transporters belonging 
 to the neurotransmitter : sodium symporter 
 ( nss ) family are expressed in both eukaryotic and prokaryotic organisms . by facilitating the translocation of a wide range 
 of substrates across cellular membranes ,
the transporters play important 
 roles in physiological processes such as maintenance of cellular osmotic 
 pressure and neurotransmission .
the eukaryotic serotonin 
 ( 5-hydroxytryptamine , 5-ht ) transporter ( sert ) , together with its 
 close relatives the noradrenaline and dopamine transporters ( net and 
 dat , respectively ) , is one of the most widely studied nss transporters . 
 in the central nervous system ( cns )
, sert plays a pivotal role in 
 the termination of serotonergic neurotransmission by reducing the 
 amount of the neurotransmitter available for activation of post - synaptic 
 5-ht receptors .
multiple therapeutic ( e.g. , 
 antidepressants ) and illicit ( e.g. , cocaine ) drugs inhibit this reuptake , 
 hence enhancing the serotonergic neurotransmission .
the nss transporters are secondary transporters that 
 use pre - existing 
 ion gradients as an energy source for the translocation of their substrates . in the presence of sodium ,
the substrate binding site ( termed the 
 s1 site ) , located approximately midway through the membrane , is accessible 
 from the extracellular environment but not from the cytoplasm . upon substrate binding , large conformational 
 changes occur , leading to closure of the extracellular regions and 
 opening of the cytoplasmic parts of the transporters , resulting in 
 the release of substrate and sodium to the cell .
however , the fine details of this alternate - access transport 
 mechanism are not fully known .
in fact , studies have suggested both 
 1:1 and 2:1 substrate : transporter stoichiometry . in the latter scenario , it has been suggested that substrate binding 
 to an additional site ( termed s2 ) located in the extracellular vestibule 
 is a prerequisite for initiation of substrate translocation from the 
 centrally located s1 site .
homology modeling is an important technique in the study of 
 nss 
 transporters , because , until 2013 , only one member of this large family 
 has been solved by x - ray crystallography , namely , the prokaryotic aquifex aeolicus leucine transporter ( leut ) . in accordance 
 with the alternate - access transport mechanism , leut has been crystallized 
 in three major conformations , namely , in the outward - open ( s1 site 
 accessible from the extracellular region ) , outward - occluded ( s1 site inaccessible from 
 either side of the membrane ) , and inward - open ( s1 site accessible from the cytoplasm ) conformations .
co - crystallization with substrates 
 and noncompetitive inhibitors ( inhibitors occupying the s2 site ) stabilizes the transporter in the outward - occluded conformation .
in contrast , leut adopts an outward - open conformation when co - crystallized 
 with the competitive inhibitor trp .
a 
 major breakthrough in the field of nss transporters occurred in 2013 , 
 when a report on the first eukaryotic nss transporter , the drosophila melanogaster dat in complex with the antidepressant 
 nortriptyline , was published .
in addition , 
 12 crystal structures of leut with key binding pocket residues mutated 
 to hsert ( named leutbat ) and co - crystallized with four classes of 
 antidepressants were also released .
similar 
 to leut co - crystallized with trp , the crystal structures of dat and 
 leutbat show that the antidepressants are competitive inhibitors and 
 stabilize the transporters in an outward - open conformation .
new sert compounds may increase our knowledge of both transport 
 and inhibition mechanisms and could potentially lead to the development 
 of new therapeutic drugs .
one approach for identification of novel 
 compounds is virtual screening ( vs ) , i.e. , the rapid , in silico assessment 
 of large compound libraries , which may be performed using ligand- 
 and/or structure - based approaches .
ligand - based vs can be employed 
 using two - dimensional ( 2d ) methods such as fingerprint similarity 
 searching algorithms and three - dimensional ( 3d ) pharmacophore models .
ligand - based 3d pharmacophore models are generated 
 by superimposing a set of active molecules ( termed reference ligands ) , 
 determining ligand conformations that can be overlaid in such a way 
 that a maximum number of important chemical features geometrically 
 overlap . in comparison with ligand - based 
 vs , which does not rely on protein 3d information ,
structure - based 
 vs is performed by compound docking into either x - ray structures or 
 homology models or by using implicit methods such as structure- or 
 structure - docking - based pharmacophore models .
only a limited number of sert , net , and dat vs studies have 
 been 
 published . in the majority of studies ,
ligand - based approaches have been used , 
 although five structure - based vs studies were recently published . in these studies , docking 
 into the central s1 site , the s2 site , or a putative allosteric site 
 outside the proposed substrate translocation pathway in outward - occluded homology models was performed . in the 
 present study ,
a protocol combining ligand- and structure - based vs 
 approaches has been used to screen five commercial databases containing 
 3.24 million druglike compounds .
the vs protocol comprised 
 2d and 3d ligand - based screening of the databases and docking of compounds 
 into multiple conformations of the ligand binding pocket detected 
 in an outward - open sert homology model .
following vs , compounds were evaluated using in vitro screening 
 and full binding assays and the structures of active compounds were 
 used as queries in a subsequent hit - to - lead ( h2l ) screening of the 
 databases . in total ,
97 compounds belonging to 22 structural classes 
 ( chemotypes ) were evaluated using in vitro full binding assays .
more 
 than three of four compounds tested ( 74 of 97 ) were found to be active 
 ( ki  5000 nm ) .
the screening and building block collections 
 of five commercial databases were screened : asinex , chembridge , chemdiv , enamine , and life 
 chemicals . prior to screening ,
the databases 
 were filtered using the lipinski s  rule of 5  
 and veber filters to obtain druglike compounds .
the following compounds , belonging 
 to five classes of sert inhibitors , were used as reference ligands 
 during the 2d and 3d ligand - based steps of the vs protocol : ( s)-citalopram , desmethyl-(s)-citalopram , 
 didesmethyl-(s)-citalopram , ( s)-lu-08 - 052-o , 
 ( s)-lu-33 - 086-o , ( rs)-fluoxetine , 
 desmethyl-(rs)-fluoxetine , fluvoxamine , sertraline , 
 desmethyl - sertraline , ( rs)-venlafaxine , and o - desmethyl-(rs)-venlafaxine [ ssri / snri ( 5-ht - ne reuptake inhibitor ) 
 class ] , amitriptyline , clomipramine , desipramine , imipramine , protriptyline 
 and ( rs)-trimipramine [ tca class ] , cocaine , ab-248 , 
 ab-338 , -cft , cpt - d - tartrate , rti-31 , rti-32 , rti-55 ( -cit ) , 
 rti-83 , rti-112 , rti-121 , rti-142 , rti-311 and sn-1 [ 3-phenyltropane 
 class ] , ( rs)-mazindol , ( rs)-mazindane , 
 ( rs)-maz-10 , ( rs)-maz-85 , and ( rs)-maz-89 [ mazindol class ] , and adam , 4fadam , afm , dapa , 
 dasb , idam , madam , odam , and 403u76 [ radioligand class ] . the structures 
 and affinities of the reference ligands are shown in the table s1 in the supporting information .
individual queries were constructed for the reference ligand classes ; 
 however , because of the structural heterogeneity of the compounds 
 in the ssri / snri group , additional ( s)-citalopram , 
 sertraline , fluvoxamine , and fluoxetine / venlafaxine queries were also 
 built .
finally , a general query was prepared from the structures of 
 all 56 reference ligands .
hence , in the 2d and 3d steps of the vs 
 protocol , 10 reference ligand queries were used for screening . to maximize the screening 
 performance and
to obtain structurally diverse compounds , 2d pharmacophore - based 
 fingerprints and structural ( hashed chemical ) fingerprints were generated 
 based on the 56 reference ligands in the 10 queries .
two - dimensional ( 2d ) pharmacophore - based and structural 
 ( hashed chemical ) fingerprints were generated using the generatemd 
 command line tool of jchem , using default 
 settings .
the pharmacophore - based fingerprints were constructed from 
 the 2d molecular structures of the reference ligands by defining the 
 collection of all - atom pharmacophore feature pairs along with their 
 topological distances .
the chemical fingerprints encoded the topological 
 structure of the ligands into bit strings using atom type and bond 
 type information ( linear and cyclic patterns were detected ) .
the metrics - threshold pair was determined by three optimization 
 iterations for each query which were performed using test sets containing 
 compounds from a given group and randomly selected assumed inactive 
 compounds from the zinc database .
the 
 optimized metrics and threshold values used during the screening can 
 be found in table s2 in the supporting information .
the optimization of parametrized tanimoto or euclidean metrics 
 and subsequent 2d fingerprint - based screening were performed using 
 the screen command line tool of jchem .
first , for all 56 
 reference ligands , the strongest basic pka descriptor was calculated using the instant jchem calculator plugin .
next , the obtained range of this parameter ( pka = 311.5 ) was used in the filtering 
 of compounds that passed the 2d fingerprint - based screening step . 

compounds with unfavorable admet profiles were then removed from the 
 dataset using the schrdinger software module qikprop .
the following admet descriptor values were accepted : 
 number of functional groups ( rtvfg = 02 ) , predicted aqueous 
 solubility ( qplogs = 6.5 to 0.5 ) , model for gut - blood barrier 
 ( qppcaco > 500 ) , and predicted blood - brain coefficient ( qplogbb 
 = 
 3.0 to 1.2 ) .
ten ligand - based pharmacophore 
 models were obtained using the catalyst module of discovery studio 
 ( accelrys ) , employing the fast algorithm for generation of ligand stereoisomers and conformational 
 sampling .
the hiphop algorithm implemented 
 in catalyst was used for pharmacophore 
 mapping of the compounds that passed the filtering steps of the vs 
 protocol ( see above ) .
the compounds were allowed to deviate from the 
 pharmacophore models with maximum one feature except the positively 
 ionizable ( pi ) group .
following the 3d pharmacophore - based screening , 
 overlap analysis was performed using the instant jchem tool from chemaxon in order to remove repeated structures . the construction of the homology model 
 and the 47 binding pocket conformations has been described in detail 
 elsewhere .
the model was constructed 
 based on the leut crystal structure co - crystallized with the competitive 
 inhibitor l - tryptophan ( pdb i d 3f3a ) and a comprehensive alignment of nss transporters , using internal coordinate mechanics ( icm ) software .
the compounds were docked using a flexible 
 docking protocol that previously has been used for reference ligands .
the protocol consisted of ( 1 ) detection of the 
 ligand binding pocket using the icm pocketfinder , ( 2 ) biased - probability monte carlo ( bpmc ) sampling and minimization of the pocket side chains in 
 the presence of a repulsive density representing a generic ligand 
 to prevent collapse of the binding pocket , and ( 3 ) four - dimensional 
 ( 4d ) docking of fully flexible ligands 
 into multiple pocket conformations generated during step ( 2 ) . in the 
 present study
, the compounds were docked into 47 low - energy conformations 
 of the ligand binding pocket . the protein  ligand complexes 
 were scored using the virtual 
 ligand screening ( vls ) scoring function of icm .
compounds passed the structure - based screening step when 
 their scores were less than 10 and their protonated amine 
 moieties were located in the vicinity of d98 ( tm1 ) .
the selected compounds 
 were clustered using molprint2d fingerprints and tanimoto metrics 
 using the schrdinger software module canvas .
in addition to the flexible docking results and the clustering 
 of the compounds , the final selection of compounds for in vitro evaluation 
 was based on financial and laboratory limitations and stock availability .
rat neocortical tissue 
 was homogenized in 20 volumes of ice - cold 50 mm tris - hcl buffer , ph 
 7.7 containing 150 mm nacl and 5 mm kcl using an ultra turrax t25b 
 ( ika labortechnik , usa ) homogenizer ( 3 pulses , each of 10 s , 19  000 
 rpm ) .
the resulting supernatant 
 was decanted and pellet was resuspended in the same buffer and centrifuged 
 two more times in the same conditions .
two hundred forty microliters ( 240 l ) of the tissue suspension 
 ( 5 mg / ml ) , 30 l of 1 nm [ h]-citalopram , and 30 
 l of the analyzed compound or 1 m imipramine ( displacer ) 
 were incubated at 24 c for 1 h. during the screening experiments 
 the compounds were analyzed at a single concentration of 1.66  
 10 m. for compounds that exhibited at least 30% 
 [ h]-citalopram binding full competition experiments were 
 performed in concentration range from 10 to 10 m. after incubation , the reaction mix was filtered 
 immediately onto a gf / b glass fiber filter , using a 96-well filtermate 
 harvester system ( perkinelmer , usa ) .
the filter mate was dried in 
 a microwave oven for 10 min at a power setting of 40% ( 700 w total 
 power ) , and then it was placed in a sample bag and 10 ml of liquid 
 scintillation cocktail was melted onto the filter .
the radioactivity 
 on the filter was measured using a microbeta trilux 1450 scintillation 
 counter ( perkinelmer , usa ) .
the radioligand binding data were analyzed 
 using iterative curve fitting routines graphpad prism 3.0 ( graphpad 
 software ) , which used the built - in three parameter logistic model 
 to describe the ligand competition binding to radioligand - labeled 
 sites .
the log ic50 value was estimated from the data used 
 to obtain the ki by applying the cheng  prusoff 
 approximation .
results are expressed 
 as the means of at least two separate experiments . a second in silico screening 
 of the druglike subset of the five databases
was performed using core 
 structures of the compounds in chemotypes c01c13 ( see table 1 ) as queries .
the instant jchem substructure searching 
 algorithm and the symbolic query definition language module were employed .
following the substructure screening step , the 
 obtained compounds were screened using the basic property and admet 
 filters , 3d pharmacophore models , and flexible docking procedure , 
 as described above . to determine the novelty 
 of the identified compounds , the similarity between the compounds 
 with ki  5000 nm and known sert 
 compounds found in the mdl drug data report ( mddr , version 2011 ) and chembl_13 databases 
 was assessed using chemical hashed fingerprint and tanimoto metric 
 > 0.7 ( instant jchem ) .
in the first step of 
 the vs protocol , screening of the druglike subsets of the asinex , chembridge , chemdiv , enamine , and life 
 chemicals databases using 2d pharmacophore - based 
 fingerprints and structural ( hashed chemical ) fingerprints and 56 
 reference ligands resulted in a great decrease in the number of compounds : 
 nearly 98.5% of the druglike compounds did not pass this screening 
 step ( see table 2 ) .
experimental studies 
 have suggested that d98 in transmembrane helix 1 ( tm1 ) may anchor 
 substrates as well as inhibitors in sert .
a filter was thus employed to 
 select compounds with basic pka values 
 between 3 and 11.5 , i.e. , compounds containing at least one protonable 
 nitrogen moiety .
an admet filter was also used to remove compounds 
 that had an unfavorable number of functional groups , and/or unfavorable 
 aqueous solubility , blood - brain barrier , and/or gut - blood barrier 
 coefficients .
approximately 13  500 compounds passed the filtering 
 steps ( see table 2 ) .
the compounds were 
 then screened using ten 3d pharmacophore models constructed based 
 on the reference ligands .
all 3d pharmacophore models contained one 
 positively ionizable ( pi ) feature , one hydrophobic ( hyd ) feature , 
 and one or two aromatic ( ar ) features ( figure 1 , figure s1 in the supporting information ) .
the simplest pharmacophore models were the general hypothesis , 
 ssri and tca models , all of which contained one pi , hyd , and ar feature , 
 and the sertraline and mazindol models , which contained one additional 
 ar group ( see figure 1 , as well as figure s1 in the supporting information ) .
the 
 remaining pharmacophore models were more complex : the 3-phenyltropane , 
 ( s)-citalopram , fluoxetine / venlafaxine and fluvoxamine 
 models possessed an additional h - bond acceptor ( hba ) feature , whereas 
 the radioligand and fluvoxamine models included an additional h - bond 
 donor ( hbd ) feature and hyd region , respectively ( figure s1 in the supporting information ) . during mapping to 
 the pharmacophore models ,
the compounds were allowed to deviate from 
 the pharmacophore models with maximum one feature ( except the pi feature ) 
 in order to be selected .
approximately 2300 unique compounds passed 
 the 3d pharmacophore - based screening step of the vs protocol ( see 
 table 2 ) .
schematic of the 3d  general hypothesis  
 pharmacophore 
 model with desmethyl-(r)-fluoxetine mapped ( pi , positive 
 ionizable feature ; ar , aromatic feature ; hyd , hydrophobic feature ) . in the structure - based step of the 
 vs protocol ,
a homology model generated based on an outward - open leut 
 x - ray structure was used for docking 
 of the compounds that passed the 3d pharmacophore - based screening . 

in the outward - open conformation , the central s1 site of sert was 
 accessible from the extracellular environment and the putative inhibitor 
 binding region constituted both the central substrate binding site 
 ( including d98 ( tm1 ) ) and extracellular vestibular regions ( including 
 the s2 site ) of the transporter ( figure 2 ) . 

protein flexibility was included by docking the compounds into 47 
 low - energy conformations of the ligand binding pocket , using the 4d docking approach .
a total of 564 unique compounds had scores of less than 
 10 and a protonable nitrogen moiety in the vicinity of that 
 of d98 ( tm1 ) and , hence , passed the structure - based step ( table 2 ) .
docking results : ( a ) outward - open sert homology model 
 ( gray and 
 red ribbon representation ) with ligand binding region detected by 
 icm pocketfinder ( gray wire mesh ) and 
 ( b ) docking orientation of c466 - 0145 ( chemotype c09 ) . selected amino 
 acid side chains are shown ( xstick representation ) .
the localization of the s1 and s2 
 binding sites are also indicated in the figure . a total 
 of 202 compounds from 37 chemotypes
were purchased and screened in 
 vitro using a [ h]-citalopram competition binding assay 
 ( see table s3 in the supporting information ) .
twenty - three ( 23 ) of the compounds that exhibited at least 30% 
 inhibition of [ h]-citalopram binding at a concentration 
 of 1.66  10 m were further evaluated in 
 full binding assays ( see table s4 in the supporting 
 information ) .
in addition , less - potent compounds were also 
 selected to obtain structure  activity relationship ( sar ) data 
 and to increase the structural diversity of the evaluated compounds 
 ( table s4 in the supporting information ) . in total
, 46 compounds from 22 chemotypes were evaluated using 
 [ h]-citalopram competition full binding assays ( see table 2 ) .
the results of the full binding assays 
 revealed that 24 of the 46 compounds had ki  1000 nm ( see table s4 in the supporting 
 information ) .
the affinities of 13 compounds ranged between 
 1000 nm and 3100 nm , whereas the remaining 9 compounds may be regarded 
 as nonbinders ( ki > 10  000 nm ) 
 ( table s4 in the supporting information ) . thirteen ( 13 ) chemotypes ( c01c13 ) contained compounds 
 with ki  1000 nm , 3 ( c14c16 ) 
 had compounds with ki between 2300 and 
 2700 nm , while 5 ( c17c22 ) only contained compounds regarded 
 as nonbinders ( ki > 20  000 nm ) 
 ( table s4 in the supporting information ) . to detect analogues of 
 the compounds identified using the vs protocol , an in silico h2l screening 
 of the druglike subsets of the five databases was performed ( recall 
 table 2 ) . the substructure search , using the 
 core structures of the compounds in chemotypes c01c13 ( table 1 ) as queries , resulted in the detection of 8700 
 analogues ( see table 2 ) .
application of the 
 basic property and admet filters reduced the number of compounds to 
 5000 , while 3855 unique compounds were selected during the 
 3d pharmacophore - based screening step and 504 unique compounds passed 
 the flexible docking step ( table 2 ) . in total , 
 198 compounds were selected for in vitro [ h]-citalopram 
 screening during h2l ( table 2 ) . based on the 
 results of the in vitro screening
, 33 compounds that exhibited 30% 
 inhibition of [ h]-citalopram binding at a concentration 
 of 1.66  10 m and 18 less - potent analogues 
 were selected for evaluation in full binding studies ( see table s4 in the supporting information ) . using the h2l approach ,
active analogues were identified in 11 of 
 the 13 chemotypes ( see table s4 in the supporting 
 information ) . in total , 22 of the h2l compounds had ki values 1000 nm and compounds with 
 higher affinity than their 
compounds were identified 
 in five chemotypes ( chemotypes c01 , c03 , c04 , c08 and c10 ; see table s4 in the supporting information ) .
the 
 structures of the highest - affinity binder from each chemotype identified 
 using the vs and h2l approaches are shown in figure 3 .
structures of selected reference ligands and highest affinity ligand 
 in chemotypes c01c16 , identified using the vs / h2l protocol .
in addition to the number and affinity 
 of compounds identified using vs , the compound novelty is an important 
 vs performance indicator .
the structural similarity between the compounds 
 identified in the present study and known sert binders found in the 
 chembl and mddr databases was hence determined .
the results of the analysis indicated 
 that compounds in 9 of the 16 chemotypes were structurally nonrelated 
 to known sert ligands while the compounds in the remaining seven chemotypes 
 showed varying degrees of similarities ( tanimoto coefficients values 
 ranging from tc = 0.50 to tc = 0.96 ; see table 1 ) .
in the present study , a multistep vs protocol 
 ( see table 2 ) has been used to screen for novel , 
 structurally 
 diverse sert compounds in commercially available databases . to accomplish 
 this objective , ( i ) five databases containing 3.24 million 
 druglike compounds
were screened , ( ii ) multiple compounds from several 
 structural classes of sert inhibitors were used as reference compounds 
 in the ligand - based steps , ( iii ) docking into 47 low - energy conformations 
 of the binding pocket detected in the outward - open sert homology model 
 was performed in the structure - based step , and ( iv ) a h2l screening 
 of the databases using the structures of the compounds identified 
 using vs as queries was performed . in vitro evaluation of the compounds 
 was followed by novelty analysis of the identified hits .
a combination 
 of ligand- and structure - based vs approaches was 
 used to screen five commercial databases , which were chosen for screening 
 because they contain numerous , as well as a high percentage of , exclusive 
 compounds .
the ligand - based approaches 
 have the advantages of not heavily relying on macromolecular target 
 information . in ligand - based vs ,
3d pharmacophore models are commonly 
 used ; however , screening of large compound databases using pharmacophore 
 models can be time - consuming . by reducing 
 the number of compounds in the databases prior to pharmacophore - based 
 screening by applying a series of filters , as in the present study
another challenge in using ligand - based pharmacophore models is 
 that these implicit models normally only cover a limited chemical 
 space . in the present study ,
this shortcoming 
 was addressed by constructing ten pharmacophore models based on structurally 
 diverse groups of reference ligands and allowing partial mapping of 
 compounds to the pharmacophore models . by docking compounds 
 into their 3d protein targets , steric and 
 distance - sensitive interactions between the compounds and the protein 
 that are not so easily explained using pharmacophore models ,
because of the lack of a sert 
 x - ray structure , a homology model constructed 
 using the prokaryotic leut as a template was used for docking in the 
 present study . despite the low overall sequence identity between leut 
 and the eukaryotic nss transporters , leut 
 is considered to be a good homology modeling template .
an important consideration during homology modeling of nss transporters , 
 however , is which leut conformation to use as template , i.e. , whether 
 to use an outward - open , outward - occluded , or inward - open conformation . 

because studies have indicated that most sert ligands stabilize outward - facing 
 conformations of the transporter , the two former conformations may be good choices 
 of templates for models used for docking .
leut has been co - crystallized 
 in the outward - occluded conformation with tca and ssri antidepressants , 
 which , in leut , are noncompetitive low - affinity inhibitors . in the present study , however , leut co - crystallized with the competitive 
 inhibitor l - tryptophan ( trp ) , which stabilizes leut in an 
 outward - open conformation , was used as 
 a template .
our previous results from docking of the reference ligands 
 into outward - open and outward - occluded sert models suggested that 
 the former conformation best accommodated these compounds . in the outward - open conformation , the central 
 substrate binding site of sert ,
containing d98 ( tm1 ) , which was indicated 
 to be important for the binding of 5-ht and inhibitors in sert , was accessible from the extracellular environment and , hence , the 
 putative inhibitor binding region constituted both the central substrate 
 binding site and extracellular vestibular regions of the transporter 
 ( figure 2 ) .
furthermore , during preparation 
 of the current manuscript , crystal structures of d. 
 melanogaster dat and leutbat were published . in support of our findings , these crystal structures show that the 
 antidepressants indeed are competitive inhibitors of the human transporters 
 and stabilize the transporters in outward - open conformation .
in addition to the lack of protein x - ray structures , other 
 limitations 
 of structure - based vs may be a lack of the inclusion of protein flexibility 
 during docking and the difficulties in scoring the protein 
the degrees of freedom needed to keep proteins fully flexible 
 during docking makes such simulations computationally unfeasible and 
 most standard docking programs use a semiflexible approach , keeping 
 the ligands fully flexible but the proteins rigid .
one method to include 
 a degree of protein flexibility is docking into multiple receptor 
 conformations , which is known to improve the results of vs. in the present study , the compounds were docked into 47 low - energy 
 conformations of the ligand binding pocket that had been generated 
 prior to docking by bpmc side - chain sampling .
docking into multiple conformations of the binding pocket was also 
 a way of obtaining structurally diverse compounds , since studies have 
 indicated that sert binders most likely stabilize different outward - facing 
 transporter conformations .
furthermore , the bpmc side - chain sampling resulted in an increased 
 distance between the aromatic amino acids of the extracellular gate 
 ( y176 ( tm3 ) and f335 ( tm6 ) ) , hence resulting in a widening of the 
 ligand binding pocket .
this was important 
 for the binding of the sert binders which are larger in size than 
 the co - crystallized leut inhibitor trp . in structure - based vs , scoring is used to separate potential 
 binders 
 from nonbinders .
empirical scoring functions such as the icm vls function consist of weighted energy terms that describe 
 known ligand binding properties ( e.g. , hydrogen bonding , ionic , lipophilic 
 and aromatic interactions and the conformational entropy loss of the 
 ligand ) .
the limitations of the current scoring functions may , to 
 some degree , be addressed by evaluating the docking results using 
 additional parameters . in the present study , the ability of the highly 
 scored compounds to form an ionic interaction with d98 ( tm1 ) was used 
 to evaluate the top - scored ligands .
analysis of the docking orientations 
 of the compounds identified as sert binders showed that they , when 
 interacting with d98 ( tm1 ) , occupied the central substrate binding 
 and lower vestibular regions ( figure 2 ) .
halogenated 
 moieties of the compounds were furthermore often located in the vestibular 
 region .
namely , 
 l99 ( tm1 ) , g100 ( tm1 ) , w103 ( tm1 ) , r104 ( tm1 ) , y176 and i179 ( tm3 ) , 
 and f335 ( tm6)have been suggested to form a halogen binding 
 pocket ( hbp ) in sert .
the results 
 of the in vitro full binding assays showed that more 
 than 80% of the compounds evaluated were active ( c01c16 ; ki  5000 nm ) ( see table s4 in the supporting information ) . in order to find 
 analogues of the highest - affinity binders ,
a h2l screening of the 
 five databases was undertaken using the core structures of chemotypes 
 c01c13 as queries ( recall table 1 ) . 

the h2l screening resulted in the identification of compounds that 
 would not have been detected using the vs approach alone : comparison 
 of the unique compounds that passed the structure - based steps of the 
 vs and h2l protocols revealed that only 134 compounds had been selected 
 in both approaches ( results not shown ) .
the results of the in 
 vitro full binding evaluation showed that 
 46 of the 97 compounds selected using the vs and h2l approaches had ki values of 1000 nm ( see table s4 in the supporting information ) .
the 
 highest affinity obtained was 1.5 nm ( t6125232 , chemotype 
 c04 ) ( see table s4 in the supporting information , as well as figure 3 ) , which is in the range 
 of the affinities of marketed antidepressants .
the clustering of the identified binders furthermore showed that 
 they were structurally diverse , belonging to 16 different structural 
 classes ( figure 3 ) , and the theoretical novelty 
 analysis suggested that compounds in multiple of the chemotypes were 
 structurally unrelated to known sert binders in the mddr and chembl databases . 

these databases , which contain information on compounds derived primarily 
 from the patent and primary scientific 
 literature , respectively , are , however , 
 not fully comprehensive .
the novelty analysis did not reveal that t6275452 in chemotype c04 is a known sert binder , showing that the compound is not annotated as 
 such in the databases .
hence , although the results indicate that multiple 
 compounds are novel sert binders , the results of the novelty analysis 
 must be more rigorously evaluated .
in 
 the present study , virtual screening ( vs ) of 3.24 million 
 druglike compounds has resulted in the identification of 74 active 
 sert binders belonging to 16 structural classes , of which 46 compounds 
 in 13 chemotypes had ki values of 1000 
 nm . by combining vs and hit - to - lead ( h2l ) approaches and selecting 
 compounds that show varying degrees of [ h]-citalopram 
 inhibition in the in vitro screening assays
sar data may be useful for 
 elucidating the inhibition mechanism of sert and may also be used 
 for the development of compounds as antidepressants .
 the 
 serotonin ( 5-hydroxytryptamine , 5-ht ) transporter ( sert ) plays 
 an essential role in the termination of serotonergic neurotransmission 
 by removing 5-ht from the synaptic cleft into the presynaptic neuron . 
 
 it is also of pharmacological importance being targeted by antidepressants 
 and psychostimulant drugs . here , five commercial databases containing 
 approximately 3.24 million drug - like compounds have been screened 
 using a combination of two - dimensional ( 2d ) fingerprint - based and 
 three - dimensional ( 3d ) pharmacophore - based screening and flexible 
 docking into multiple conformations of the binding pocket detected 
 in an outward - open sert homology model . 
 following virtual screening 
 ( vs ) , selected compounds were evaluated using in vitro screening and 
 full binding assays and an in silico hit - to - lead ( h2l ) screening was 
 performed to obtain analogues of the identified compounds . using this 
 multistep vs / h2l approach , 74 active compounds , 46 of which had ki values of 1000 nm , belonging to 16 
 structural classes , 
 have been identified , and multiple compounds share 
 no structural resemblance with known sert binders . 
Introduction
Methods
Results
Discussion
Conclusion