Resolution of SEC is influenced by many parameters of stationary phase, including, column volume, particle size, pore size distribution [17].

The matrix of SEC are often composed of polymers by cross-linking to form a three-dimen‐ sional network. The matrix is manufactured in small spherical particles. On the surface and the inside of the particles, small channels and pores are formed with different sizes by controlling different degree of cross-linking. The selectivity of a medium depends on the distribution of pore sizes and can be described by a selectivity curve (Figure 9). For example, the medium superdex 200 (by GE company) has a linear selectivity range of 1x104 ~6x105 , that means solutes having molecular mass (Mw) in this range could be differentially retarded. The molecules larger than the upper limit are completely excluded from the inside space of the medium because no pores are big enough to allow them enter. At this time, the distribution coefficient (Kd) reaches to 0. On the contrary, those molecules smaller than the lower limit are free to enter any channel, therefore they are maximally retarded without selectivity and has a Kd=1. Those solutes with Mw between the two extremes could enter channels with different degree, Kd is between 0 and 1, are retarded differentially.

The media with narrow linear range often employed in group separations, by which solutes are simply separated into two groups. A typical application is protein desalting by a G25 column (Figure 9). On the contrary, the media with wide linear range usually used to separate similar components (Figure 9), such as using superdex 200 to separate IgG (Mw=1.5 x 105 ) and albumin (Mw=6.6 x 104 ).

**Figure 8.** In SEC large molecules run though the space between media with a shorter pathway, while the smaller mol‐ ecules run through the channels inside the medium with a longer pathway.

**Figure 9.** Selectivity curves of Superdex 200 and G25 media.

The height of packing bed affects both resolution and the separation time. Larger bed height often gives a better resolution with same sample volume, but takes more time to run a separation (Figure 10C).

The size of particle also is a parameter affecting resolution and the separation time. Smaller resin particles supply more efficient mass transfer between mobile and stationary phase, therefore present higher resolution. But simultaneously smaller particles increase the flow resistance and generally cause prolonged separation time.

## **5.2. Mobile phase**

An unparalleled advantage of SEC in all chromatography is the wide compatibility to various solutions. Because SEC separates proteins depends on molecular size rather than interactions between solutes and media, so pH value and polarity of mobile phase generally have slight influence the retention of compounds.

Since SEC has no concentration effect on elutes, so volumes of elution peak of each components are proportional to the sample volume. Increased sample volume will decrease the resolution (Figure 10B).

High viscosity in mobile phase has a certain effect on resolution by influence on the mass transfer between the mobile and the stationary phases, so that will cause broadening and tailing peaks (Figure 10D).

It is should be noticed that the ionic interaction between proteins and the resin possibly takes place at a low ionic strength, so generally 0.15 M NaCl is added to avoid it.

#### **5.3. Elution**

**Figure 8.** In SEC large molecules run though the space between media with a shorter pathway, while the smaller mol‐

ecules run through the channels inside the medium with a longer pathway.

50 Protein Engineering - Technology and Application

SEC has no a definite elution step, since molecules are not adsorbed by media. After sample is loaded, a buffer usually same to the initial buffer is pumped with two column volumes until all solutes are eluted.

**Figure 10.** The factors affecting resolution of SEC.

#### **5.4. Application**

SEC has the most mild separation condition, since in the whole process the composition of mobile phase needs no change. This is a good property for separating proteins that are unstable to alterations of pH value, ionic strength or polarity. SEC is often used in polish step after a sample has been crudely separated by other chromatography, especially in separation of the monomer and polymers. Since monomer and polymers usually could not be separated by IEXC and HIC due to the similarities in charge and hydrophobic property. But fortunately SEC can well separate them by different molecular size.

#### *5.4.1. Purification of recombinant human Midkine by SP column and SEC column*

A recombinant human Midkine (Mw=14 kDa) was expressed by an *E.coli* BL21 strain as inclusion body form. The inclusion body was denatured by 6 M guanidinium chloride and renatured through 10-fold dilution in renature buffer. The renatured protein was separated by IEXC and SEC (figure 11). Since the incorrect formation of intermolecular disulfide bond, a fraction of the rhMK molecules formed different polymers, which could not be separated from monomers by IEXC and were eluted as a mixture (Figure 11A). To separate bioactive monomers, a Sephadex G-75 column, which owns a fractionation range of 3000~80,000 dalton, was used to separate monomers from polymers. Non-reduced SDS PAGE demonstrated the purity of monomers reached 95% in the target peak.

**Figure 11.** Purification of E. coli rhMK by IEXC and SEC. (result of Shixiang Jia, Ping Tu et al. General regeneratives (shanghai) limited, Shanghai, PR China)

**5.4. Application**

**Figure 10.** The factors affecting resolution of SEC.

52 Protein Engineering - Technology and Application

SEC has the most mild separation condition, since in the whole process the composition of mobile phase needs no change. This is a good property for separating proteins that are unstable to alterations of pH value, ionic strength or polarity. SEC is often used in polish step after a sample has been crudely separated by other chromatography, especially in separation of the monomer and polymers. Since monomer and polymers usually could not be separated by IEXC

## **6. Affinity chromatography**

Affinity chromatography (AC) extensively refers to a series of techniques that separate proteins on the basis of a reversible interaction between proteins and their specific ligands coupled to a chromatography matrix [18]. The affinity interactions derive from a wide range of biorecog‐ nition, briefly including interactions between (1) enzymes and substrate analogues, inhibitors, cofactors [19], (2) antibodies and antigens [20], (3) membrane receptors and ligands [21], (4) nucleic acid and complementary sequence, histones, or nucleic acid polymerase, nucleic acid binding proteins, (5) biological small molecules and their receptors or carrier proteins [22], (6) metal ions and proteins having polyhistidine sequence.

Affinity interactions are always a result of a combination of different types of interactions, including electrostatic interactions, hydrophobic interactions, van der Vaals' forces, or hydrogen bonding. The interactions of high specificity always supply extremely high selec‐ tivity, by which a target protein could easily be separated in one step with thousands fold of increase in purity and high recovery.

## **6.1. Media**

Development of an AC media is much more complex than that other chromatography. It needs not only a specific ligand, but also complex coupling process to couple the ligand to the matrix without reducing its binding activity significantly. Therefore more and more ready-to-use matrices, which already have active ligands coupled to, were developed commercially to satisfy different separation. If no suitable ligand is available, it can be considered to develop a specific affinity medium or use alternative purification techniques.

## *6.1.1. Base matrix*

The mostly used material is agarose or cross-linked agarose. The hydroxyl groups on the sugar resides are easily derivatized for covalent attachment of a ligand or spacer arms and the porous structure also supplies ideal flow rate and high capacity.

### *6.1.2. Spacer arms*

The binding site of a target protein often locates deep within the molecule. Due to steric interference, a small ligand directly coupled to the matrix always shows a lower affinity with the target protein than in their free state. To overcome this situation, spacer arms, typically linear molecules with different chain length, are used to bridge ligands and matrix. In general a spacer arm is necessary in coupling ligands Mw <1000, and not need for larger ligands (Figure 12). An ideal spacer arms should have active groups at two ends by which it can be covalently coupled with matrix and ligand respectively. After coupling with matrix and ligand, the arms should be chemically stable to avoid reaction with other solutes and be hydrophilic to avoid the hydrophobic interaction with proteins.

**Figure 12.** The influence of spacer arms on small or large ligands. A spacer arm is often necessary for coupling small li‐ gands, which ensure a efficient binding between ligands and target proteins (A), but not necessary for large ligands (B).

The atom number of commonly used space arms varies from 4 to 12. They often coupled with agarose matrix by stable ether links at one end and with ligand by other chemical bonds at the opposite end.

### *6.1.3. Ligand coupling*

**6. Affinity chromatography**

54 Protein Engineering - Technology and Application

increase in purity and high recovery.

**6.1. Media**

*6.1.1. Base matrix*

*6.1.2. Spacer arms*

metal ions and proteins having polyhistidine sequence.

Affinity chromatography (AC) extensively refers to a series of techniques that separate proteins on the basis of a reversible interaction between proteins and their specific ligands coupled to a chromatography matrix [18]. The affinity interactions derive from a wide range of biorecog‐ nition, briefly including interactions between (1) enzymes and substrate analogues, inhibitors, cofactors [19], (2) antibodies and antigens [20], (3) membrane receptors and ligands [21], (4) nucleic acid and complementary sequence, histones, or nucleic acid polymerase, nucleic acid binding proteins, (5) biological small molecules and their receptors or carrier proteins [22], (6)

Affinity interactions are always a result of a combination of different types of interactions, including electrostatic interactions, hydrophobic interactions, van der Vaals' forces, or hydrogen bonding. The interactions of high specificity always supply extremely high selec‐ tivity, by which a target protein could easily be separated in one step with thousands fold of

Development of an AC media is much more complex than that other chromatography. It needs not only a specific ligand, but also complex coupling process to couple the ligand to the matrix without reducing its binding activity significantly. Therefore more and more ready-to-use matrices, which already have active ligands coupled to, were developed commercially to satisfy different separation. If no suitable ligand is available, it can be considered to develop

The mostly used material is agarose or cross-linked agarose. The hydroxyl groups on the sugar resides are easily derivatized for covalent attachment of a ligand or spacer arms and the porous

The binding site of a target protein often locates deep within the molecule. Due to steric interference, a small ligand directly coupled to the matrix always shows a lower affinity with the target protein than in their free state. To overcome this situation, spacer arms, typically linear molecules with different chain length, are used to bridge ligands and matrix. In general a spacer arm is necessary in coupling ligands Mw <1000, and not need for larger ligands (Figure 12). An ideal spacer arms should have active groups at two ends by which it can be covalently coupled with matrix and ligand respectively. After coupling with matrix and ligand, the arms should be chemically stable to avoid reaction with other solutes and be hydrophilic to avoid

a specific affinity medium or use alternative purification techniques.

structure also supplies ideal flow rate and high capacity.

the hydrophobic interaction with proteins.

A coupling procedure of ligand is generally composed of three steps. First a group on matrix or spacer arm is activated by an activating agent. And then the activated group reacts with a functional group on ligand molecules. Finally, residual unreacted groups are blocked by blocking agent [23]. A matrix can be coupled with a ligand by a chemical group on itself or by groups on spacer arms. A variety of spacer arms are available to couple with to functional groups on ligands such as amino, hydroxyl, carboxyl, thiol groups (Figure 13).

**Figure 13.** Commonly used spacer arms and immobilization procedures of ligands. (A) Ligands are directly coupled with matrix by reaction between Cyanogen bromide activated hydroxyl on matrix and amino group on ligand. (B) Li‐ gands are coupled with spacer arms by reaction between N-hydroxysuccinimide activated carboxyl and amino group on ligand. (C) Lgands couple with spacer arms by reaction with epoxy group. (D) Coupling through condensation be‐ tween a free amino and a free carboxyl group. (E) Coupling through bisulfide bond or additive reaction between sila‐ nol and double bond in ligand, such as N=N or C=N.

## *6.1.4. Steric interference*

For a small ligand, it should be paid attentions to the influences of steric interference even if a spacer arm has been used. For small ligands the amount of each functional group is rare. even just one. A bad choice that makes a wrong spatial orientation in coupling will likely cause a serious decrease in binding capacity or even complete failure. On the contrary, large ligands have several equivalent groups through which coupling takes place, so that a large proportion couplings leave sufficient space for binding with target molecules (Figure 14). Therefore in coupling a small ligand, it is important to choose a suitable functional group without intro‐ ducing significant steric interference. The information of structure can be obtained from databases of X-ray crystal diffraction or NMR, or prediction by computational biology.

**Figure 14.** The influences of steric interference to small and large ligands. (A) For a small ligand, an inappropriate cou‐ pling orientation likely results in steric interference and inefficient adsorption. (B) This situation is less happened on large ligands.

#### **6.2. Binding and elution**

**Figure 13.** Commonly used spacer arms and immobilization procedures of ligands. (A) Ligands are directly coupled with matrix by reaction between Cyanogen bromide activated hydroxyl on matrix and amino group on ligand. (B) Li‐ gands are coupled with spacer arms by reaction between N-hydroxysuccinimide activated carboxyl and amino group on ligand. (C) Lgands couple with spacer arms by reaction with epoxy group. (D) Coupling through condensation be‐ tween a free amino and a free carboxyl group. (E) Coupling through bisulfide bond or additive reaction between sila‐

nol and double bond in ligand, such as N=N or C=N.

56 Protein Engineering - Technology and Application

An ideal binding buffer should be optimized to ensure efficient interaction between target molecules and ligands and minimize the nonspecific interaction at same time. Since the ligandprotein interaction is a result of combination of electrostatic attraction, hydrophobic interaction and hydrogen bonds, the binding conditions can be optimized on these aspects.

Adsorbed proteins could be eluted by modification of pH value, ionic strength, or polarity. pH value could be decrease to pH 2~3 to reduce the charge property of interaction surface between proteins. For example, immunoglubin could be adsorbed by a protein A column and eluted by a glycine buffer with pH 3.0. But the eluted sample should be neutralized as soon as possible to avoid being destroyed in extreme circumstance.

The ionic interaction also can be weakened by adding neutral salt, for example 1M NaCl is frequently used in practice.

A specific elution can be performed by adding competitors of either ligands or target proteins in elution buffer. An ideal competitor should have a moderate dissociation coefficient to the ligand or the target molecule, so that the competitor can elute target with high concentration but can be easily removed from column by wash or isolated from target protein by dialysis. Two classic applications is affinity chromatography of Glutathione S-transferase (GST) and polyhistdine [24] (Figure 15).

In binding process, flow rate should be control at a relative low degree to ensure an effective binding capacity.

**Figure 15.** Different elution mechanisms in GST affinity chromatography and metal chelate interaction chromatogra‐ phy (A) In GST purification, GST is captured by a medium with immobilized glutathione, and then dissociated by add‐ ing excess reduced glutathione. The excess glutathione is eluted together with target protein and removed by dialysis. (B) In nickel ion chelate interaction chromatography, protein with polyhistidine sequence is adsorbed by a medium with immobilized ionized nickel through a chelation between nickel ion and imidazolyl on polyhistidine sequence. The protein is eluted by adding high concentration of imidazol, a competitor of the imidazolyl on the protein. Finally, the small competitor is washed away from column by binding buffer.

## **6.3. Tag purification strategy**

eluted by a glycine buffer with pH 3.0. But the eluted sample should be neutralized as soon as

The ionic interaction also can be weakened by adding neutral salt, for example 1M NaCl is

A specific elution can be performed by adding competitors of either ligands or target proteins in elution buffer. An ideal competitor should have a moderate dissociation coefficient to the ligand or the target molecule, so that the competitor can elute target with high concentration but can be easily removed from column by wash or isolated from target protein by dialysis. Two classic applications is affinity chromatography of Glutathione S-transferase (GST) and

In binding process, flow rate should be control at a relative low degree to ensure an effective

**Figure 15.** Different elution mechanisms in GST affinity chromatography and metal chelate interaction chromatogra‐ phy (A) In GST purification, GST is captured by a medium with immobilized glutathione, and then dissociated by add‐ ing excess reduced glutathione. The excess glutathione is eluted together with target protein and removed by dialysis. (B) In nickel ion chelate interaction chromatography, protein with polyhistidine sequence is adsorbed by a medium with immobilized ionized nickel through a chelation between nickel ion and imidazolyl on polyhistidine sequence. The protein is eluted by adding high concentration of imidazol, a competitor of the imidazolyl on the protein. Finally, the

small competitor is washed away from column by binding buffer.

possible to avoid being destroyed in extreme circumstance.

frequently used in practice.

58 Protein Engineering - Technology and Application

polyhistdine [24] (Figure 15).

binding capacity.

AC separates protein typically on the basis of interactions between ligands and local domains of target proteins. The interactions are not interfered by other domains in most case. Therefore, the tag purification strategy was invented to rapidly separate recombinant protein by fusion expression and co-separation [25].

First the target protein is expressed with a tag protein in fusion form. Then the target protein is purified using an affinity column that is specific to tag protein. After that if the tag needs to be removed, a restrictive protease is used to hydrolyze the fusion protein and the freed tag is finally be separated from target protein by running the same column once again.

The ideal tag protein should (1) have economical affinity chromatography media for conven‐ ient separation, (2) be very stable in bioactivity, and (3) have a good expressing property that is helpful to increase the expression of target protein. Commonly used tags are GST tag, FLAG tag, S tag, Strep tag, His tag, and so on.

## **6.4. Application**

Affinity chromatography is a rapid and efficient chromatography technique. The high specific biorecognition give the technique an extremely high selectivity, by which a protein or a group of proteins could be separated from a crude sample in one step and reaches to a satisfying purify. However the excellent performance is based on the complex productive technology. Development of each noval medium needs a plenty of trials on finding suitable ligand and coupling the ligand on matrix properly. It is worth time and effort to develop a new specific affinity medium for high scale protein production, otherwise, the alternative method such as tag purfication or other chromatography should be a better choice for small scale preparation in expiremental research.

## **7. Summary**

This chapter introduces principles and applications of several basic chromatography techni‐ ques. Different techniques separate proteins depending on different properties including net surface charge, hydrophobicity, molecular size, and affinity interaction. Affinity chromatog‐ raphy has the highest selectivity and can purify target proteins in one step to > 95% purify. But due to the difficulties on obtaining and immobilization of suitable ligand, this chromatography technique is not used as widely as other ones. HIC and RPC are both based upon hydrophobic interaction. PRC is widely used in analytic separation because of its high resolution, but less used on preparative separation of proteins since the high nonpolarity of the eluent likely causes irreversible inactivation of proteins. IEXC, HIC and SEC separate proteins in mild conditions and are suitable for large scale separation of active proteins. However, their resolutions are comparatively lower and hard to purify a protein from complex components by a single technique. An ideal purification could be achieved by combined application of several techniques.

## **Author details**

Jingjing Li1 , Wei Han1 and Yan Yu2

1 Laboratory of Regeneromics, School of Pharmacology, Shanghai Jiao Tong University, Shanghai, China

2 School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China

## **References**

[12] Parente, E. S, & Wetlaufer, D. B. Relationship between isocratic and gradient reten‐ tion times in the high-performance ion-exchange chromatography of proteins. Theo‐ ry and experiment, *J Chromatogr*, (1986).

**Author details**

Shanghai, China

**References**

, Wei Han1

60 Protein Engineering - Technology and Application

and Yan Yu2

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powdered cellulose, *Nature*, (1948).

tion in open hole tubes, *J Chromatogr*, (1963).

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1 Laboratory of Regeneromics, School of Pharmacology, Shanghai Jiao Tong University,

[2] Dorsey, J. G, Foley, J. P, & Cooper, W. T. Liquid chromatography: theory and meth‐

[3] Hough, L, Jones, J. K, & Wadman, W. H. Application of paper partition chromatogra‐ phy to the separation of the sugars and their methylated derivatives on a column of

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[5] Dorsey, J. G, Cooper, W. T, & Wheeler, J. F. Liquid chromatography: theory and

[6] Cashman, P. J, & Thornton, J. I. High speed liquid adsorption chromatography in

[7] Woods, M. C, & Simpson, M. E. Purification of sheep pituitary follicle-stimulating hormone (FSH) by ion exchange chromatography on diethylaminoethyl (DEAE)-cel‐

[8] Melander, W. R, Corradini, D, & Horvath, C. Salt-mediated retention of proteins in hydrophobic-interaction chromatography. Application of solvophobic theory, *J Chro‐*

[9] Biswas, K. M, Devido, D. R, & Dorsey, J. G. Evaluation of methods for measuring

[10] Zhang, Y, & Cremer, P. S. Interactions between macromolecules and ions: The Hof‐

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2 School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China

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criminalistics. I. Theory and practice, *J Forensic Sci Soc*, (1971).

Jingjing Li1

## **Protein-Protein and Protein-Ligand Docking**

Alejandra Hernández-Santoyo, Aldo Yair Tenorio-Barajas, Victor Altuzar, Héctor Vivanco-Cid and Claudia Mendoza-Barrera

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/56376

## **1. Introduction**

Molecular interactions including protein-protein, enzyme-substrate, protein-nucleic acid, drug-protein, and drug-nucleic acid play important roles in many essential biological proc‐ esses, such as signal transduction, transport, cell regulation, gene expression control, enzyme inhibition, antibody–antigen recognition, and even the assembly of multi-domain proteins. These interactions very often lead to the formation of stable protein–protein or protein-ligand complexes that are essential to perform their biological functions. The tertiary structure of proteins is necessary to understand the binding mode and affinity between interacting molecules. However, it is often difficult and expensive to obtain complex structures by experimental methods, such as X-ray crystallography or NMR. Thus, docking computation is considered an important approach for understanding the protein-protein or protein-ligand interactions [1-3]. As the number of three-dimensional protein structures determined by experimental techniques grows —structure databases such as Protein Data.

Bank (PDB) and Worldwide Protein Data Bank (wwPDB) have over 88000 protein structures, many of which play vital roles in critical metabolic pathways that may be regarded as potential therapeutic targets — and specific databases containing structures of binary complexes become available, together with information about their binding affinities, such as in PDBBIND [4], PLD [5], AffinDB [6] and BindDB [7], molecular docking procedures improve, getting more importance than ever [8].

Molecular docking is a widely used computer simulation procedure to predict the conforma‐ tion of a receptor-ligand complex, where the receptor is usually a protein or a nucleic acid molecule and the ligand is either a small molecule or another protein (Figure 1).

© 2013 Hernández-Santoyo et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 Hernández-Santoyo et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**Figure 1.** Elements in molecular docking.

The accurate prediction of the binding modes between the ligand and protein is of fundamental importance in modern structure-based drug design. The most important application of docking software is the virtual screening, in which the most interesting and promising molecules are selected from an existing database for further research. This places demands on the used computational method: it must be fast and reliable. Another application is the research of molecular complexes.

Since the pioneering work of Kuntz *et al*. [9] during the early 1980s, significant progress has been made in docking research to improve the computational speed and accuracy. Over the last years several important steps beyond this point have been given. Handling efficiently the flexibility of the protein receptor is currently considered one of the major challenges in the field of docking. The binding-site location and binding orientation can be greatly influenced by protein flexibility. In fact, X-ray structure determination of protein–ligand complexes frequently reveals ligands with a buried surface area in the range of 70–100%, which can only be achieved as a consequence of protein flexibility [3]. There are many interesting docking suites and algorithms that have shown significant progress in predicting near-native binding poses by making use of biophysical and biochemical information combination with bioinfor‐ matics.

## **2. Theory**

Modeling the interaction of two molecules is a complex problem. Many forces are involved in the intermolecular association, including hydrophobic, van der Waals, or stacking interactions between aromatic amino acids, hydrogen bonding, and electrostatic forces. Modeling the intermolecular interactions in a ligand-protein complex is difficult since there are many degrees of freedom as well as insufficient knowledge of the effect of solvent on the binding association. The process of docking a ligand to a binding site tries to mimic the natural course of interaction of the ligand and its receptor via the lowest energy pathway [3]. There are simple methods for docking rigid ligands with rigid receptors and flexible ligands with rigid recep‐ tors, but general methods of docking considering conformationally flexible ligands and receptors are problematic. Docking protocols can be described as a combination of a search algorithm, and the scoring functions (Figure 2).

**Figure 2.** Methods used for protein-ligand docking.

**Figure 1.** Elements in molecular docking.

64 Protein Engineering - Technology and Application

of molecular complexes.

matics.

**2. Theory**

The accurate prediction of the binding modes between the ligand and protein is of fundamental importance in modern structure-based drug design. The most important application of docking software is the virtual screening, in which the most interesting and promising molecules are selected from an existing database for further research. This places demands on the used computational method: it must be fast and reliable. Another application is the research

Since the pioneering work of Kuntz *et al*. [9] during the early 1980s, significant progress has been made in docking research to improve the computational speed and accuracy. Over the last years several important steps beyond this point have been given. Handling efficiently the flexibility of the protein receptor is currently considered one of the major challenges in the field of docking. The binding-site location and binding orientation can be greatly influenced by protein flexibility. In fact, X-ray structure determination of protein–ligand complexes frequently reveals ligands with a buried surface area in the range of 70–100%, which can only be achieved as a consequence of protein flexibility [3]. There are many interesting docking suites and algorithms that have shown significant progress in predicting near-native binding poses by making use of biophysical and biochemical information combination with bioinfor‐

Modeling the interaction of two molecules is a complex problem. Many forces are involved in the intermolecular association, including hydrophobic, van der Waals, or stacking interactions between aromatic amino acids, hydrogen bonding, and electrostatic forces. Modeling the intermolecular interactions in a ligand-protein complex is difficult since there are many degrees of freedom as well as insufficient knowledge of the effect of solvent on the binding association. The process of docking a ligand to a binding site tries to mimic the natural course of interaction of the ligand and its receptor via the lowest energy pathway [3]. There are simple methods for docking rigid ligands with rigid receptors and flexible ligands with rigid recep‐ tors, but general methods of docking considering conformationally flexible ligands and

The search algorithm should create an optimum number of configurations that include the experimentally determined binding modes. Although a rigorous searching algorithm would go through all possible binding modes between the two molecules, this search would be impractical due to the size of the search space and amount of time it might take to complete. As a consequence, only a small amount of the total conformational space can be sampled, so a balance must be reached between the computational expense and the amount of the search space examined. Some common searching algorithms include molecular dynamics, Monte Carlo methods, genetic algorithms, fragment-based, point complementary and distance geometry methods, Tabu, and systematic searches. On the other hand, scoring function consists of a number of mathematical methods used to predict the strength of the non-covalent interaction called the binding affinity. In all the computational methodologies, one important problem is the development of an energy scoring function that can rapidly and accurately describe the interaction between the protein and ligand. Several reviews on scoring are available in the literature [10-12].

There are three important applications of scoring functions in molecular docking. First is to determine the binding mode and site of a ligand on a protein. The second application is to predict the absolute binding affinity between protein and ligand. This is particularly important in lead optimization. The third application, and perhaps the most important one in structurebased drug design, is to identify the potential drug hits/leads for a given protein target by searching a large ligand database. Over the course of the last years, different scoring functions have been developed that exhibit different accuracies and computational efficiencies. Some of these commonly-used functions are: force-field, empirical, knowledge-based and consensus scoring.

The protein-ligand docking procedure can be typically divided into two parts: rigid body docking and flexible docking [9].

## **3. Experimental docking procedures**

There are a number of excellent reviews of molecular docking methods and a large number of publications comparing the performance of a variety of molecular docking tools [1-3], [13]. Following, we will describe the four-step procedure adopted in this study to perform the molecular docking.

### **3.1. Target selection**

Ideally, the target structure should be determined experimentally by either X-ray crystallog‐ raphy or nuclear magnetic resonance, which can be downloaded from PDB; however, docking has been performed successfully in comparison to homology models or threading. The model should have good quality. It can be tested using validation software such as Molprobity [14]. After selecting the model, it must be prepared by removing the water molecules from the cavity, stabilizing charges, filling the missing residues, and generating the side chains, all according to the available parameters. The receptor should be at this point biologically active and in the stable state.

## **3.2. Ligand selection and preparation**

The type of ligands chosen for docking will depend on the goal. It can be obtained from various databases, e.g. ZINC or/and PubChem, or it can be sketched by means of Chemsketch tool [8]. Often it is necessary to apply filters to reduce the number of molecules to be docked. Examples include the net charge, molecular weight, polar surface area, solubility, commercial availabil‐ ity, similarity thresholds, pharmacophores, synthetic accessibility, and absorption, distribu‐ tion, metabolism, excretion, and toxicology properties. Many times the researchers design their own molecules such as those generated by us in the example that will be described in this work in the section 5.

## **3.3. Docking**

predict the absolute binding affinity between protein and ligand. This is particularly important in lead optimization. The third application, and perhaps the most important one in structurebased drug design, is to identify the potential drug hits/leads for a given protein target by searching a large ligand database. Over the course of the last years, different scoring functions have been developed that exhibit different accuracies and computational efficiencies. Some of these commonly-used functions are: force-field, empirical, knowledge-based and consensus

The protein-ligand docking procedure can be typically divided into two parts: rigid body

**1.** *Rigid Docking*. This approximation treats both the ligand and the receptor as rigid and explores only six degrees of translational and rotational freedom, hence excluding any kind of flexibility. Most of the docking suites employ rigid body docking procedure as a

**2.** *Flexible Docking*. A more common approach is to model the ligand flexibility while assuming having a rigid protein receptor, considering thereby only the conformational space of the ligand. Ideally, however, protein flexibility should also be taken into account, and some approaches in this regard have been developed. There are three general categories of algorithms to treat ligand flexibility: systematic methods, random or stochastic methods, and simulation methods [3]. Due to the large size of proteins and their multiple degrees of freedom, their flexibility may be the most challenging issue in molecular docking. The methods to address the flexibility of proteins can be grouped into: soft docking, side-chain flexibility, molecular relaxation and protein ensemble docking.

There are a number of excellent reviews of molecular docking methods and a large number of publications comparing the performance of a variety of molecular docking tools [1-3], [13]. Following, we will describe the four-step procedure adopted in this study to perform the

Ideally, the target structure should be determined experimentally by either X-ray crystallog‐ raphy or nuclear magnetic resonance, which can be downloaded from PDB; however, docking has been performed successfully in comparison to homology models or threading. The model should have good quality. It can be tested using validation software such as Molprobity [14]. After selecting the model, it must be prepared by removing the water molecules from the cavity, stabilizing charges, filling the missing residues, and generating the side chains, all according to the available parameters. The receptor should be at this point biologically active

scoring.

first step.

molecular docking.

**3.1. Target selection**

and in the stable state.

docking and flexible docking [9].

66 Protein Engineering - Technology and Application

They were described by Huang *et al* [1].

**3. Experimental docking procedures**

This is the last step, where the ligand is docked onto the receptor and the interactions are checked. The scoring function generates a score depending on the best selected ligand.

## **3.4. Evaluating docking results**

The success of docking algorithms in predicting a ligand binding pose is normally measured in terms of the root-mean-square deviation (RMSD) between the experimentally-observed heavy-atom positions of the ligands and the one(s) predicted by the algorithm. The flexibility of the system is a major challenge in the search for the correct pose. The number of degrees of freedom included in the conformational search is a central aspect that determines the searching efficiency [3]. A good performance is usually considered when the RMSD is less than 2Å.

### **3.5. Docking software description**

There are many algorithms available to assess and rationalize ligand-protein or proteinprotein interactions, and their number is constantly increasing. Speed and accuracy are key features for obtaining successful results in docking approaches. Several algorithms share commonmethodologieswithnovelextensionsfocusedonobtainingafastmethodwithaccuracy as high as possible. The most common docking programs include AutoDock [15], DOCK [9], FlexX[16],GOLD[17],ICM[18],ADAM[19],DARWIN [20],DIVALI[21], andDockVision[22].

## **4. Application of molecular docking to a particular case — Biopolymers docked to dengue virus E protein**

In the last decades, the incidence of Dengue disease has dramatically increased around the world. About 2.5 billion persons (two fifth of the world population) are exposed to the risk of contracting the disease. Every year, dengue virus (DENV) infects more than 50 million people, with approximately 22 000 fatal cases [23]. The disease is endemic in more than 100 countries of Africa, America, Oriental Mediterranean, Southeast Asia, and the Western Pacific Ocean with the last two regions being the most affected by the disease. Before 1970 only nine countries suffered from the Hemorrhagic Dengue (HD) epidemics, number that in 1995 was multiplied for more than four. There are four antigenically distinct, but closely related, serotypes of dengue virus (DENV), which is a Flavivirus member of the family Flaviviridae [24]. Each serotype has genotypes, which are virulent at several levels; nevertheless, the factors of virulence are not totally established [25]. A better understanding of the mechanisms and the molecules involved in the key steps of the DENV transmission cycle may lead to the identifi‐ cation of new anti-dengue targets [26]. In fact, the presence of two or more serotypes in the same geographical region implies a growing risk to population of contracting Hemorrhagic Dengue or Dengue Shock Syndrome (SSD) due to a phenomenon known as the Antibody – Dependent Enhancement (ADE). As a result, the diagnosis and treatment of dengue disease has become a world-wide global problem to deal with. The mature DENV virion contains three structural proteins: capsid protein (C), membrane protein (M), and envelope protein (E). In particular, the DENV E glycoprotein (51-60 kDa~ 495 aa), found on the viral surface, is important in the initial attachment of the viral particle to the host cell, as it contains two Nlinked glycosylation sites at Asn-67 and Asn-153. While the glycosylation site at position 153 is conserved in most flaviviruses, the site at position 67 is thought to be unique for dengue virus. N-linked oligosaccharide side chains on flavivirus E proteins have been associated with viral morphogenesis, infectivity, and tropism [27, 28]. In addition, E protein is closely associ‐ ated with the lipid envelope containing a cellular receptor-binding site (s) and a fusion peptide [29]. It can be found in a form of a homodimer on the surface of the mature virion, and inside the cell, it creates a prM-E heterodimer together with the prM protein. E protein is the principal component of the virion surface, containing the antigenic determinants (epitopes) responsible for the neutralization of the virus and the hemagglutination of erythrocytes, inducing thereby an immunological response in the infected host [29]. On native virions, the elongated threedomain E molecule is positioned tangentially to the virus envelope in a head-to-tail homodi‐ meric conformation. Upon penetration of the virion into the target cell endosome, E dimers are converted into stable target-cell membrane-inserted homotrimers that reorient themselves vertically to promote virus-cell fusion at low pH [30]. Furthermore, there is a great deal of evidence that E protein contains the majority of molecular markers for pathogenicity. Com‐ paring the nucleotide sequence of the E protein gene in different flaviviruses has demonstrated a perfect conservation of 12 cysteine residues, which form six disulfide bridges. The structural model for the E protein was refined by Mandl and co-workers [31], who correlated the structural properties of different epitopes with disulfide bonds [32].

#### **4.1. Biopolymers as potential adjuvants carriers**

The aim of this work is to study the docking of monomers of polyvinylpyrrolidone (PVP), chitosan (CS), and chitosan-tripropylphosphate-chitosan (CS/TPP/CS) with E protein of dengue virus in order to use them as potential adjuvant carriers. Given their structure, these polymers have specific molecular anchor sites that are expected to be exploited to induce antigenic specificity to the conserved regions of dengue virus. Several authors report that the E protein produces immunity and confers protection against infection in mice with low levels of neutralizing antibodies [33-35]. Because of the dual role of its receptors as well as the cell entry through membrane fusion, the E protein, apart from being the most exposed protein, is the main target against which the neutralizing antibodies are produced to inhibit its functions.

At present, the biggest challenge in developing an efficient dengue vaccine is to achieve a lifelong protective immune response to all 4 serotypes (DEN1-4) simultaneously. Although several vaccines are currently being developed, so far only a chimeric dengue vaccine for live attenuated yellow fever (YF) has reached stage 3 in clinical trials. The candidate vaccines can be divided into the following types: (a) live attenuated, (b) DEN-DEN and DEN-YF live chimeric virus, (c) inactivated whole virus, (d) live recombinant, (e) DNA, and (f) subunit vaccines [36].

Chitosan is a polycationic polymer comprising of D-glucosamine and N-acetyl-D-glucosamine linked by β(1,4)-glycosides' bonds. It is produced by deacetylation of chitin, which is extracted from the shells of crabs and shrimp. It is a linear, hydrophilic, positively charged, water soluble biopolymer, can form thin films, hydrogels, porous scaffolds, fibers, and micro and nanopar‐ ticles in mild acidity conditions. As a polycationic polymer, it has a high affinity to associate macromolecules such as insulin, pDNA, siRNA, heparin, among others, with antigenic molecules, protecting them in turn from hydrolytic and enzymatic degradation [37].

Polyvinylpyrrolidone (N-vinyl-2-pyrrolidone, PVP) has chemical, physical and physiological properties which have been exploited in various industries, including but not limited to medical, pharmaceutical, cosmetic, food, and textile, due to its biological compatibility, low toxicity, tackiness, resistance to thermal degradation in solutions as well as inert behavior in salt and acidic solutions [38, 39]. It is a water soluble homopolymer with a wide range of molecular weights (2.5 to 1.200 kDa), molecules between 12 and 1350 monomers, and end-toend distances ranging from 2.3 to 93 nanometers. It is physically and chemically stable; it tolerates heating and air atmospheres for up to 16 hours at 100 °C, as well as the change of appearance for 2 months at 24 ° C and 15% HCl. When heated with strong bases such as lithium carbonate, trisodium phosphate or sodium metasilicate, it generates a precipitate due to the ring opening and subsequent crosslinking of chains. Yen-Jen *et al*. studied its effect as a drug deliverer and intracellular acceptor [40].

### *4.1.1. Molecular docking*

suffered from the Hemorrhagic Dengue (HD) epidemics, number that in 1995 was multiplied for more than four. There are four antigenically distinct, but closely related, serotypes of dengue virus (DENV), which is a Flavivirus member of the family Flaviviridae [24]. Each serotype has genotypes, which are virulent at several levels; nevertheless, the factors of virulence are not totally established [25]. A better understanding of the mechanisms and the molecules involved in the key steps of the DENV transmission cycle may lead to the identifi‐ cation of new anti-dengue targets [26]. In fact, the presence of two or more serotypes in the same geographical region implies a growing risk to population of contracting Hemorrhagic Dengue or Dengue Shock Syndrome (SSD) due to a phenomenon known as the Antibody – Dependent Enhancement (ADE). As a result, the diagnosis and treatment of dengue disease has become a world-wide global problem to deal with. The mature DENV virion contains three structural proteins: capsid protein (C), membrane protein (M), and envelope protein (E). In particular, the DENV E glycoprotein (51-60 kDa~ 495 aa), found on the viral surface, is important in the initial attachment of the viral particle to the host cell, as it contains two Nlinked glycosylation sites at Asn-67 and Asn-153. While the glycosylation site at position 153 is conserved in most flaviviruses, the site at position 67 is thought to be unique for dengue virus. N-linked oligosaccharide side chains on flavivirus E proteins have been associated with viral morphogenesis, infectivity, and tropism [27, 28]. In addition, E protein is closely associ‐ ated with the lipid envelope containing a cellular receptor-binding site (s) and a fusion peptide [29]. It can be found in a form of a homodimer on the surface of the mature virion, and inside the cell, it creates a prM-E heterodimer together with the prM protein. E protein is the principal component of the virion surface, containing the antigenic determinants (epitopes) responsible for the neutralization of the virus and the hemagglutination of erythrocytes, inducing thereby an immunological response in the infected host [29]. On native virions, the elongated threedomain E molecule is positioned tangentially to the virus envelope in a head-to-tail homodi‐ meric conformation. Upon penetration of the virion into the target cell endosome, E dimers are converted into stable target-cell membrane-inserted homotrimers that reorient themselves vertically to promote virus-cell fusion at low pH [30]. Furthermore, there is a great deal of evidence that E protein contains the majority of molecular markers for pathogenicity. Com‐ paring the nucleotide sequence of the E protein gene in different flaviviruses has demonstrated a perfect conservation of 12 cysteine residues, which form six disulfide bridges. The structural model for the E protein was refined by Mandl and co-workers [31], who correlated the

structural properties of different epitopes with disulfide bonds [32].

The aim of this work is to study the docking of monomers of polyvinylpyrrolidone (PVP), chitosan (CS), and chitosan-tripropylphosphate-chitosan (CS/TPP/CS) with E protein of dengue virus in order to use them as potential adjuvant carriers. Given their structure, these polymers have specific molecular anchor sites that are expected to be exploited to induce antigenic specificity to the conserved regions of dengue virus. Several authors report that the E protein produces immunity and confers protection against infection in mice with low levels of neutralizing antibodies [33-35]. Because of the dual role of its receptors as well as the cell

**4.1. Biopolymers as potential adjuvants carriers**

68 Protein Engineering - Technology and Application

In this work, the molecular docking calculations were performed using the AutoDock program. In particular, it uses a Lamarckian genetic algorithm (LGA) and a force field function based approximately on the AMBER force field, which consists of five terms: 1) the 12-6 dispersion term of Lennard-Jones, 2) a 12-10 directional hydrogen bonding term, 3) an electrostatic Coulomb potential, 4) an entropic term, and 5) one term of desolvation pairs. The scaling factor of these terms is empirically calibrated using a set of 30 structurally-known protein-ligand complexes, which affinities have been experimentally determined. The AutoDock program has become widely used due to its good precision and high versatility; moreover, the latest version of AutoDock (version 4.0) added flexible functions to the side chains in the receptor.

#### *4.1.2. Model preparation*

In this study we used the E protein of dengue virus. It consists of a dimer with 394 amino acids (aa) per monomer and, as mentioned before, it is the main component of the dengue virus envelope. E protein enters the cell by fusion with the membrane due to a previous conforma‐ tional change produced by a low pH, generating thereby a change of form from dimer to trimer, in which the fusion peptide between the II and III domains is exposed. When the pH is lower than 6.3, dimers dissociate from dimer phase, making the I and II domains rotate outwards and exposing the fusion loop, which interacts with the endosomal membrane of the cell. Domain III then rotates backwards to pull the I and II domains, which were already bound to the cell membrane by the fusion peptide, thus attaching the cell membrane with the membrane of the virus in order to release the RNA [27, 29, 41-45]. It is important to mention that Bressanelli showed that the virus domains remain at neutral pH but their relative orientation is altered [27]. For best results during the molecular docking process, we optimize the original model of the dengue virus protein E (PDB code 1OKE) with a number of refinements and validations cycles with Phenix and Molprobity programs respectively. Figure 3 shows the corrected model of the dimer and trimer.

**Figure 3.** Dengue virus protein E. (A) Dimeric protein after geometric and refining corrections with Phenix program. (B) Trimeric protein that represents a postfusion state (C) Top view of the trimeric form. Domain I (aa1-52,132-193,280-296) is in red, domain II (aa52-132, 193-280) in yellow and domain III (aa296-394) in blue color.

## *4.1.3. Ligands preparation*

*4.1.2. Model preparation*

70 Protein Engineering - Technology and Application

of the dimer and trimer.

In this study we used the E protein of dengue virus. It consists of a dimer with 394 amino acids (aa) per monomer and, as mentioned before, it is the main component of the dengue virus envelope. E protein enters the cell by fusion with the membrane due to a previous conforma‐ tional change produced by a low pH, generating thereby a change of form from dimer to trimer, in which the fusion peptide between the II and III domains is exposed. When the pH is lower than 6.3, dimers dissociate from dimer phase, making the I and II domains rotate outwards and exposing the fusion loop, which interacts with the endosomal membrane of the cell. Domain III then rotates backwards to pull the I and II domains, which were already bound to the cell membrane by the fusion peptide, thus attaching the cell membrane with the membrane of the virus in order to release the RNA [27, 29, 41-45]. It is important to mention that Bressanelli showed that the virus domains remain at neutral pH but their relative orientation is altered [27]. For best results during the molecular docking process, we optimize the original model of the dengue virus protein E (PDB code 1OKE) with a number of refinements and validations cycles with Phenix and Molprobity programs respectively. Figure 3 shows the corrected model

**Figure 3.** Dengue virus protein E. (A) Dimeric protein after geometric and refining corrections with Phenix program. (B) Trimeric protein that represents a postfusion state (C) Top view of the trimeric form. Domain I (aa1-52,132-193,280-296) is

in red, domain II (aa52-132, 193-280) in yellow and domain III (aa296-394) in blue color.

To prepare the ligands, we utilized the linear PVP and CS monomers, and CS/TPP/CS chains (Figure 4). The coordinates of those ligands were obtained using the SMILES program [46].

**Figure 4.** Ligands used in molecular docking. (A) PVP monomer, (B) CS monomer, and (C) CS/TPP/CS chain.

#### *4.1.4. Molecular docking*

Molecular docking was performed by means of the AutoDock program that combines rapid grid-based energy evaluation and efficient search of torsional freedom. This program uses a semi-empirical free energy force field to evaluate the conformations during the docking simulations. The force field is quantified using a large number of protein-inhibitor complexes, for which the inhibition constants (Ki ), are known. The force field evaluates the union in two steps, first when the ligand and the protein are separated. Then, the intramolecular energies are estimated for the transition from the unbound state to the protein-ligand bound state. In the second step, intermolecular energies are evaluated by combining the ligand with the protein conformations bound to themselves. The force field includes six pairs-wise of evalu‐ ations (Vi) and an estimated loss of conformational entropy after binding (ΔSconf):

$$
\Delta G = \left( V\_{bound}^{\;L\;-L} - V\_{umbound}^{\;L\;-L} \right) + \left( V\_{bound}^{\;P\;-P} - V\_{umbound}^{\;P\;-P} \right) + \left( V\_{bound}^{\;P\;-L} - V\_{umbound}^{\;P\;-L} + \Delta S\_{conf} \right) \tag{1}
$$

where L refers to the ligand and P to the "protein" in a ligand-protein docking. Each of the pair-wise energetic terms includes evaluations for dispersion/repulsion, hydrogen bonding, electrostatics, and desolvation [47].

The calculations can be summarized in the following four steps: (1) preparation of files using AutoDockTools coordinates, (2) pre-calculation of atomic affinities by using AutoGrid, (3) docking of ligands by using AutoDock, and (4) analysis of the results applying AutoDockTools.

## **4.2. Results**

## *4.2.1. Amino acids of interest in the dengue virus infection mechanism*

In the loop conformation, several amino acids are involved in trimerization of unit E of DENV. These amino acids are of particular interest since they are allocated in between I and II domains, the fusion loop of the host cell located between domains II and III, and aa268-270 (kl loop). Also are important, the loop of fusion to the host cell located between domains II and III, which subsequently is exposed in the trimer with the aa98-111 fusion peptide, and the C-terminal of domain III, which holds the protein to the virus membrane. Other important amino acids were mentioned by Mazumder [48], who made a structural analysis of the dengue virus E protein of the 4 serotypes in order to find the conserved and exposed sites as well as the epitopes in the T-cell. In our study, we additionally considered the sites of interest described by Yorgo Modis [42, 43] (Table 1).

In addition to the ten conserved regions presented in Table 1, we predicted around 740 E proteins of the 4 serotypes, some of which are included in the same Table 1. Their sequences were quantified using Shannon's entropy [48] with a variation from 0.3 to 1.1 bits.

**Table 1.** Sites of interest identified in the structure of the dengue virus E protein according to Yorgo Modis [42, 43, 48].

The analyzed proteins can be identified as: N8-G14, V24-D42, R73-E79, V97-S102, D192-M196, V208-W220, V252-H261, G281-C285, E314-T319, E370-G374, and K394-G399; whereas the hidden amino acids, which change to exposed amino acids in the trimer, can be listed as follows: M1, H244, K246, G254, G330 and K344; and the exposed residues that remain hidden include the following: S16, Q52, Q167, S169, P243, D290, Q293, S331 and E343. It is worth mentioning that we have identified at least 14 conserved negative sites in at least 3 of the 4 serotypes (C3, C60, R73, T189, F213, A267, F306, T319, S376, F392, K394, S424, G445, and V485). The importance of this discovery relies on the fact that it has demonstrated that the epitopes with negative sites work better as vaccines than those with positive sites as they are less likely to change due to their functional restrictions.

#### *4.2.2. Dengue virus E protein — PVP docking*

**4.2. Results**

72 Protein Engineering - Technology and Application

Modis [42, 43] (Table 1).

L191,T268-I270 This region is known as kl

V382-G385 C terminal that attaches

D98-G111 The loop is protected

*4.2.1. Amino acids of interest in the dengue virus infection mechanism*

In the loop conformation, several amino acids are involved in trimerization of unit E of DENV. These amino acids are of particular interest since they are allocated in between I and II domains, the fusion loop of the host cell located between domains II and III, and aa268-270 (kl loop). Also are important, the loop of fusion to the host cell located between domains II and III, which subsequently is exposed in the trimer with the aa98-111 fusion peptide, and the C-terminal of domain III, which holds the protein to the virus membrane. Other important amino acids were mentioned by Mazumder [48], who made a structural analysis of the dengue virus E protein of the 4 serotypes in order to find the conserved and exposed sites as well as the epitopes in the T-cell. In our study, we additionally considered the sites of interest described by Yorgo

In addition to the ten conserved regions presented in Table 1, we predicted around 740 E proteins of the 4 serotypes, some of which are included in the same Table 1. Their sequences

> The ligand is present; however, the kl loop does not adopt the open conformation present in the dimer-ligand pair.

It combines to create a trimeric contact with the other two domains.

It is exposed only in the trimeric conformation during the conformational changes, and it maintains

its structure.

N37, P207 Exposed. Exposed. Conserved epitope in the 4

A hinge allowing movement of domains I and II, as well as conformational changes when varying the pH of the

endosome.

serotypes.

4 serotypes.

serotypes.

It holds and folds the domains I and II, acting as a zipper. It is the most variable region among the 4

It is the region of highest interest since it is the binding receptor for the host cell. In the trimeric form it fuses and binds the cell and virus's membranes. It is the most conserved region among the

were quantified using Shannon's entropy [48] with a variation from 0.3 to 1.1 bits.

**Amino acid Dimer configuration Trimer configuration Function**

loop, without the presence

domain III to premembrane

between the domain II and III; it contains a fusion peptide that is formed by hydrophobic residues.

of the ligand (β-Octylglucoside, BOG), it forms a salt bridge and a hydrogen bond with beta strand I and j of the counterpart dimer.

(prM) virus.

The docking of PVP molecules with the E protein of dengue virus has demonstrated that the interface of the I and II domain was the most energetically favorable site for the binding (Figure 5). The interaction between protein and ligand takes place by establishing 8 hydrogen bonds with the Asn124, Lys202, and Asp203 amino acids (Table 2). This region is extremely impor‐ tant for the pivotal role it plays in the conformational changes triggered by low pH, which in turn is closely related to the infectivity of the virus. In particular, the PVP molecule, which interacts with aa124,202,203 in the E protein-BOG ligand complex, could act as a blocker of the kl aa268-270 pitchfork activity, which is responsible for the conformational changes in the E proteinatlowpH.Inotherwords,it couldinhibittheirfunctiontoworkas ahinge for conforma‐ tional changes due to its proximity to amino acids through steric hindrance, preventing thereby the hinge action between the I and II domain, which in turn could stiffen the area. Alternative‐ ly, if BOG ligand is absent, the molecule could be internalized into the hydrophobic pocket and replace it, but the subsequent molecular prediction simulations would be required to deter‐ mine how it could act in the presence of low pH, in order to find out whether the conformation‐ al changes would appear or be inhibited. The PVP is well-known to be highly stable at acid pH and high temperatures, so its structural integrity is assured to remain intact; the loop or kl pitchfork amino acids mutate, resulting in an increase of the pH threshold, at which conforma‐ tional changes occur.Itis achievedby replacing long hydrophobic side chains by the short ones. As the result, the site can be consistently represented as a potential trigger in the virus replica‐ tion cycle and a good candidate to inhibit its function (Figure 5).

**Table 2.** Polar interactions of the PVP molecule with dengue virus E protein.

**Figure 5.** Dengue virus E protein with PVP ligand. The lower part shows a close up of the docking area.

## *4.2.3. Dengue virus E protein — CS docking*

the hinge action between the I and II domain, which in turn could stiffen the area. Alternative‐ ly, if BOG ligand is absent, the molecule could be internalized into the hydrophobic pocket and replace it, but the subsequent molecular prediction simulations would be required to deter‐ mine how it could act in the presence of low pH, in order to find out whether the conformation‐ al changes would appear or be inhibited. The PVP is well-known to be highly stable at acid pH and high temperatures, so its structural integrity is assured to remain intact; the loop or kl pitchfork amino acids mutate, resulting in an increase of the pH threshold, at which conforma‐ tional changes occur.Itis achievedby replacing long hydrophobic side chains by the short ones. As the result, the site can be consistently represented as a potential trigger in the virus replica‐

**PVP molecule Amino acid Distance (Å)**

tion cycle and a good candidate to inhibit its function (Figure 5).

74 Protein Engineering - Technology and Application

**Table 2.** Polar interactions of the PVP molecule with dengue virus E protein.

**Figure 5.** Dengue virus E protein with PVP ligand. The lower part shows a close up of the docking area.

O1 OD1-Asp 203 2.75 O2 OD1-Asp 203 2.44 O3 N-Asp 203 2.64 O3 N-Lys 202 2.58 O4 N-Lys 202 3.37 O4 O-Asn 124 2.92 O5 O-Asn 124 3.32 O5 N-Asn 124 2.87 The docking of CS molecules in the E protein of dengue virus resulted in the interaction with the interface of domain I and II of the protein (see Figure 6). The CS ligand binds to seven amino acids of E protein by ten hydrogen bonds (see Table 3). The elongated CS molecule settles into a channel formed in the II domain surface of the protein. Additionally, it interacts with amino acids near the kl hinge or loop of I and II domain interface. There is a remarkable familiarity between the BOG and NAG complexes. Amino acids-CS molecule interactions, which are shown in Table 10 (aa65,68,202,249,251,272,273), suggest that the mechanism of action of this molecule is similar to PVP ligand. Additionally, it is very close to the conserved region V252-H261 that forms a channel in the 4 serotypes. This finding is of the highest importance since it could very well serve as a ligand for the 4 serotypes, and it could be even more useful in the development of a chimera vaccine with the four domains III of E protein, which would be similar to the chimeric vaccine developed in India at the International Centre for Genetic Engineering and Bionanotechnology.

**Table 3.** CS molecule interactions with dengue virus E protein.

#### *4.2.4. Dengue virus E protein — CS/TPP/CS docking*

In this case, we used the CS and TPP monomers taking into account that the CS units form bindings by means of 1-4 beta bonds. Similarly to the E protein–PVP docking, the molecular docking between the CS/TPP/CS ligand and the E protein was carried out between the domains I and II, although we observed more interactions in the case of PVP monomer. Table 4 and Figure 7 illustrate seven interactions between the amino acids and the BOG. The CS-TPP-CS complex interacts with aa49, 124, 126, 200, 202, 203, 271 amino acids, and the docking results suggest that these three molecules are attracted the most to the area formed by the hydrophobic pocket, indicating that the latter molecule has a direct interaction with the BOG ligand oxygen.

**Table 4.** Docking of CS/TPP/CS molecule with dengue virus E protein.

**Figure 7.** CS/TPP/CS molecule docking with the dengue virus E protein.

## **5. Conclusions**

**CS/TPP molecule atom Amino acid atom Distance (Å)**

**Figure 6.** Docking of dengue virus E protein with CS ligand. The interaction takes place at an interface between the

N ring 1 O-Ser 274 3.43 O3 ring 1 OE2-Glu 49 2.90 O5 ring 1 NE2-Gln 271 3.08 O5 ring 1 OE1-Gln 271 2.66 O5 ring 1 O3-BOG 2.74 O1 TPP1 O-Ser274 3.03 O3 TPP1 O4-BOG 3.14 O1 TPP2 OD1-Asp 203 2.83 O3 TPP2 O4-BOG 3.30 O1 TPP3 O-Lys 202 2.19 O1 TPP3 OD1-Asp 203 3.18 O3 TPP3 NE2-Gln 200 3.43 O4 TPP O-Lys 202 2.51 O1 ring 2 N-Lys 202 2.89 O3 ring 2 ND2-Asn 124 2.89 O3 ring 2 OD1-Asn 124 2.38 O4 ring 2 OE2-Glu 126 2.49

two monomers.

76 Protein Engineering - Technology and Application

**Table 4.** Docking of CS/TPP/CS molecule with dengue virus E protein.

We have reviewed the key concepts and current experimental procedures, including the recent advances in protein flexibility, ligand sampling, and scoring function. In addition, challenges and possible future directions were addressed in this chapter. As an example of protein ligand study we analyzed the interaction between the dengue virus E protein and Polyvinylpyrroli‐ done and Chitosan biopolymers and we confirmed that PVP, CS, and CS/TPP/CS biopolymers can fulfill the function of adjuvant carriers in the potential development of a chimeric dengue vaccine against the 4 serotypes of dengue virus. Furthermore, the ring-shaped molecules have shown affinity to or preference for a place of vital importance in the virus's cycle of infection and replication, which placed us on the path to develop an inhibitor of the aforementioned conformational changes (see Figures 5-7). Their binding to the E protein is possible due to the great affinity they present to simulated molecules. However, further analysis of molecular simulation is required to determine the behavior of the protein without the presence of BOG ligand or in different environmental conditions in the presence of low pH.

## **Acknowledgements**

This work has been supported by Fomix-Veracruz (2009-128001) and CONACyT-Mexico (CB2008-105491, CMB).

## **Author details**

Alejandra Hernández-Santoyo1 , Aldo Yair Tenorio-Barajas2 , Victor Altuzar2 , Héctor Vivanco-Cid3 and Claudia Mendoza-Barrera2\*

\*Address all correspondence to<EMAIL_ADDRESS>
1 Instituto de Química, Universidad Nacional Autónoma de México, Mexico, D.F., Mexico

2 Laboratorio de Nanobiotecnología, Centro de Investigación en Micro y Nanotecnología, Universidad Veracruzana, Boca del Rio, Veracruz, Mexico

3 Instituto de Investigaciones Médico-Biológicas, Universidad Veracruzana, Boca del Río, Veracruz, Mexico

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**Author details**

Héctor Vivanco-Cid3

Veracruz, Mexico

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78 Protein Engineering - Technology and Application

\*Address all correspondence to<EMAIL_ADDRESS>
Universidad Veracruzana, Boca del Rio, Veracruz, Mexico

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80 Protein Engineering - Technology and Application

**Section 2**


**11. Conclusion**

The liver is the second most common affected organ in abdominal trauma and therefore has a prominent role in all the abdominal traumas. During the past decade, the management presented a significant evolution especially with the growth of interventional radiology. Procedures such as arteriography and arterial embolization helped to manage once difficult lesions with poor prognosis. Nevertheless, when it is possible, the nonoperative management should be preferred since it presents less morbidity.

Hepatic lesions classified as grade IV are a cause for anguish and anxiety for the surgeons, since they present a higher morbidity and mortality. The first concern in severe liver trauma should be the patient stabilization, which can be done through damage control surgery, which consists of executing the crucial and strategically ordered steps (shortened surgery, correction of physiological measurements in intensive care and proposed reoperation) to reduce operational time, correct a loss of death (medicated by acidosis, hypothermia, and coagulopathy), and improve the patient's long-term prognosis.

In the context of trauma, control damage surgery appears as an alternative for severely injured patients, who have multiple injuries to the abdominal viscera.

After clinical stabilization in an intensive care unit, the patient will be reoperated, and less severe injuries will be corrected, with the patient's gradual recovery after correcting the lethal triad.

In the same perspective, this chapter reviewed liver trauma centered on damage control surgery, providing the main content related to the topic, from its causes, trauma mechanism, classification, bibliographic review, therapeutic options, and current statistics to prognosis and the role of damage control surgery in this context. Thus, it is expected that at the end of the chapter, the reader will be able to organize the main topics related to liver trauma and consider making difficult decisions in practice in trauma hospital, always seeking the best prognosis for patients.


**6. Communication infrastructure of WAMS**

The communication system of WAMS is responsible for data delivery from data resources to the control center(s) and from control center(s) to the system actuators. Indeed, the communication network of WAMS is similar to the neural network of humans. As in case of failure or mal-functioning of neural network paralyzed may happen, failure of

Wide Area Measurement Systems 315

On the other hand, unguided media provides a means to transmit electromagnetic waves. However, this media does not guide the signals. The atmosphere and outer space are some examples of this case and usually referred to as wireless communication. Unlike guided media, in the case of unguided media, the signal strength provided by wireless antenna is more important than the media itself (Stallings, 1997). The next sub-sections review these

Power line carrier (PLC) has used transmission lines as a medium for communication. This type of transmission media has been one of the first reliable media utilized in power systems for critical communications (Marihart, 2001). This media is also the first guided media commonly utilized in power systems and is a part of power system infrastructure. As a result, failure in power system infrastructure such as line outage causes communication difficulty. PLC systems may be classified as two groups in common, narrow band and broad

Narrow band PLC usually has low data rates (up to 100kbps). It is used for automation and control applications or few voice channels (Hrasnica et al., 2004). However, due to the fact that the narrowband PLC works in low data rates, this system is very reliable and PLC

Unlike narrowband PLC, broadband PLC establishes a high data rate (beyond 2 Mbps) between two modems (Hrasnica et al., 2004). This kind of communication can be used for multi services such as automation, internet access and telephony at the same time. Broadband PLCs work in high data rates; therefore, distance between two modems is short and modems require more maintenance. This type of communication is not recommended

When power lines are used for broadband internet access, power line communication is known as broadband over power line (BPL). BPLs use spread spectrum techniques to deliver data rates previously inaccessible. But because of the fundamental physical constraints, successful data rates will be achieved much above several megabits per second

Optical fiber can be used as a medium for communication. Because of its flexibility, fiber optic can be bundled as a cable. As mentioned at the beginning of this section, signals are transmitted through the media by a type of waveform. In fiber cables, the signal is a light wave; either visible or infrared light. Essentially, two types of fiber optic cables including optical power ground wire (OPGW) and all-dielectric self supporting (ADSS) are used in

OPGW cable combines the function of grounding and communication. This kind of cable can be used in transmission or distribution lines. In transmission lines, OPGW is replaced

with shield wire and is suspended above the lines (Marihart, 2001).

modems can be installed far from each other (Shahraeini et al., 2010).

two groups of media.

**6.1.1 Power Line Carrier (PLC)**

band PLCs (Shahraeini et al., 2010).

for noisy power lines (Marihart, 2001).

power industries (Shahraeini et al., 2010).

(Nordell, 2008).

**6.1.2 Optical fiber**

**6.1 Guided media**

communication network may cause huge problems in system operation and control, especially in operation of WAMS applications. Consequently, especial attention should be paid to communication infrastructure, which is as important as electrical infrastructure itself. These two infrastructures (communication and electrical) have become increasingly interdependent so that in the case of failure for each of them, another one may also become out of service (Shahidehpour & Wang, 2003; Lukszo et al., 2010).

New communication systems are designed based on open system interconnection (OSI) layer model. In this architecture, upper layers relay data, assuming that the lower layers work perfectly. In fact, this model is an effective architecture for explanation, designing, implementation, standardization and use of communications networks. The OSI reference model consists of seven layers: physical, data link, network, transport, session, presentation, and application (Shahraeini et al., 2010).

In wide area measurement systems, data resources and WAMS applications normally work at the upper layers of network models. Fig. 4 shows the map between OSI layers and three major blocks of WAMS shown in Fig. 1 i.e. data resources, WAMS applications and communication system (Shahraeini et al., 2010).

Fig. 4. Layering in WAMS based on OSI reference model (Shahraeini et al., 2010).

The first layer of OSI model, referred to the physical layer, is a kind of medium that establishes the physical connection between transmitter and receiver. The characteristics of the communication systems will become seriously influenced by the characteristics of their media. Therefore, it can be concluded that the characteristics of the transmission media play an important role in communication infrastructure of WAMS. Some major characteristics of a medium are as follows: cost, bandwidth, propagation delay, security and reliability (Shahraeini et al., 2010).

Transmission media, as described below, can be classified as guided and unguided ones (Stallings, 1997). Guided media guides the waves through a solid medium. Twisted pair, coaxial cable, power transmission/distribution line and optical fiber are some examples of guided media. In the case of guided media, the media itself has the most important role in characterizing the limitations of transmission (Stallings, 1997).

On the other hand, unguided media provides a means to transmit electromagnetic waves. However, this media does not guide the signals. The atmosphere and outer space are some examples of this case and usually referred to as wireless communication. Unlike guided media, in the case of unguided media, the signal strength provided by wireless antenna is more important than the media itself (Stallings, 1997). The next sub-sections review these two groups of media.


**Author details**

*Pathogenic Bacteria*

from the LCV.

vesicles through different domains.

within eukaryotic hosts.

the LCV. This would indicate that somehow microdomains of PI(3)P within membranes are being recognized, sequestered, and sorted into vesicles for removal or that perhaps PI(3)P-positive vesicles do not stably interact with the LCV. How the LCV can distinguish the simultaneous shedding of PI(3)P-compartments with the fusion of PI(4)P-compartments has yet to be determined. We can speculate that *L. pneumophila* has evolved cohorts of effectors that can independently regulate the acceptance of PI(4)P-rich membrane or the egress of PI(3)P-rich membrane

PI(3)P is completely lost from the LCV membrane after 2 hours; however, it is unclear why there is a strong presence of PI(3)P-binding effectors that are on the LCV membrane after this time point (LpnE, SetA, LotA, RidL, LtpM, LtpD, RavD). At later stages of infection, an accumulation of stagnant PI(3)P-positive vesicles can be seen surrounding the LCV. It is possible that effectors anchored to the LCV could be interacting with these vesicles by recognizing multiple membrane compartments. Most LCV localization studies are assessed using light microscopy, in which the resolution may not be high enough to visualize smaller distinct structures around the LCV. Light microscopy showed RavD is present on the LCV membrane; however higher-resolution imaging techniques like structured illumination and transmission electron microscopy revealed RavD is also present on a subset of unidentified vesicles adjacent to the LCV. It is most likely these vesicles are PI(3) P-rich, as RavD does not localize to PI(4)P-positive compartments. Moreover, RavD does not rely on PI(3)P binding to anchor to the LCV, supporting that effectors may exhibit dual localization patterns and that RavD may interact with the LCV and

*L. pneumophila* has developed intricate strategies to facilitate intracellular growth by circumventing essential host cellular processes. The arsenal of effectors secreted by the type IV secretion system has evolved to target specific eukaryotic components such as proteins and lipids. Localization to the correct compartments within this host cell is imperative for protein function. A number of *Legionella* effectors rely on phosphoinositides to confer this directionality during infection. Not only are phosphoinositides needed to govern organelle identity, but they also dictate the path the phagosome embarks on once engulfed into the host cell. Thus, some effectors are ingeniously equipped to directly modify the lipid content on the phagosome membrane to avoid being routed toward degradation. Only a small percentage of effectors have been reported to interact with or modify phosphoinositides. Future studies that continue to expand on the repertoire of PIP-binding effectors will undoubtedly enhance our understanding of how intracellular pathogens survive within membrane-bound compartments

**50**

Colleen M. Pike, Rebecca R. Noll and M. Ramona Neunuebel\* Department of Biological Sciences, University of Delaware, Newark, DE, USA

\*Address all correspondence to<EMAIL_ADDRESS>
© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


**5. Oak wood chips vs. barrel**

*Chemistry and Biochemistry of Winemaking, Wine Stabilization and Aging*

quently the wood toasting reduces significantly its content.

**4. Sensory profile of wines refined with alternative products**

reduced in the oak-treated samples than in the control wines [75].

The sensory profile of wine also depends on the phase of the winemaking process at which the oak chips are added, as well as on the oak chip dose. A study on the red wine Bobal [76] showed that the wines with oak wood chips added during alcoholic fermentation had a similar sensory profile to control wines with olfactory attributes of red fruits, liquorice, pepper, leather, tobacco, and cassis, but with some woody notes. On the other hand, wines with oak chips added during malolactic fermentation showed higher intensities for the oak descriptors than wines with the oak chips added when the malolactic fermentation had finished. The intensity of woody attributes was higher when the chips were added in higher doses (6 g/L). Another experiment with white wines, Verdejo, showed the different effects of medium-toasted oak chips added during the alcoholic fermentation or aging stage [75]. With respect to the control (no chips were added), oak-treated wines showed a decrease of the descriptors fresh, green apple, fruity, tropical fruit, and citric and higher intensities for "ripe fruit" and "sweet" and for new attributes like coconut, sweet spices, woody (oak), and toasty in the oak chip-treated wines. Specifically, the wines with oak chips added during the alcoholic fermentation presented a lower content of volatile oak-extractable compounds, thus intensity of wood-related sensory attributes, but higher concentrations of fermentative volatile substances than the new wines aged with oak chip. The toasting status of oak chips (toasted or not toasted) seemed to be more relevant than the origin of oak in a study carried out on Chardonnay wine [77]. The differences highlighted among wines with added oak chips of different origin, did not influence the preference of the panel. On the other hand, the level of toasting was more important than the origin of the oak chips (German or French) [78] . Finally, the quantity of oak chips can have greater impact than the origin of the oak [79]. The sensory profile of the white wines *Listan blanco,* indeed*,* was mainly influenced by the amount of oak chips, less by the geographical origin of the oak, which was more relevant only in the case of comparing oak chips

Nevertheless, other research results have shown sensory differences attributed to the origin of the oak chips [31]. The wines (Romanian red wines Fetească neagră)

amino acids, fatty acids and minerals.

below.

to "corky," potato, green hazelnut, and dusty odor [74]. However this compound, synthesized by some proteobacteria, degrades at temperatures above 220° C, conse-

Other extractable compounds present in smaller quantities in oak wood are

Several research studies have highlighted the effects of the application of wood fragments on the sensory profile of wines. Some findings on the topic are reported

Generally, the oak-chip treatment favors the polymerization of anthocyanins and tannins, leading to a reduction of monomers in wines. In a research involving two Italian red wines, Aglianico and Montepulciano, after 1 year of aging, the content of polymeric phenols in both red wines was about 40% higher in oaktreated samples compared with the control wines. This effect, however, strongly depends on grape variety and on the polyphenolic profile of each cultivar. The same oak chip-treated samples showed attenuation of floral and fruity descriptors and the introduction of oak notes (woody, vanilla, spicy notes, and black pepper), accompanied by a higher astringency. After 1 year of aging, the flavor complexity decreased, especially the spicy notes and astringency, which were even more

**104**

and barrels.

#### **5.1 Sensory differences and consumer preferences**

As previously described, the quantity of oak chips, their dimensions and shape, their degree of toasting, contact time, and the stage of the winemaking process of their application can influence the sensory characteristics of the wine in numerous ways. Moreover, traditional refinement in wooden containers can lead to different results based on factors such as the time of contact, the use of new woods or used barrels, the period and frequency of an eventual *batonnage*, together with the possibility of using containers of different sizes. Therefore, the challenge to distinguish between wines obtained using barrel or chip-aged wines is particularly complicated due to the multiplicity of variables involved.

From a sensory point of view, wines refined with chips in steel containers are not clearly different from those long preserved in new barrels [81]. On the other hand, young wines made with chips are almost sensorially indistinguishable from those stored in new barrels for short periods (about 3 months); both are characterized by light *boisé* olfactory notes. Moreover, considering the effects of oak wood chip size, wood contact time (3, 6, and 9 months) and type of container (tank or used wood barrel) in wines analyzed after 6 months of bottling [82], some evident sensory differences were observed. The sensory effect of the addition of oak wood chips was more evident for the wines in tanks than for those in used barrels. Moreover, wines in used wood barrels with wood chips were not easily distinguishable from wines with no added wood chips. Considering wines treated with alternative products, the more appreciated were those aged in contact with cubes for 3 or 6 months. The authors suggested to use oak wood chips for short-aged wines and to reuse wood barrels still in good condition, pointing out that new wood barrels give wines of higher quality [82].

The sensory differences between wines aged in wood barrels or with oak wood fragments do not always reflect significant differences regarding consumer preference [83]. In a survey on consumer preferences, a large disparity of preferences was found among the participants that traditionally consume quality wines. A large proportion of respondents (55%) said that they would not buy wines produced using oak wood chips, whereas others declared that they would buy them only if, after tasting they had perceived the same quality as the wines in wood barrels. However, young people seemed to be less traditional and more open to buy a wine produced using oak wood fragments. Another online survey [84] involving Australian wine consumers reached similar conclusions**.**

Finally, the use of oak wood fragments could be an interesting alternative to barrels in emerging wine countries, such as Mexico [85] or Brazil [86], due to their lower costs. Nevertheless, before using oak wood in winemaking, local producers should investigate the preferences of their potential consumers.


**Appendix A. Summary of Results**

The construction system proposed for the basic and improved models used in the test exercise is described in detail on the following diagrams:

**Figure A1.** Construction details of the proposed base model.

**Figure A2.** Construction details of the improved model of the V1 climatic zone, Mexico City.

**Figure A3.** Construction details of the improved model of the V3 climatic zone, Toluca de Lerdo.

**Figure A4.** Construction details of the improved model of the W1 climatic zone, Merida.

**Figure A5.** Construction details of the improved model of the X1 climatic zone, Campeche.

**Figure A6.** Construction details of the improved model of the Y1 climatic zone, Culiacan.

**Figure A7.** Construction details of the improved model of the Z2 climatic zone, Mexicali.

**Figure A8.** Construction details of the improved model for the wood–cork system.

**Figure A9.** Construction details of the improved model for the adobe (mud and straw) and galvanized steel system.


**Author details**

Hidetoshi Ikeda1 \*, Natsuko Muranaka1 , Keisuke Sato1 and Eiji Nakano2 **References**

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\*Address all correspondence to<EMAIL_ADDRESS>
© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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