this is especially true in the case of protein kinases , which are important therapeutic targets ( 1 ) . while targeting the atp - binding site of protein kinases was initially thought to be useless due to a lack of specificity , the first crystal structure of a protein kinase in 1991 revealed unexpected structural features leading to brighter hopes for the development of specific inhibitors ( 2 ) . since then , a number of protein kinase structures have been solved , including many inhibitor - bound proteins . a number of protein kinase inhibitors are now in the clinic and several others in clinical trials ( 1 ) . despite this progress , the gap between the number of reported sequences and experimental structures continues to increase ( 3 ) , and we are far from determining the structure of all the 518 protein kinases identified in the human genome . furthermore , a larger gap exists in the case of proteins complexed with their known ligands . at the same time , recurrent substructures are observed among the known ligands of a given protein family ( or superfamily ) as observed in the case of protein kinases ( 4 ) . structure comparisons have been widely used to identify protein similarities and to derive functional or structural information ( 3 ) . automatic procedures are now available to provide three - dimensional models of good quality when the sequence identity is above 30% ( 5 ) . on the contrary , the modelling of protein  ligand complexes remains a more difficult and tedious task ( 5 ) . indeed , template searches generally focus on sequence similarities rather than on the presence or not of a ligand bound to the template . in the case of well - characterized protein families , one template may provide the best protein scaffold while a more distantly related template may provide a valid ligand ( e.g. atp for protein kinases ) . in parallel , virtual screening ( vs ) while the use of vs had often been restricted to the structures of crystallized proteins , it was recently shown that some three - dimensional models can be accurate enough to perform vs ( 7,8 ) . however , vs is still a highly cpu - intensive task and it needs an appropriate active site structure ( e.g. corresponding to an active conformation ) . this conformation might differ from one class of compounds to another due to the ligand - induced fit phenomenon ( 8) . on the one hand , current comparative modelling can provide theoretical models of protein structures with significant accuracy . on the other hand , vs has been developed to search rather large chemical libraries and to identify potential ligands . however , because of a lack of appropriate tools ( e.g. for local evaluation of protein conformations ) , the interplay between macromolecular modelling and ligand docking is not yet efficiently and automatically performed . we present here a new server , kindock , which has been developed to speed up these processes . it combines structural comparisons , immediate transfer of known ligands from the template structure into the target structure , visualization of the deduced protein  ligand complexes and evaluation of protein  ligand interactions . using this server , the quality of a modelled structure ( especially the active site or the ligand binding sites ) as well as the conformation of a protein ( active / open conformation , inactive / closed conformation ) can be rapidly and precisely evaluated . it is also possible to identify protein templates in complex with a given ligand in order to restrain the active site modelling and take into account potential ligand induced - fit . generic ligands or putative inhibitors can also be searched in our focused library prior to in vitro assays . because protein kinases are important therapeutic targets , this server has been dedicated to the study of this class of enzymes ( 8,9 ) . several examples described herein , illustrate the various uses of kindock in the new field of comparative docking . first , a set of protein kinase structures solved in complex with a ligand ( e.g. atp , inhibitors ) was manually gathered from the protein data bank ( pdb ) ( ) ; ( 10 ) and organized in a hierarchical database . a multiple - sequence alignment of these kinases based on the hanks alignment ( 11 ) was manually refined using the alignment editor vito ( 12 ) . this profile can now be used to search automatically the pdb for protein kinase complexes to update our library . the bound protein kinase ligands were extracted and rewritten in mol2 format using the program prodrg ( ) ; ( 13 ) . the kindock server needs , as an input data , either a coordinate file in pdb format or the four - letter pdb code of the target structure . the sequence of the protein kinase structure submitted to the server is aligned to the kinase profile using the program suite hmmer ( ) . then , the target structure is superposed on each of the protein kinase complexes of our library according to the alignment . the superposition is based on a subset of c carbons defining the common binding site . the latter is composed of any aligned amino acid that possesses an atom at less than 6  from the ligand in the experimental complex . the binding affinities of the new theoretical complexes are evaluated using the program score ( 14 ) . the affinity score ( pk ) predicted by score ( 14 ) is log(ic50 ) so the higher the score , the stronger the predicted affinity . beside the predicted affinity scores , the sequence identity and the root mean square deviation ( rmsd ) of the active site superposition are displayed . ranking the complexes according to these values or according to the ligand or structure pdb codes is also possible . the resulting complexes can be visualized directly using a java applet , jmol ( , see figure 1 ) . the coordinates of the new complexes can be downloaded in pdb format for further analysis as well as the re - oriented ligands in mol2 format for further analysis and virtual screening . kindock allows a rapid and straightforward building of complexes using a three - dimensional structure ( which may be experimental or theoretical ) of a given protein kinase and a specialized library of protein kinase complexes . ligand complexes representing currently 52 different protein kinases and 196 different ligands despite some redundancies for several compounds , such as atp and its analogs and staurosporine . automatic updates will be set up to follow the increasing number of complex structures solved . kindock performs the four following tasks : ( i ) the alignment of the sequence of the submitted protein kinase onto the family profile , ( ii ) the superposition of its three - dimensional structure on the protein kinase  ligands structures ( according to the alignment ) , ( iii ) the extraction of the ligand from each complex and its transfer into the active site of the submitted structure and then ( iv ) the evaluation of the protein  ligand interactions . herein , we called this approach  comparative docking by analogy with comparative modelling of protein structure . currently , one comparative docking on the protein kinase family lasts a few minutes . the orientation of a given ligand has been shown to be conserved among various protein kinases , especially for ligands containing at least three cycles ( 4 ) . thanks to protein  protein superposition , kindock brings each ligand into the target active site with an orientation similar to the one found in the original ligand - kinase crystal structure . the deduced binding mode was expected to be more correct than one deduced by classical docking ( 15 ) . visual surveys suggested that the ligand orientation in the complexes deduced by kindock closely resembles the experimental one . figure 2 illustrates the case of staurosporine docked into pdb1stc from the 15 other complexes of a protein kinase with this generic inhibitor . thanks to the redundancy of the complex library , an extensive evaluation of the quality of the molecule orientation predicted by kindock was performed . for any compound found in at least two structures , the rmsd between the molecule posed by kindock and the one in the pdb structure was computed . most poses deduced by kindock are within 2  from the experimental one ( heavy atom rmsd ; figure 3 ) meaning that they are correct according to the standard threshold used in virtual screening . furthermore , this appeared to be true whatever the sequence identity shared by the proteins ( down to 20% ) . the java viewer , jmol , allows a rapid visualization of the protein  ligand contacts and a rapid survey of strong steric clashes and favourable interactions ( salt bridge , ring stacking ,  ; see figure 1 ) . alternatively , kindock may also reveal an inaccurate modelling of the active site or a conformational rearrangement preventing the ligand binding . as the set of complexes includes atp - bound structures ( and also atp analog complexes ) and other known binders ( e.g. staurosporine , a generic inhibitor of protein kinases ) , the structure of the atp binding site of a protein kinase can be probed . kindock was used to place atp into the crystal structures of pkb , either in its active conformation ( pdb1o6l ) or in its inactive conformation ( pdb1gzn ) . ligand interactions were evaluated using the scoring function score ( see table 1 ) . the best predicted affinity of the active form of pkb for atp was nanomolar ( pk = 9.5 ) while the pk was negative for the inactive form . the scores for the inactive form are all negative ( mean pk  9.1 ) , suggesting that atp can not fit into this conformation . in some protein kinases , the activation loop can adopt the so - called  dfg - out conformation and this structural rearrangement prevents the binding of most ligands , especially atp and atp - competitive inhibitors . the server kindock can rapidly highlight such rearrangements and their implications in the ligand entrance . this is exemplified with the three distinct conformations of the protein kinase c - kit . the latter has been co - crystallized with atp , pp1 an atp - competitive inhibitor ( 16 ) and sti-571 ( also named imatinib mesylate or gleevec ) a ligand inducing a  dfg - out conformation . the corresponding structures have been submitted to kindock and the affinity for the three different ligands was predicted ( see results for human c - kit in table 2 and at ) . the predicted affinity of the active form of this protein ( pdb1pkg ) for atp and pp1 is nanomolar while that for sti-571 is negative . the opposite situation is observed for the structure of c - kit co - crystallized with sti-571 ( pdb1t46 ) which adopts a  dfg - out conformation . a third structure of the c - kit kinase which corresponds to an emtpy and inactive form does not bind to any of these ligands according to kindock . this suggests that no unique structure can represent a protein kinase and that several conformations have to be determined or modelled . poor scoring for a given type of ligand can also reveal incorrectly modelled side - chains or loops . this might allow the selection of optimal models prior to extensive vs in order to improve its hit rate ( 8) . in order to evaluate the capabilities of kindock to select the best model among a set of models for a given protein kinase , we use the example of the well - characterized cdk4 which has been , so far , recalcitrant to crystallization ( 17 ) . a comparative docking was performed on the protein kinase cdk4 whose three - dimensional structure was modelled using various templates and the modelling server @tome ( ) in a fully automatic manner ( see results at ) . kindock was used to discriminate three distinct models built from two closely related templates : cdk2 and cdk6 . cdk6 and cdk2 are roughly 60 and 40% identical to cdk4 . however , only cdk2 crystallized in an active form ( in presence of atp and cyclin a ; pdb1qmz ) while both cdk2 and cdk6 can be observed in an inactive form ( pdb1hcl and pdb1blx , respectively ) . models deduced from inactive forms failed to accommodate most ligands while the model built from the active cdk2 structure nicely accommodates atp . to evaluate further the quality of these three models , we took advantage of the knowledge of two crystal structures of a mutated cdk2 with two known cdk4-specific inhibitors ( 17 ) . the best model also provides us predicted affinities for these inhibitors ( mean pk of 5.2 , with the best model versus 1.3 and 1.6 with those from the two inactive forms ) in agreement with the experimental ones ( sub - micromolar range ) . the evaluation , by kindock , of the crystal structures of the mutated cdk2 with these two inhibitors ( pdb1gii and pdb1gij ) provided similar values ( predicted pk for their own ligand of 5.6 and 6.3 , respectively ) . this result suggested that kindock can correctly evaluate the active site conformation of molecular models while providing relatively accurate poses ( see above ) as well as relatively good estimates of protein  ligand interactions . as illustrated above , kindock allows a rapid screening of a small library of chemical compounds . despite the partial loss of chemical diversity , the proposed approach focuses on privileged pharmacophores . the second advantage comes from the accuracy of the poses ( see above ) that allows for a better evaluation of protein  ligand interactions . alternatively , the specificity of a given inhibitor for a set of protein kinases can be evaluated by submitting each structure to kindock . the question has also been recently addressed by experimental means for several protein kinase inhibitors ( 19 ) . in the case of the pyrido[2,3-d]pyrimidine derivatives , affinity assays on the molecule pp58 , closely related to the ligands pd166326 and pd173955 in our library ( figure 4 ) , allowed us to evaluate the performance of kindock . a good correlation between observed and predicted affinities was observed for a set of six distinct protein kinases ( see table 3 ) . this result is in agreement with a specific amino - acid substitution ( methionine versus threonine at the gatekeeper position ) that distinguishes the two protein kinases subsets , with micromolar ( pk score 6 ) versus nanomolar ( pk score 9 ) affinities for the pp58 molecule . similar correlations were observed with another set of protein kinases and two imidazol derivatives ( data not shown ) . on the contrary , in the case of hymenialdisine , a correlation could not be found using kindock , and no sequence variation in the active site was detected . additional analyses will be necessary to explain the distinct binding affinities for this very rigid inhibitor . similarly , some other parameters influencing binding energies can not be evaluated directly by our approach ( e.g. ligand flexibility , water displacement , metal binding ,  ) . this approach may also rapidly reveal potential chemical substitutions to better fit the studied active site . the results presented herein , are promising , but more accurate affinity predictions could be obtained from the combined use of several evaluation programs . as shown in the previous examples ( described above ) , kindock can discriminate active conformations from inactive ones , and the server works equally well for theoretical models and experimental structures . using the server @tome dedicated to molecular modelling , different conformations of a protein kinase can be automatically built and evaluated at a global and structural level . then , the atp - binding site of the various models can be evaluated at a local and functional level using kindock . this approach might provide distinct conformations according to the template used ( e.g. using related structures crystallized in  dfg - in or  dfg - out conformations ) . an alternative means for creating such variability in the active site structure was recently proposed and shown to improve vs results ( 20 ) . in that work the diversity in the active site conformations is obtained by molecular dynamic simulations . in contrast , in the present work we use @tome to model several conformations of the same active site in order to take into account the protein flexibility and a potential ligand - induced fit . we believe that our approach is much faster and will predict conformations more likely to be accessible , as they are already observed in related structures . the server kindock will be connected with the modelling server @tome in order to provide a complete and fully automatic pipeline for molecular modelling and focused screening based on protein structure similarity . kindock allows a rapid and straightforward building of complexes using a three - dimensional structure ( which may be experimental or theoretical ) of a given protein kinase and a specialized library of protein kinase complexes . ligand complexes representing currently 52 different protein kinases and 196 different ligands despite some redundancies for several compounds , such as atp and its analogs and staurosporine . automatic updates will be set up to follow the increasing number of complex structures solved . kindock performs the four following tasks : ( i ) the alignment of the sequence of the submitted protein kinase onto the family profile , ( ii ) the superposition of its three - dimensional structure on the protein kinase  ligands structures ( according to the alignment ) , ( iii ) the extraction of the ligand from each complex and its transfer into the active site of the submitted structure and then ( iv ) the evaluation of the protein  ligand interactions . herein , we called this approach  comparative docking by analogy with comparative modelling of protein structure . currently , one comparative docking on the protein kinase family lasts a few minutes . the orientation of a given ligand has been shown to be conserved among various protein kinases , especially for ligands containing at least three cycles ( 4 ) . thanks to protein  protein superposition , kindock brings each ligand into the target active site with an orientation similar to the one found in the original ligand - kinase crystal structure . the deduced binding mode was expected to be more correct than one deduced by classical docking ( 15 ) . visual surveys suggested that the ligand orientation in the complexes deduced by kindock closely resembles the experimental one . figure 2 illustrates the case of staurosporine docked into pdb1stc from the 15 other complexes of a protein kinase with this generic inhibitor . thanks to the redundancy of the complex library , an extensive evaluation of the quality of the molecule orientation predicted by kindock was performed . for any compound found in at least two structures , the rmsd between the molecule posed by kindock and the one in the pdb structure was computed . most poses deduced by kindock are within 2  from the experimental one ( heavy atom rmsd ; figure 3 ) meaning that they are correct according to the standard threshold used in virtual screening . furthermore , this appeared to be true whatever the sequence identity shared by the proteins ( down to 20% ) . the java viewer , jmol , allows a rapid visualization of the protein  ligand contacts and a rapid survey of strong steric clashes and favourable interactions ( salt bridge , ring stacking ,  ; see figure 1 ) . alternatively , kindock may also reveal an inaccurate modelling of the active site or a conformational rearrangement preventing the ligand binding . as the set of complexes includes atp - bound structures ( and also atp analog complexes ) and other known binders ( e.g. staurosporine , a generic inhibitor of protein kinases ) , the structure of the atp binding site of a protein kinase can be probed . kindock was used to place atp into the crystal structures of pkb , either in its active conformation ( pdb1o6l ) or in its inactive conformation ( pdb1gzn ) . ligand interactions were evaluated using the scoring function score ( see table 1 ) . the best predicted affinity of the active form of pkb for atp was nanomolar ( pk = 9.5 ) while the pk was negative for the inactive form . the scores for the inactive form are all negative ( mean pk  9.1 ) , suggesting that atp can not fit into this conformation . in some protein kinases , the activation loop can adopt the so - called  dfg - out conformation and this structural rearrangement prevents the binding of most ligands , especially atp and atp - competitive inhibitors . the server kindock can rapidly highlight such rearrangements and their implications in the ligand entrance . this is exemplified with the three distinct conformations of the protein kinase c - kit . the latter has been co - crystallized with atp , pp1 an atp - competitive inhibitor ( 16 ) and sti-571 ( also named imatinib mesylate or gleevec ) a ligand inducing a  dfg - out conformation . the corresponding structures have been submitted to kindock and the affinity for the three different ligands was predicted ( see results for human c - kit in table 2 and at ) . the predicted affinity of the active form of this protein ( pdb1pkg ) for atp and pp1 is nanomolar while that for sti-571 is negative . the opposite situation is observed for the structure of c - kit co - crystallized with sti-571 ( pdb1t46 ) which adopts a  dfg - out conformation . a third structure of the c - kit kinase which corresponds to an emtpy and inactive form does not bind to any of these ligands according to kindock . this suggests that no unique structure can represent a protein kinase and that several conformations have to be determined or modelled . poor scoring for a given type of ligand can also reveal incorrectly modelled side - chains or loops . this might allow the selection of optimal models prior to extensive vs in order to improve its hit rate ( 8) . in order to evaluate the capabilities of kindock to select the best model among a set of models for a given protein kinase , we use the example of the well - characterized cdk4 which has been , so far , recalcitrant to crystallization ( 17 ) . a comparative docking was performed on the protein kinase cdk4 whose three - dimensional structure was modelled using various templates and the modelling server @tome ( ) in a fully automatic manner ( see results at ) . kindock was used to discriminate three distinct models built from two closely related templates : cdk2 and cdk6 . however , only cdk2 crystallized in an active form ( in presence of atp and cyclin a ; pdb1qmz ) while both cdk2 and cdk6 can be observed in an inactive form ( pdb1hcl and pdb1blx , respectively ) . models deduced from inactive forms failed to accommodate most ligands while the model built from the active cdk2 structure nicely accommodates atp . to evaluate further the quality of these three models , we took advantage of the knowledge of two crystal structures of a mutated cdk2 with two known cdk4-specific inhibitors ( 17 ) . the best model also provides us predicted affinities for these inhibitors ( mean pk of 5.2 , with the best model versus 1.3 and 1.6 with those from the two inactive forms ) in agreement with the experimental ones ( sub - micromolar range ) . the evaluation , by kindock , of the crystal structures of the mutated cdk2 with these two inhibitors ( pdb1gii and pdb1gij ) provided similar values ( predicted pk for their own ligand of 5.6 and 6.3 , respectively ) . this result suggested that kindock can correctly evaluate the active site conformation of molecular models while providing relatively accurate poses ( see above ) as well as relatively good estimates of protein  ligand interactions . as illustrated above , kindock allows a rapid screening of a small library of chemical compounds . despite the partial loss of chemical diversity , the proposed approach focuses on privileged pharmacophores . the second advantage comes from the accuracy of the poses ( see above ) that allows for a better evaluation of protein  ligand interactions . alternatively , the specificity of a given inhibitor for a set of protein kinases can be evaluated by submitting each structure to kindock . the question has also been recently addressed by experimental means for several protein kinase inhibitors ( 19 ) . in the case of the pyrido[2,3-d]pyrimidine derivatives , affinity assays on the molecule pp58 , closely related to the ligands pd166326 and pd173955 in our library ( figure 4 ) , allowed us to evaluate the performance of kindock . a good correlation between observed and predicted affinities was observed for a set of six distinct protein kinases ( see table 3 ) . this result is in agreement with a specific amino - acid substitution ( methionine versus threonine at the gatekeeper position ) that distinguishes the two protein kinases subsets , with micromolar ( pk score 6 ) versus nanomolar ( pk score 9 ) affinities for the pp58 molecule . similar correlations were observed with another set of protein kinases and two imidazol derivatives ( data not shown ) . on the contrary , in the case of hymenialdisine , a correlation could not be found using kindock , and no sequence variation in the active site was detected . additional analyses will be necessary to explain the distinct binding affinities for this very rigid inhibitor . similarly , some other parameters influencing binding energies can not be evaluated directly by our approach ( e.g. ligand flexibility , water displacement , metal binding ,  ) . this approach may also rapidly reveal potential chemical substitutions to better fit the studied active site . the results presented herein , are promising , but more accurate affinity predictions could be obtained from the combined use of several evaluation programs . as shown in the previous examples ( described above ) , kindock can discriminate active conformations from inactive ones , and the server works equally well for theoretical models and experimental structures . using the server @tome dedicated to molecular modelling , different conformations of a protein kinase can be automatically built and evaluated at a global and structural level . then , the atp - binding site of the various models can be evaluated at a local and functional level using kindock . this approach might provide distinct conformations according to the template used ( e.g. using related structures crystallized in  dfg - in or  dfg - out conformations ) . an alternative means for creating such variability in the active site structure was recently proposed and shown to improve vs results ( 20 ) . in that work the diversity in the active site conformations is obtained by molecular dynamic simulations . in contrast , in the present work we use @tome to model several conformations of the same active site in order to take into account the protein flexibility and a potential ligand - induced fit . we believe that our approach is much faster and will predict conformations more likely to be accessible , as they are already observed in related structures . the server kindock will be connected with the modelling server @tome in order to provide a complete and fully automatic pipeline for molecular modelling and focused screening based on protein structure similarity . the results were sorted by ligand name to highlight the scores and a binding mode obtained for staurosporine . all stauroporines  protein kinase complexes present in the pdb ( 16 in the current database ; listed in figure 1 ) were used to transfer the common ligand into the camp - dependent protein kinase ( pdb1stc ) . the active site of camp - dependent protein kinase is drawn as a black ribbon . the experimental orientation of staurosporine ( pdb1stc ) is in black wireframe while the staurosporines docked by similarity are in grey wireframe . rmsd between the ligand poses as deduced by kindock and the ligand in the template pdb structure . discrimination of active / inactive forms by kindock the predicted affinity scores are given as log(ic50 ) for the best ranked ligand as well as the best atp analog . discrimination of distinct conformations of the c - kit protein kinase by kindock the predicted affinity score of the best atp analog , sti-571 and pp1 are shown . the affinity score deduced from experimental assays of c - kit with sti-571 and pp1 are respectively 7.0 and 7.2 ( 16 ) . discrimination of protein kinases with micromolar or nanomolar affinities for pyrido[2,3-d]pyrimidine derivatives by kindock the affinities of the pp58 ( a pyrido[2,3-d]pyrimidine derivative related to pd166326 and pd173955 ) for each of the different protein kinases are deduced from experimental data ( 19 ) . the mean predicted affinity score for the pd166326 and pd173955 ligands is shown in the < pd > column .
kindock is a new web server for the analysis of atp - binding sites of protein kinases . 
 this characterization is based on the docking of ligands already co - crystallized with other protein kinases . a structural library of protein kinase 
 ligand complexes has been extracted from the protein data bank ( pdb ) . 
 this library can provide both potential ligands and their putative binding orientation for a given protein kinase . 
 after protein  protein structural superposition , the ligands are transferred from the template complexes to the target protein kinase . 
 the resulting complexes are evaluated using the program score to compute a theoretical affinity . 
 they can be dynamically visualized to allow a rapid mapping of important steric clashes and potential substitutions relevant for specificity and affinity . 
 these characteristics allow a quick characterization of protein kinase active sites including conformation changes potentially required to accommodate particular ligands . 
 additionally , promising pharmacophores can be identified in the focussed library . 
 these features will help to rationalize or optimize virtual screening ( vs ) on larger chemical compound libraries . 
 the server and its documentation are freely available at .