 5 mM tyramine solution was used as the substrate. In order to determine the activity of both MAO-B and MAO-A, concentration series as duplicates were prepared. The protein was combined with the chromogenic solution and incubated 30 min at 37◦C. The background signal was measured using multilabel reader (VictorTM X4, 2030 Multilabel Reader, PerkinElmer, Waltham, MA, USA) at A490 before reaching the total 200 µl volume by adding 20 µl of tyramine to final concentration of 0.5 mM on the plate. As a result, the final concentration of the chromogenic solution on the plate was 250µM vanillic acid, 125µM 4-aminoantipyrine and 2 U/ml horseradish peroxide. After adding the substrate, the plates were measured 300 times every 15 s using 1 s exposure time. The device was set to 37◦C for the duration of the experiment.

Based on the activity measurement, suitable concentrations were chosen for both MAO-B and MAO-A to be used in the inhibition studies (Supplementary Figures S1, S2, and S5, **Table 1**, Supplementary Table S1). The experiment conditions should produce absorbance change of ∼0.35 (Holt et al., 1997). With MAO-B, this was reached using 10 µl (equals 50 µg of protein with enzymatic activity 3.2 units per well) of the protein and running the experiment for 2 h (Supplementary Figures S1, S2, and S5, **Table 1**, Supplementary Table S1). MAO-A was significantly more active, providing absorbance change of >0.5 with 5 µl (equals 25 µg of protein with enzymatic activity 1.05 units per well) of protein and, consequently, the reaction maximum was reached already in 30 min (Supplementary Figure S5, **Table 1**, Supplementary Table S1). Thus, a wide panel of coumarin derivatives was analyzed at 10µM (**Table 1,** Supplementary Table S1) and those 3-phenylcoumarin derivatives producing >70% inhibition were selected for further analysis (**Table 1**, **Figure 2**). The selected 24 candidates were measured as duplicates on a dilution series ranging from 50µM to 1 nM, and based on the normalized measurement results, IC50 values were calculated (**Table 1**). The same wide panel of coumarin derivatives was additionally used to analyze the MAO-A inhibition at 100µM (**Table 1,** Supplementary Table S1).

GRAPHPAD PRISM 5.03 (GraphPad Software Inc., CA, USA) was used to normalize the spectrophotometric assay data where the maximal signal was reached at the lowest concentration of 10−8 or 10−9 depending on the sample and the starting concentration of 5·10−5 acted as the lowest point of signal. The measured data was then fitted on a curve using non-linear regression with the equation for log[inhibitor] vs. response. The IC50 values were therefore determined based on the curve fit. The fitted curves are shown on –log scale in Supplementary Figures S1, S2.

### 17-β-Hydroxysteroid Dehydrogenase 1

Inhibition of the 17-β-hydroxysteroid dehydrogenase 1 (HSD1) was determined by HPLC using recombinant human HSD1 proteins, produced in Sf9-insect cells, as described earlier (Messinger et al., 2009). The assay was performed in a final volume of 0.2 ml buffer (20mM KH2PO4, 1mM EDTA, pH 7.4) containing 0.1 mg/ml protein, 1 mM cofactor NADPH, 30 nM substrate estrone or estradiol, 800,000 cpm/ml of tritium labeled estrone ([3H]-E1) or estradiol ([3H]-E2) and inhibitor concentrations in the range of 0.1–5 mM. Triplicate samples were incubated for 25 min at RT. The reaction was stopped by addition of 20 ml 10% trichloroacetic acid per sample. After incubation the substrate and the product of enzymatic conversion [3H]-E1 and [3H]-E2, were separated and quantified by HPLC (Alliance 2790, Waters) connected to an online counter (Packard Flow Scintillation Analyzer). The ratio of [3H]- E1 converted to [3H]-E2, or vice versa, determines the sample conversion percentage. Inhibition efficiencies were calculated by comparing the conversion percentages of the samples including inhibitors with those of conversion controls (without inhibitors).

#### Aromatase

Aromatase (CYP19A1) activity was measured as described previously (Pasanen, 1985) by using human placental microsomes and 50 nM [3H]-androstenedione as a substrate and inhibitor concentrations in the range of 60–1,000 nM. Aromatase activities were measured as released [3H]-H2O in Optiphase Hisafe 2 scintillation liquid (Perkin Elmer, USA) with a Wallac 1450 MicroBeta Trilux scintillation counter (Perkin Elmer, USA). As a positive control for aromatase inhibition, 1µM finrozole (generous gift from Olavi Pelkonen, University of Oulu, Finland) was used.

### Cytochrome P450 1A2

Inhibition of CYP1A2 activity was determined with commercial heterologously expressed human CYP1A2 enzyme (Corning Inc., Corning, NY, USA) as described earlier (Korhonen et al., 2005). The metabolic activity was not in the scope of this particular study. The assay was adapted to the 96-well plate format. In each well, a 150 µL incubation volume contained 100 mM Tris-HCl buffer (pH 7.4), 4.2 mM MgCl2,1µM 7-ethoxyresorufin, 0.5 pmol of cDNA expressed CYP1A2, 0-40 mM inhibitor, and a NADPH-generating system. All inhibitors were dissolved in ethanol, and the final concentration of ethanol was 2% in all incubations. The reaction was initiated by adding the NADPHregenerating system after a 10 min preincubation at 37◦C, and after a 20 min incubation, the reaction was terminated by the addition of 110 µL of 80% acetonitrile/20% 0.5 M Tris base. The formed fluorescence was measured with a Victor2 plate counter (Perkin-Elmer Life Sciences Wallac, Turku, Finland) at 570 nm excitation and 616 nm emission.

# Estrogen Receptor

The pIC50 values for the derivatives (**Table 1**, Supplementary Table S1) were measured with green PolarScreenTM ER Alpha Competitor Assay (Life Technologies, CA, The United States of America) kit, following the manufacturer protocol as previously described (Niinivehmas et al., 2016). The final concentration of the compounds ranged from 0.0007 to 10 000 nM in the dilution series which were performed as duplicates. The molecules were combined with 25 nM ERα and 4.5 nM fluormone in the assay buffer and placed on black low volume 384-well assay plate with NBS surface (Corning, NY, The United States of America). After mixing the assay plate, it was incubated for 2 h in RT. The fluorescence polarization was measured using excitation wave length 485 and emission wave length 535 with bandwidths of 25/20 nm on a 2104 EnVision R Multilabel Plate Reader which had EnVision Workstation version 1.7 (PerkinElmer, MA, The United States of America).

# Computational Methods

The small-molecule ligand structures were drawn in 3D and their tautomeric states at pH 7.4 were built using LIGPREP module in MAESTRO 2016-3 (Schrödinger, LLC, New York, NY, USA, 2016). The derivatives were docked to the X-ray crystal structure of MAO-B (PDB: 2V60) (Binda et al., 2007) with PLANTS 1.2 (Korb et al., 2009) using 10 Å radius and the C8 atom of inhibitor C18 (PDB: 2V60) was used as the center. The R1-methoxy group rotamers of compounds **1**, **8**, **9**, **21**, **15**, **18**, and **22** were manually adjusted to indicate how the groups exploit the small hydrophobic niche in the cavity (green sector in **Figures 3A,B**). The 2D structures of the 3-phenylcoumarin scaffold and the 24 most potent inhibitor derivatives shown in **Figures 1E**, **2** were drawn with BIOVIA DRAW 2016 (Dassault Systèmes, San Diego, CA, USA, 2016). **Figures 1A–D**, **3–5** were prepared using BODIL (Lehtonen et al., 2004) and VMD 1.9.2 (Humphrey et al., 1996). The negative images of the MAO-B and MAO-A binding cavities shown in **Figure 3A** and C were outlined using PANTHER (Niinivehmas et al., 2011, 2015) and visualized with BODIL, MOLSCRIPT (Kraulis, 1991), and RASTER3D (Merritt and Murphy, 1994).

# RESULTS AND DISCUSSION

#### Spectrophotometric Activity Measurements for Monoamine Oxidase B

All of the 52 derivatives were docked, synthetized and tested experimentally. Those 24 compounds that provided IC50 values below 10µM were tested more thoroughly (**Table 1**). The fact that 24 of the synthesized derivatives with a wide variety of different R1-R7 groups (**Figure 2**) passed the 70% threshold indicates that the 3-phenylcoumarin is indeed a highly suitable scaffold for building MAO-B inhibitors. Notably, eight of these tested derivatives (**3**, **9**–**13**, **17,** and **23** in **Figure 2**) had been synthesized previously (Bhandri et al., 1949; Kirkiacharian et al., 1999, 2003; Prendergast, 2001; Vilar et al., 2006; Ferino et al., 2013; Chauhan et al., 2016; Dobelmann-Mara et al., 2017), however, this is the first time they are tested for MAO-B activity. The novel derivative **1** is the most potent inhibitor of the analog set with the IC50 value of 56 nM (**Figure 2**, **Table 1**); meanwhile, the rest of the tested derivatives are evenly distributed within a range of 0.1–10µM (**Figure 2**, **Table 1**).

By focusing solely on the R1-R7 constituents of the derivatives (**Figures 1E**, **2**) and the activity data (**Table 1**) it is possible to outline trends that determine which functional groups, positions or their combinations establish and weaken or improve the MAO-B inhibition.

Although the R1 and R2 groups in the coumarin ring are not necessarily required for establishing MAO-B inhibition (see **11**; **Figure 2**, Supplementary Figure S3F; **Table 1**), the activity measurements indicate that adding a methoxy, hydroxyl, acetoxy, methyl or even halogen group(s) into the ring can facilitate strong

the active site, displays the contours (opaque surface) that roughly match the inhibitor shape and conformation. The colored sectors highlight specific sections of the cavity dedicated to different aspects of the 3-phenylcoumarin derivative binding: 3-phenyl ring (orange), the R4-R7 groups of the 3-phenyl ring (red), coumarin ring (yellow), the hydrophobic niche occupied by the R1/R2-groups of the coumarin ring (green). (C) A negative image of the MAO-A active site shows that only two residue changes (Ile199→ Phe208; Leu164→ Phe173) are enough to prevent 3-phenylcoumarin analog binding. (D) The docked poses of the 23 most potent 3-phenylcoumarin derivatives show what space is collectively occupied by the new inhibitors. See Figure 1 for details.

inhibition (**Table 1**). As a rule of thumb, introducing R1-methoxy group produces strong MAO-B inhibition (e.g., **1**; **Figure 2**; **Table 1**). In contrast, inserting for example a bulky R3 substituent such as acetoxy group weakens the inhibition considerably (26, 35, 47; Supplementary Figure S4; Supplementary Table S1). Whether the R1 or R2 position or any specific functional group in particular is favored depends on the composition of the 3-phenyl ring's R4-R7 constituents.

In fact, the activity data indicates that the R4-R7 substituents are vital for assuring strong MAO-B inhibition and without any 3-phenyl substituents, the activity is lost (41, 50, 52; Supplementary Figure S4, Supplementary Table S1). The most potent inhibitors were **1** (IC50 of ∼56 nM; **Table 1**) and **2** (IC50 of ∼138 nM; **Table 1**) housing R6-trifluoromethyl, but **3** (IC50 of ∼141 nM; **Table 1**) with structurally similar R6-trifluoromethoxy group is almost equally potent. The combination of the R6-acetoxy and R7-fluorine groups in **6** (IC50 of ∼189 nM) produces relatively strong inhibition. Furthermore, housing just one methoxy group at the R7 position (**8**; IC50 of ∼230 nM) or two methoxy groups at both R5 and R7 positions (**9**; IC50 of ∼255 nM) assures < 300 nM inhibition.

The effects of the R4-R7 groups of the 3-phenyl ring and the R1-R3 groups of coumarin ring (**Figure 2**) for the derivative binding and inhibition are detailed below in a docking-based structure-activity relationship (SAR) analysis.

# The Alignment of the 3-Phenylcoumarin Scaffold at the Active Site

The 3-phenylcoumarin derivative binding at the MAO-B active site is based on the premise that the coumarin and phenyl ring systems occupy roughly the same 3D space as the equivalent ring systems of the coumarin-based inhibitors co-crystallized with the enzyme (PDB: 2V60, 2V61; **Figures 1A–D**) (Binda et al., 2007). The fundamental difference between the 3-phenylcoumarin derivatives and those coumarin inhibitors with validated binding poses is that the coumarin alignment is reversed and the phenyl ring is attached to the C3-position instead of the C7-position (**Figures 1C,D**).

What is more, the "canonical" coumarin ring positioning inside the pocket is somewhat analogous to even simpler double ring constructs such as the indole of inhibitor isatin (PDB: 1OJA) (Binda et al., 2003). In fact, the hydrophobicity of the aromatic coumarin (yellow sector in **Figures 3A,B**) and 3-phenyl (orange sector in **Figures 3A,B**) rings is vital for establishing the MAO-B binding and it outweighs all other favorable interactions such as hydrogen or halogen bonding (via sigma hole) in importance (**Figure 4**). Thus, although the docking suggests variability in the coumarin and 3-phenyl ring positioning for the 3 phenylcoumarin derivatives due to different R1-R7 substituents, the hydrophobic interactions of the aromatic rings are highly similar between them (**Figure 3D**).

It is also noteworthy that the coumarin's C2-carbonyl is not facing the solvent based on the molecular docking simulations

(**Figure 3D**). Paradoxically, this does not matter, because the carbonyl group finds an atypical interaction partner from the thiol group of Cys172 side chain (**Figure 4**). Although the C2 carbonyl cannot form a full-fledged H-bond with the proton of the thiol group, the hydrophobic environment of the cavity likely enhances this ordinarily weak interaction between the two groups.

# R6-Trifluoromethyl Packing Produces the Strongest Inhibition

Halogen substituents in the 3-phenyl ring ensure strong MAO-B inhibition (**Figure 4**). This makes sense with MAO-B, because despite their apparent electronegativity the halogen substituents actually improve the steric packing of small-molecules via persistent van der Waals interactions while also retaining the ability to act as a halogen bond donor. Both of these properties should assist inhibitor binding into the active site that is mostly hydrophobic (**Figures 3A,B**). Besides, the increased lipophilicity conveyed by the halogen substituents (logP values in **Table 1**) should assist the 3-phenylcoumarin derivatives in aggregating on the outer mitochondrial membrane on route to the MAO-B active site (**Figure 1A**).

The most potent derivative **1** (**Figure 2**, **Table 1**) has trifluoromethyl group at the R6 position in the 3-phenyl ring. The derivative is relatively flat when bound at the active site and the proximal R6-group cannot flex out of this plane (**Figure 5A**). The trifluoromethyl of **1** fits very snugly into the hydrophobic end of the cavity (red sector in **Figures 3A,B**). The high shape complementarity of this cavity part and the R6 trifluoromethyl of **1** is typical for this bulky moiety in drug compounds. Thus, the R6-group alignment of **1** is mostly relying on the collective potency of individually weak van der Waals interactions (**Figures 3A,B, 5A**).

Replacing the R6-trifluoromethyl of derivative **1** with a trifluoromethoxy in **4** (**Figure 2**) produces six times lower MAO-B inhibition (**Table 1**, Supplementary Figure S3B). This happens because the trifluoromethoxy already fills the available space almost optimally (**Figures 3A,B**, **5A**) and elongating the substituent with an ether bond does not improve the fit (Supplementary Figure S3B). In fact, there is no extra wiggle room to fit the trifluoromethoxy (**Figures 3A,B**), if the 3 phenylcoumarin scaffold would be kept at the "canonical" position (**Figures 1C,D**). Hence, the coumarin ring of **4** pushes slightly closer to the cofactor. Although the binding site residues can adjust slightly in response to this shift, the realignment or rather misalignment of the scaffold (Supplementary Figure S3B) imposes an energetic cost that is reflected in the MAO-B inhibition (**Table 1**). In addition, depending on the rotamer pose of the R6-trifluorometoxy, a hydrogen bond could be bridged between a fluorine atom and the Pro102O by a water molecule (not shown).

# The Effects of Halogenation on the 3-Phenyl Ring Alignment

The chlorine and fluorine substituents of prior coumarin-based inhibitors form halogen bond with the Leu164O based on

X-ray crystallography (PDB: 2V60, 2V61; **Figures 1A–D**; Binda et al., 2007). Accordingly, it is not surprising that those 3 phenylcoumarin derivatives with single halogen substituent at their 3-phenyl rings are also capable of blocking the MAO-B activity (**Figure 4**, **Table 1**).

Although it is known that fluorine is the poorest halogen bond donor (Cavallo et al., 2016), the R7-fluorine groups of **20** and **22** (**Figure 2**) could form halogen bond with the Leu164◦ (**Figures 6E,F**) similarly to the halogens of previously published inhibitors with validated binding modes (**Figures 1B–D**; Binda et al., 2007). In fact, the R7-halogen groups of **20** and **22** are inserted into the exact same position as the halogen groups of the established inhibitors (**Figure 1B** vs. **Figures 6E,F**). The MAO-B inhibition (**Table 1**) is reinforced further by the R6-hydroxyl group H-bonding with the Pro102O (magenta dotted lines in **Figures 6E,F**). Because both **20** and **22** are bonding simultaneously with the Leu164O and the Pro102O, they elicit equivalent or stronger inhibition than derivatives **21** (**Figure 5D**), **23** (Supplementary Figure S3K), and **24** (Supplementary Figure S3L) that do not retain either one of these two interactions. Docking suggests that replacing the R6 hydroxyl with an acetoxy group prevents **6** (**Figure 2**) from forming direct halogen or hydrogen bonds (**Figure 5C**), but the R6-acetoxy and R7-fluorine could potentially connect via a water bridge with the Pro102O (not shown). Despite this, the hydrophobic packing of the R6-acetoxy in **6** against the hydrophobic residues, mainly Phe103 (**Figure 5C**), is likely the reason behind doubling the inhibition in comparison to **20** (IC50 value of 391 vs. 189 nM; **Table 1**, **Figure 6E**).

Introducing fluorine to the R6 position of the 3-phenyl ring in derivatives **21**, **23**, and **24** (**Figure 2**) produces MAO-B inhibition ranging from 433 to 1,060 nM (**Table 1**). Due to the overall planarity of the 3-phenylcoumarin scaffold (**Figures 1C,D**), the R6-fluorine (**Figure 5D**, Supplementary Figures S3K,L), cannot take on the equivalent site occupied by the halogens of validated coumarin-based inhibitors that form halogen bond with the Leu164◦ (**Figure 1B**; Binda et al., 2007). In addition, the R6-fluorine is too limited in size to fill the end of the binding cavity as completely as for example the trifluoromethyl of **1** does (**Figures 3A,B**, **5A**). In addition, the R6-fluorine groups of derivatives **21**, **23,** and **24** (**Figure 5D**, Supplementary Figure S3K,L) reside within a suitable distance to form a halogen bond with the Pro102O (3.6 Å), however, the available angles seem to rule out actual bonding.

Derivatives **15** and **16** (**Figure 2**) house three fluorine atoms at their 3-phenyl groups' R4, R6, and R7 positions (**Figures 6A,B**). In the case of **15** (**Figure 6A**), these halogen substituents assure an IC50 value that is almost 150 nM stronger than what is seen with derivatives housing only a single fluorine moiety at the R6 or R7 position (**21**, **23,** and **24**; **Figure 5D**, Figure S3K-L, **Table 1**). This is achieved by filling the hydrophobic cavity end (orange and red sectors in **Figure 3**) efficiently with the 3-phenyl ring and its fluorine moieties (**Figures 6A,B**). The fit is better for a 3-phenyl ring with the R5-trifluoromethyl than what is seen with the ring housing three separate fluorine substituents (**Figure 5A** vs. **Figure 6A**) and; accordingly, derivative **15** is not as potent MAO-B inhibitor as **1** (IC50 292 vs. 56 nM; **Table 1**). In addition, depending on the 3-phenyl ring pose, the R4 or R7 fluorine

groups could again potentially act as weak halogen bond donors to the Phe168O or the Leu164O, respectively (not shown).

# The Effects of the Methoxy and Dimethylamine Groups for the 3-Phenyl Alignment

Derivatives with proximal methoxy groups (**Figure 2**), especially at the R7 position, assure relatively strong MAO-B inhibition (**Figure 4**) and produce at best 230 nM inhibition (e.g., **8** in **Figure 2**, **Table 1**).

Based on the docking, derivatives **8** and **11** (**Figure 2**) flip their R7-methoxy groups toward the Leu164◦ (**Figure 5E**, Supplementary Figure S3F), which is shielded from a clash with the methoxy group by forming intra-protein H-bond with the Phe168N (not shown). Inserting an extra R5-methoxy into the 3-phenyl of **8** to produce otherwise identical derivative **9** (**Figure 2**) weakens the inhibition slightly (IC50 difference of 23 nM; **Table 1**), because the added methoxy group is unable to form particularly favorable interactions with the nearby Pro102◦ (**Figure 5F**). With derivatives **10** or **13** (**Figure 2**), the methoxy group is added to the phenyl ring's para position, and due to the planarity of the 3-phenylcoumarin scaffold, there is an energetic penalty for pushing the group toward either side of the cavity end (red sector in **Figures 3A,B**). Accordingly, to avoid a scaffold misalignment, the R6-methoxy group of **10** (and **13**) points directly toward the side chains of Phe103, Pro104, Trp119, and Ile199 (Supplementary Figures S3E,F), which, in turn, produces roughly 170 nM difference in the IC50 values with otherwise identical **8** (**Figure 5E**, **Table 1**) in favor of the R7-methoxy position.

A dimethylamine group at the 3-phenyl ring's para position (a.k.a. dimethylaniline; **Figure 2**) produces moderately strong MAO-B inhibition (**Table 1**) for derivatives **17** (**Figure 2**; IC50 value of 400 nM), **18** (**Figure 2**; IC50 value of 798 nM), and **19** (**Figure 2**; IC50 value of 955 nM). This is due to the ability of the R6-dimethylamine to fill the cavity end (red sector in **Figures 3A,B**) similarly to the R6-trifluoromethyl of **1** (**Figures 5A,B** vs. **Figures 6C,D**, Supplementary Figure S3J). The downside is that the bulkier R6-substituent cannot form halogen or hydrogen bonds with water or residues nor push against either side of the cavity and, most importantly, it causes unfavorable coumarin alignment. Accordingly, the R6 dimethylamine of derivatives **17**–**19** packs directly against the side chains of Phe103, Pro104, Trp119, Leu164, and Ile316 (**Figures 4C,D**, Supplementary Figure S3J).

## Refining the Alignment via the R1–R3 Substituents of the Coumarin Ring

Inserting a functional group such as methoxy to the R1/R2 position of the coumarin ring (**Figure 2**), capable of forming both hydrophobic and hydrophilic interactions, generally improves the MAO-B inhibition (**Figure 4**, **Table 1**).

The benefits of this sort of dual-purpose group are evident when comparing the activity of otherwise identical derivatives with and without the proximal group; i.e., **11**, that lacks only the R1-methoxy of **8** (Supplementary Figure S3F vs. **Figure 5E**), produces significantly lower inhibition (IC50 value of 798 vs. 231 nM; **Table 1**). On one hand, the methyl of the R1-methoxy group of **8** (**Figure 5E**) packs into a hydrophobic niche formed by the side chains of Tyr60, Gln206, Tyr326, Leu328, Phe343, and Met341 (green sector in **Figures 3A,B**). On the other hand, the methoxy's oxygen increases the 3-phenyl ring's hydrophilicity and softens the clash of the coumarin ring with the solvent shielding the cofactor (**Figure 5E**).

Switching the R1-methoxy of **1** into the R2 position in **2** (**Figure 2**) makes the alignment of the coumarin ring more challenging, because the R2-methoxy is unable to occupy the same hydrophobic niche (green sector in **Figures 3A,B**) as the R1-methoxy (**Figure 4A** vs. Supplementary Figure S3A). Although the R1/R2 methoxy switch, by all means, does not prevent binding, it leads to ∼80 nM reduction in the IC50 value (**Table 1**). Paradoxically, the opposite and considerably larger difference in inhibition is produced by the R1/R2 switch, when comparing the activity of derivatives **20** and **22** (**Figure 2**; **Table 1**). Accordingly, **20** with the R2-methoxy of (IC50 value of 391 nM; **Table 1**) provides twice as strong inhibition as **22** with the R1-methoxy (IC50 value of 831 nM; **Table 1**). The vast difference is caused by the coordinated R6/R7 interactions of the 3-phenyl ring, which pushes the coumarin ring closer to the Tyr326 side chain—a critical shift that is stunted by the R1-methoxy of **22** (**Figure 5E** vs. **Figure 5F**).

Replacing the R2-acetoxy of **3** (**Figure 2**) with the R1-methoxy in **4** (**Figure 2**) weakens the inhibition ∼180 nM (**Table 1**). The coumarin ring of **4** is pushed closer to the cofactor due to the addition of the R6-trifluoromethoxy into the 3-phenyl ring (**Figure 5B** vs. Supplementary Figure S3B) and, in this new pose, the methyl of the R2-acetoxy is able to occupy the small hydrophobic niche (green sector in **Figures 3A,B**), meanwhile, exposing the acetoxy's oxygen atoms to the solvent (**Figure 3B**). However, substituting the R1-methoxy of **18** with the R2-acetoxy in **19** (**Figure 2**) does not improve the inhibition; instead, the IC50 value is reduced by ∼250 nM (**Table 1**). This happens, because the R6-dimethylamine of **19** (Supplementary Figure S3J) is not forcing the scaffold to align close to the cofactor the same way as the R6-trifluoromethoxy does (**Figure 5B** vs. **Figures 6C,D**). In contrast, replacing the R1-methoxy of **18** with the R2-hydroxyl in **17** improves the inhibition (IC50 improvement of 234 nM; **Table 1**) by promoting water solubility near the cofactor (**Figure 6C** vs. **Figure 6D**).

The R6 and R7 interactions of **7** (**Figure 2**) are expected to remind closely those of **6** (Supplementary Figure S3D vs. **Figure 5C**), but its coumarin ring's R1- and R3-chlorine groups weaken the inhibition ∼700 nM (**Table 1**). The R2 methoxy of **6** is able to play into the hydrophobic/hydrophilic dual nature of the cavity end facing the cofactor (**Figure 5C**) without occupying the small hydrophobic niche (green sector in **Figures 3A,B**). In this respect, the R1-chlorine is too bulky to occupy this specific niche although a methoxy group at the same position should be able to occupy the available space (e.g., **1** in **Figure 5A**).

# Selectivity of the 3-Phenylcoumarin Derivatives

Determining the specificity and subtype selectivity of the 3 phenylcoumarin derivatives for MAO-B is needed to evaluate their true pharmacological potential. Unintended off-target effects with other proteins can render even the most promising drug candidates useless, ambiguous or even toxic. Here, the focus is put on MAO-A which has shared activity with MAO-B in deamination of dopamine and dietary amines tyramine and tryptamine. In addition, the effects of the derivatives are tested with a specific subset of enzymes, including HSD1, aromatase, CYP1A2, and ER, whose function is linked to different stages of estradiol action and metabolism. These particular enzymes were looked at with the derivatives, because they are known to have structurally similar ligands or even coumarin-based inhibitors based on prior studies and our upcoming study (Mattsson et al., 2014; Niinivehmas et al., 2016; Niinivehmas et al., unpublished results).

Monoamine oxidase A (MAO-A) is more prevalent than the subtype B in the gastrointestinal tract and, accordingly, the MAO-A inhibition can cause accumulation of tyramine from dietary sources. Because tyramine can displace neurotransmitters leading to potentially fatal hypertensive crisis, it is highly desirable to design MAO-B-specific inhibitors lacking MAO-A activity. The vast majority of the novel derivatives do not produce MAO-A inhibition at 100µM despite the fact that it is ten times the concentration used in this study to determine MAO-B inhibition percentage (**Table 1**, Supplementary Table S1). Furthermore, only in those few cases where inhibition was detected, especially with the most potent MAO-B derivatives, it remains at moderate or close to non-existent level (**Table 1**). The strongest MAO-A inhibition was elicited by derivatives **42** and **43** (48.86 and 56.76%), but derivatives **27** and **45** (43.83 and 43.36%) are close runner-ups and next analogs down the list are already much weaker (Supplementary Figure S4, Supplementary Table S1). Notably, **1**, which is the most potent MAO-B inhibitor of the derivative set with the IC50 value of 56 nM, does not produce MAO-A inhibition at 100µM (**Table 1**). The molecular basis for the lack of MAO-A activity is evident, when comparing the shape and size of the active sites of the two enzyme subtypes in the context of 3-phenylcoumarin binding (**Figure 3A** vs. **Figure 3B**).

17-β-hydroxysteroid dehydrogenase 1 (HSD1), which functions as the catalyst of the final reducing step in the estradiol biosynthesis, is often overexpressed in breast cancer and endometriotic tissue (Vihko et al., 2004; Dassen et al., 2007; Hanamura et al., 2014). Thus, specific inhibition of HSD1 has potential to reduce effective estradiol levels in the treatments. Although the synthesized 3-phenylcoumarin set contains several molecules that exhibit activity toward HSD1, the inhibition was generally very weak and the active compounds are not among the most potent MAO-B inhibitors. Of the 24 most potent MAO-B inhibitors, the strongest HSD1 inhibition could be recorded for **20** and **22** (46 and 54%; **Figure 2**, **Table 1**); however, considerably higher activity (48.20–83.90%) was seen with derivatives **30**, **31**, **33**, **38,** and **48** (Supplementary Figure S4, Supplementary Table S1). Modest HSD1 inhibition (12–33%) was also elicited by **6**, **15**, **16**, **23**, **24** (**Figure 2**, **Table 1**) and **51** (Supplementary Figure S4, Supplementary Table S1). Importantly, derivative **1**, which is the most potent MAO-B inhibitor of the derivative set, does not inhibit HSD1.

Aromatase (CYP19A1) inhibition, which is important for blocking local estradiol synthesis for example in breast cancer treatment (Pasqualini et al., 1996), was not detected with the derivatives (**Table 1**, Supplementary Table S1). Although 3 phenylcoumarin should be able to sterically mimic the steroidal positioning at the active site (not shown), it would have to house a clear-cut H-bond acceptor at the R5/R7-position in the 3 phenyl to facilitate aromatase binding. This is, because X-ray crystallography shows that the Asp309 side chain is in neutral state at pH 7.4 and donating a proton to the carbonyl group of inhibitor androstenedione (PDB: 3EQM) (Ghosh et al., 2009). Inserting a hydroxyl group to the R5/R7 position could put an Hbond acceptor to this same location with the 3-phenylcoumarins (see **31**, **38**, **40**, **42**, **43**; Supplementary Figure S4, Supplementary Table S1). However, because the hydroxyl always has a dual role as an H-bond donor as well, any aromatase binding by the derivatives remains theoretical as it is prevented by a proton donor clash. The issue is described more thoroughly in our upcoming study (Niinivehmas et al., unpublished results).

Estrogen receptor (ER) agonists/antagonists or selective modulators are developed for infertility, contraception, hormone replacement, and ER positive breast cancer therapies. If the MAO-B inhibitors would function also as ER agonists, they could promote tumorigenesis in the breast tissue as a side effect. Unintended ER inhibition could also disturb natural estrogen levels or interrupt ER-targeted therapies. The measurements indicate that the 3-phenylcoumarin derivatives either are a hit or miss when considering ER inhibition. Although the ER activity could not be measured for all of the analogs due to running out of the synthesis products, the acquired results overwhelmingly support our prior findings stating that the R2-hydroxyl or the R6 hydroxyl/halogen is needed to prompt ER activity (Niinivehmas et al., 2016). This ER-specific effect is prominent with **12**, **20**, **22**, **27**, **28**, **29**, **30**, **39**, **40**, **41**, **44**, and **48** (**Table 1**, Supplementary Table S1, **Figure 2**, Supplementary Figure S4) and, moreover, ER activity is predicted for **17** and likely for **32** and **47** based on the well-established trend.

Cytochrome P450 1A2 (CYP1A2) catalyzes the oxidation of xenobiotics, especially polyaromatic hydrocarbons and steroid hormone-sized compounds such as 3-phenylcoumarins, into more soluble form for excretion (Zhou et al., 2010). Accordingly, it was prudent to get a rough estimate of the CYP1A2 inhibition levels for the novel 3-phenylcoumarin derivatives as well. In general, all of the derivatives inhibited CYP1A2 at some level (**Table 1**, Supplementary Table S1); however, typically the most potent CYP1A2 inhibitors such as **21**–**24** were less potent MAO-B inhibitors (**Table 1**). Similar to MAO-A, HSD1, and aromatase, the most potent MAO-B derivative **1** displayed only low CYP1A2 activity (IC50 value of 124µM; **Table 1**).

#### Overall Assessment on the Druglikeness

As a whole, the selectivity analysis indicates that the crossreactivity of 3-phenylcoumarins can be managed or even avoided via specific functional group substitutions without taking away the MAO-B activity. Coumarins in general do not belong to the PAINS (pan assay interference compounds) category as it is a privileged scaffold structure. Only derivative **50**, which is not a potent MAO-B inhibitor (Supplementary Table S1, Supplementary Figure S4), was recognized as a potential PAINS ligand by PAINS3 filter (or A filter) in CANVAS module in MAESTRO (Baell and Holloway, 2010). In the ChEMBL database, ∼14,200 coumarin derivatives are included (observed online in 8.2.2018), which indicates that the scaffold can be tailored to target multitude of proteins. Despite this, the literature does not raise widespread concerns that the coumarin-based compounds in particular would cause harmful cross-reactivity or selectivity issues. The 24 active derivatives presented in this study (**Table 1**, **Figure 2**) have lower potency than some of the prior 3-phenylcoumarin compounds (Supplementary Figure S6, Supplementary Table S2) (Matos et al., 2009b, 2011a,b; Santana et al., 2010; Viña et al., 2012a); however, one has to be aware of fact that these results originate from different laboratories and activity assays and are, therefore, not fully comparable. To a degree this is the case even for the positive control pargyline (Fisar et al., 2010). Importantly, the new compounds follow closely the Lipinski rule of five regarding the logP value (logP < 5) and remain in the logP range of 2–4. Moreover, the ligandlipophilicity efficiency (LiPE) values of the new analogs suggest reasonable druglikeness (Freeman-Cook et al., 2013). What is more, derivative **1** clearly has the most promising selectivity profile of the derivatives for future consideration, because it is not only the most potent MAO-B inhibitor of the set but it is also selective against the other tested enzymes.

# CONCLUSION

A broad set of 3-phenylcoumarin derivatives was designed using virtual combinatorial chemistry or rationally de novo, synthesized and tested for MAO-B inhibition potency using spectrophotometry (Supplementary Table S1). The results further validate prior studies suggesting that the 3-phenylcoumarin is a suitable scaffold for building potent small-molecule MAO-B inhibitors by functionalizing its ring systems. A moderate MAO-B inhibition could be achieved by inserting a wide variety of functional groups into the coumarin (R1–R3; **Figure 4**) or 3-phenyl (R4–R7; **Figure 4**) rings (Supplementary Table S1). Twenty-four of the derivatives (**Figures 2**, **3D**) were found to elicit >70% inhibition (**Table 1**, Supplementary Figures S1, S2). These promising derivatives inhibit the MAO-B at a ∼100 nM to ∼1µM range (**Table 1**), while the most potent derivative **1** produces ∼56 nM MAO-B inhibition. A molecular dockingbased (**Figures 5**, **6**, Supplementary Figure S3) SAR analysis (**Figure 4**) describe the determinants of the MAO-B binding and inhibition at the atomistic level. Firstly, without any kind of the 3-phenyl substituents, no inhibition was detected. Although both hydrogen and halogen bonding can assist the 3-phenyl alignment and facilitate inhibition (**Figures 6E,F**, **Table 1**), the ability of the functionalized ring to fill the hydrophobic end of the binding cavity (red sector in **Figures 3A,B**) is the most important property for ensuring strong MAO-B inhibition (e.g., R6-trifluoromethyl of **1**; **Figure 5A**). Secondly, the SAR analysis reveals that a spot-on placement and composition of the coumarin ring's substituents can further enhance the MAO-B inhibition (**Figure 2**, **Table 1**), however, these effects are ultimately dependent on the scaffold alignment, which, in turn, depends on the 3-phenyl ring substituents (**Figure 4**). The cross-reactivity analysis focusing on MAO-A and a subset of estradiol metabolism-linked HSD1, aromatase, CYP1A2 and ER highlighted the potential of the 3-phenylcourmains, especially the most potent MAO-B derivative **1**, for producing selective MAO-B inhibition. Finally, the most potent 3-phenylcoumarin analogs presented in this study are estimated to operate at close to optimal ligand-lipophilicity efficiency—a feature highlighting their overall druglikeness.

### AUTHOR CONTRIBUTIONS

SR: was responsible for the experimental testing regarding MAO-A and MAO-B; EMu: performed the MAO-A experimental analysis; SR: did the docking into MAO-B and prepared most of the figures; PAP: was responsible for the final SAR analysis; SK, ES, and JH: performed the organic synthesis;

## REFERENCES

MA: did the PAINS screening; PK: performed the HSD1 measurements; NN, RJ, and HR: did the experimental analysis regarding CYP1A2; PH and MaP: executed the experimental analysis regarding aromatase; MiP: did preliminary screening for designing MAO-B ligands; SN, EMa, SK, and OTP: designed the molecules for the selected targets; SN, EMa, and OTP: designed the study. All the coauthors were involved in the manuscript preparation and approved the final version.

# FUNDING

Academy of Finland is acknowledged for funding (OTP. Project No. 250311).

#### ACKNOWLEDGMENTS

The Finnish IT Center for Science (CSC) for computational resources (OTP; Project Nos. jyy2516 and jyy2585).

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fchem. 2018.00041/full#supplementary-material

tissue homogenates. Anal. Biochem. 244, 384–392. doi: 10.1006/abio.1996. 9911

inner leaflet of presynaptic vesicles. ACS Chem. Neurosci. Acschemneuro. 8, 1242–1250. doi: 10.1021/acschemneuro.6b00395

synthesis, pharmacological evaluation, and docking studies. ChemMedChem 7, 464–470. doi: 10.1002/cmdc.201100538

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2018 Rauhamäki, Postila, Niinivehmas, Kortet, Schildt, Pasanen, Manivannan, Ahinko, Koskimies, Nyberg, Huuskonen, Multamäki, Pasanen, Juvonen, Raunio, Huuskonen and Pentikäinen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# An Efficient Implementation of the Nwat-MMGBSA Method to Rescore Docking Results in Medium-Throughput Virtual Screenings

Irene Maffucci, Xiao Hu, Valentina Fumagalli and Alessandro Contini\*

Dipartimento di Scienze Farmaceutiche, Sezione di Chimica Generale e Organica "Alessandro Marchesini," Università degli Studi di Milano, Milan, Italy

#### Edited by:

Daniela Schuster, Paracelsus Private Medical University of Salzburg, Austria

#### Reviewed by:

Alfonso T. Garcia-Sosa, University of Tartu, Estonia Pramod C. Nair, Flinders University, Australia

\*Correspondence: Alessandro Contini

#<EMAIL_ADDRESS>
Specialty section: This article was submitted to Medicinal and Pharmaceutical Chemistry, a section of the journal Frontiers in Chemistry

Received: 25 October 2017 Accepted: 19 February 2018 Published: 05 March 2018

#### Citation:

Maffucci I, Hu X, Fumagalli V and Contini A (2018) An Efficient Implementation of the Nwat-MMGBSA Method to Rescore Docking Results in Medium-Throughput Virtual Screenings. Front. Chem. 6:43. doi: 10.3389/fchem.2018.00043 Nwat-MMGBSA is a variant of MM-PB/GBSA based on the inclusion of a number of explicit water molecules that are the closest to the ligand in each frame of a molecular dynamics trajectory. This method demonstrated improved correlations between calculated and experimental binding energies in both protein-protein interactions and ligand-receptor complexes, in comparison to the standard MM-GBSA. A protocol optimization, aimed to maximize efficacy and efficiency, is discussed here considering penicillopepsin, HIV1-protease, and BCL-XL as test cases. Calculations were performed in triplicates on both classic HPC environments and on standard workstations equipped by a GPU card, evidencing no statistical differences in the results. No relevant differences in correlation to experiments were also observed when performing Nwat-MMGBSA calculations on 4 or 1 ns long trajectories. A fully automatic workflow for structure-based virtual screening, performing from library set-up to docking and Nwat-MMGBSA rescoring, has then been developed. The protocol has been tested against no rescoring or standard MM-GBSA rescoring within a retrospective virtual screening of inhibitors of AmpC β-lactamase and of the Rac1-Tiam1 protein-protein interaction. In both cases, Nwat-MMGBSA rescoring provided a statistically significant increase in the ROC AUCs of between 20 and 30%, compared to docking scoring or to standard MM-GBSA rescoring.

Keywords: MM-GBSA, explicit water, molecular dynamics, GPU, structure based virtual screening, protease, protein-protein interactions

### INTRODUCTION