{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T04:53:49Z","timestamp":1771822429761,"version":"3.50.1"},"reference-count":70,"publisher":"Springer Science and Business Media LLC","issue":"1","funder":[{"name":"Ministry of Science and Technology of the People's Republic of China (CN)","award":["2016YFA0502302"],"award-info":[{"award-number":["2016YFA0502302"]}]},{"name":"National Natural Science Foundation of China (CN)","award":["81430083"],"award-info":[{"award-number":["81430083"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["21472227"],"award-info":[{"award-number":["21472227"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["21673276"],"award-info":[{"award-number":["21673276"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National Natural Science Foundation of China (CN)","award":["21102168"],"award-info":[{"award-number":["21102168"]}]},{"DOI":"10.13039\/501100002367","name":"Chinese Academy of Sciences","doi-asserted-by":"crossref","award":["XDB20000000"],"award-info":[{"award-number":["XDB20000000"]}],"id":[{"id":"10.13039\/501100002367","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100002367","name":"Chinese Academy of Sciences","doi-asserted-by":"crossref","award":["XDB20020200"],"award-info":[{"award-number":["XDB20020200"]}],"id":[{"id":"10.13039\/501100002367","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Science and Technology Development Foundation of Macao SAR","award":["055\/2013\/A2"],"award-info":[{"award-number":["055\/2013\/A2"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2017,12]]},"DOI":"10.1186\/s12859-017-1750-5","type":"journal-article","created":{"date-parts":[[2017,7,18]],"date-time":"2017-07-18T14:20:33Z","timestamp":1500387633000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Enhance the performance of current scoring functions with the aid of 3D protein-ligand interaction fingerprints"],"prefix":"10.1186","volume":"18","author":[{"given":"Jie","family":"Liu","sequence":"first","affiliation":[]},{"given":"Minyi","family":"Su","sequence":"additional","affiliation":[]},{"given":"Zhihai","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Jie","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yan","family":"Li","sequence":"additional","affiliation":[]},{"given":"Renxiao","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,7,18]]},"reference":[{"key":"1750_CR1","first-page":"1","volume-title":"Reviews in computational chemistry","author":"I Muegge","year":"2001","unstructured":"Muegge I, Rarey M. Small molecule docking and scoring. In: Lipkowitz KB, Boyd DB, editors. Reviews in computational chemistry. New York: Wiley-VCH; 2001. p. 1\u201360."},{"key":"1750_CR2","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1146\/annurev.biophys.32.110601.142532","volume":"32","author":"N Brooijmans","year":"2003","unstructured":"Brooijmans N, Kuntz ID. Molecular recognition and docking algorithms. Annu Rev Biophys Biomol Struct. 2003;32:335\u201373.","journal-title":"Annu Rev Biophys Biomol Struct"},{"key":"1750_CR3","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1038\/nrd1549","volume":"3","author":"DB Kitchen","year":"2004","unstructured":"Kitchen DB, Decornez H, Furr JR, Bajorath J. Docking and scoring in virtual screening for drug discovery: methods and applications. Nat Rev Drug Discov. 2004;3:935\u201349.","journal-title":"Nat Rev Drug Discov"},{"key":"1750_CR4","doi-asserted-by":"crossref","first-page":"10150","DOI":"10.3390\/molecules190710150","volume":"19","author":"SZ Grinter","year":"2014","unstructured":"Grinter SZ, Zou XQ. Challenges applications and recent advances of protein\u2013ligand docking in structure-based drug design. Molecules. 2014;19:10150\u201376.","journal-title":"Molecules"},{"key":"1750_CR5","first-page":"41","volume-title":"Reviews in computational chemistry","author":"HJ B\u00f6hm","year":"2002","unstructured":"B\u00f6hm HJ, Stahl M. The use of scoring functions in drug discovery applications. In: Lipkowitz KB, Boyd DB, editors. Reviews in computational chemistry. New York: Wiley-VCH; 2002. p. 41\u201388."},{"key":"1750_CR6","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.ddtec.2004.08.004","volume":"1","author":"T Schulz-Gasch","year":"2004","unstructured":"Schulz-Gasch T, Stahl M. Scoring functions for protein\u2013ligand interactions: a critical perspective. Drug Discov Today Tech. 2004;1:231\u20139.","journal-title":"Drug Discov Today Tech"},{"key":"1750_CR7","doi-asserted-by":"crossref","first-page":"5851","DOI":"10.1021\/jm060999m","volume":"49","author":"AR Leach","year":"2006","unstructured":"Leach AR, Shoichet BK, Peishoff CE. Prediction of protein\u2013ligand interactions docking and scoring: successes and gaps. J Med Chem. 2006;49:5851\u20135.","journal-title":"J Med Chem"},{"key":"1750_CR8","first-page":"308","volume":"10","author":"R Rajamani","year":"2007","unstructured":"Rajamani R, Good AC. Ranking poses in structure-based lead discovery and optimization: current trends in scoring function development. Curr Opin Drug Discov Develop. 2007;10:308\u201315.","journal-title":"Curr Opin Drug Discov Develop"},{"key":"1750_CR9","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1021\/ci500731a","volume":"55","author":"J Liu","year":"2015","unstructured":"Liu J, Wang R. Classification of current scoring functions. J Chem Inf Model. 2015;55:475\u201382.","journal-title":"J Chem Inf Model"},{"key":"1750_CR10","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/S1359-6446(97)01163-X","volume":"3","author":"WP Walters","year":"1998","unstructured":"Walters WP, Stahl MT, Murcko MA. Virtual screening \u2013 an overview. Drug Discov Today. 1998;3:160\u201378.","journal-title":"Drug Discov Today"},{"key":"1750_CR11","doi-asserted-by":"crossref","first-page":"862","DOI":"10.1038\/nature03197","volume":"432","author":"BK Shoichet","year":"2004","unstructured":"Shoichet BK. Virtual screening of chemical libraries. Nature. 2004;432:862\u20135.","journal-title":"Nature"},{"key":"1750_CR12","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1016\/j.cbpa.2007.08.033","volume":"11","author":"C McInnes","year":"2007","unstructured":"McInnes C. Virtual screening strategies in drug discovery. Curr Opin Chem Biol. 2007;11:494\u2013502.","journal-title":"Curr Opin Chem Biol"},{"key":"1750_CR13","doi-asserted-by":"crossref","unstructured":"Plewczynski D, \u0141a\u017aniewski M, Augustyniak R, Ginalski K. Can we trust docking results? Evaluation of seven commonly used programs on pdbbind database. J Comput Chem. 2011;32:742\u201355.","DOI":"10.1002\/jcc.21643"},{"key":"1750_CR14","doi-asserted-by":"crossref","first-page":"12964","DOI":"10.1039\/C6CP01555G","volume":"18","author":"Z Wang","year":"2016","unstructured":"Wang Z, Sun H, Yao X, Li D, Xu L, Li Y, Tian S, Hou T. Comprehensive evaluation of ten docking programs on a diverse set of protein\u2013ligand complexes: the prediction accuracy of sampling power and scoring power. Phys Chem Chem Phys. 2016;18:12964\u201375.","journal-title":"Phys Chem Chem Phys"},{"key":"1750_CR15","doi-asserted-by":"crossref","first-page":"1079","DOI":"10.1021\/ci9000053","volume":"49","author":"T Cheng","year":"2009","unstructured":"Cheng T, Li X, Li Y, Liu Z, Wang R. Comparative assessment of scoring functions on a diverse test set. J Chem Inf Model. 2009;49:1079\u201393.","journal-title":"J Chem Inf Model"},{"key":"1750_CR16","doi-asserted-by":"crossref","first-page":"1700","DOI":"10.1021\/ci500080q","volume":"54","author":"Y Li","year":"2014","unstructured":"Li Y, Liu Z, Li J, Han L, Liu J, Zhao Z, Wang R. Comparative assessment of scoring functions on an updated benchmark: 1.Compilation of the test set. J Chem Inf Model. 2014;54:1700\u201316.","journal-title":"J Chem Inf Model"},{"key":"1750_CR17","doi-asserted-by":"crossref","unstructured":"Li Y, Han L, Liu Z, Wang R. Comparative assessment of scoring functions on an updated benchmark: 2. Evaluation methods and general results. J Chem Inf Model. 2014;54:1717\u201336.","DOI":"10.1021\/ci500081m"},{"key":"1750_CR18","doi-asserted-by":"crossref","unstructured":"Smith RD, Dunbar JB Jr, Ung PM, Esposito EX, Yang C, Wang S, Carlson HA. CSAR benchmark exercise of 2010: combined evaluation across all submitted scoring functions. J Chem Inf Model. 2011;51:2115\u201331.","DOI":"10.1021\/ci200269q"},{"key":"1750_CR19","doi-asserted-by":"crossref","unstructured":"Damm-Ganamet KL, Smith RD, Dunbar JB Jr, Stuckey JA, Carlson HA. CSAR benchmark exercise 2011\u20132012: evaluation of results from docking and relative ranking of blinded congeneric series. J Chem Inf Model. 2013;53:1853\u201370.","DOI":"10.1021\/ci400025f"},{"key":"1750_CR20","doi-asserted-by":"crossref","unstructured":"Dunbar JB Jr, Smith RD, Damm-Ganamet KL, Ahmed A, Esposito EX, Delproposto J, Chinnaswamy K, Kang Y, Kubish G, Gestwicki JE, Stuckey JA, Carlson HA. CSAR data set release 2012: ligands affinities complexes and docking decoys. J Chem Inf Model. 2013;53:1842\u201352.","DOI":"10.1021\/ci4000486"},{"key":"1750_CR21","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1146\/annurev.biophys.36.040306.132550","volume":"36","author":"MK Gilson","year":"2007","unstructured":"Gilson MK, Zhou HX. Calculation of protein\u2013ligand binding affinities. Annu Rev Biophys Biomol Struct. 2007;36:21\u201342.","journal-title":"Annu Rev Biophys Biomol Struct"},{"key":"1750_CR22","doi-asserted-by":"crossref","first-page":"4092","DOI":"10.1021\/cr800551w","volume":"109","author":"HX Zhou","year":"2009","unstructured":"Zhou HX, Gilson MK. Theory of free energy and entropy in noncovalent binding. Chem Rev. 2009;109:4092\u2013107.","journal-title":"Chem Rev"},{"key":"1750_CR23","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1016\/j.drudis.2009.03.013","volume":"14","author":"MHJ Seifert","year":"2009","unstructured":"Seifert MHJ. Targeted scoring functions for virtual screening. Drug Discov Today. 2009;14:562\u20139.","journal-title":"Drug Discov Today"},{"key":"1750_CR24","doi-asserted-by":"crossref","first-page":"1868","DOI":"10.1021\/ci700134p","volume":"47","author":"P Pfeffer","year":"2007","unstructured":"Pfeffer P, Gohlke H. DrugScoreRNA\u2013knowledge-based scoring function to predict rna\u2013ligand interactions. J Chem Inf Model. 2007;47:1868\u201376.","journal-title":"J Chem Inf Model"},{"key":"1750_CR25","doi-asserted-by":"crossref","first-page":"1291","DOI":"10.1021\/ci050036g","volume":"45","author":"I Antes","year":"2005","unstructured":"Antes I, Merkwirth C, Lengauer T. POEM: parameter optimization using ensemble methods: application to target specific scoring functions. J Chem Inf Model. 2005;45:1291\u2013302.","journal-title":"J Chem Inf Model"},{"key":"1750_CR26","doi-asserted-by":"crossref","first-page":"602","DOI":"10.1021\/ci700345n","volume":"48","author":"MHJ Seifert","year":"2008","unstructured":"Seifert MHJ. Optimizing the signal-to-noise ratio of scoring functions for protein\u2013ligand docking. J Chem Inf Model. 2008;48:602\u201312.","journal-title":"J Chem Inf Model"},{"key":"1750_CR27","doi-asserted-by":"crossref","first-page":"1378","DOI":"10.1021\/ci100182c","volume":"50","author":"M Xue","year":"2010","unstructured":"Xue M, Zheng M, Xiong B, Li Y, Jiang H, Shen J. Knowledge-based scoring functions in drug design 1 developing a target-specific method for kinase\u2013ligand interactions. J Chem Inf Model. 2010;50:1378\u201386.","journal-title":"J Chem Inf Model"},{"key":"1750_CR28","doi-asserted-by":"crossref","first-page":"6296","DOI":"10.1021\/jm050436v","volume":"48","author":"HFG Velec","year":"2005","unstructured":"Velec HFG, Gohlke H, Klebe G. DrugScoreCSD\u2013knowledge-based scoring function derived from small molecule crystal data with superior recognition rate of near-native ligand poses and better affinity prediction. J Med Chem. 2005;48:6296\u2013303.","journal-title":"J Med Chem"},{"key":"1750_CR29","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1021\/ci700239t","volume":"48","author":"R Teramoto","year":"2008","unstructured":"Teramoto R, Fukunishi H. Consensus scoring with feature selection for structure-based virtual screening. J Chem Inf Model. 2008;48:288\u201395.","journal-title":"J Chem Inf Model"},{"key":"1750_CR30","doi-asserted-by":"crossref","first-page":"1858","DOI":"10.1021\/ci700116z","volume":"47","author":"R Teramoto","year":"2007","unstructured":"Teramoto R, Fukunishi H. Supervised scoring models with docked ligand conformations for structure-based virtual screening. J Chem Inf Model. 2007;47:1858\u201367.","journal-title":"J Chem Inf Model"},{"key":"1750_CR31","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1016\/j.jmgm.2010.09.006","volume":"29","author":"R Teramoto","year":"2010","unstructured":"Teramoto R, Kashima H. Prediction of protein\u2013ligand binding affinities using multiple instance learning. J Mol Graph Model. 2010;29:492\u20137.","journal-title":"J Mol Graph Model"},{"key":"1750_CR32","doi-asserted-by":"crossref","first-page":"3169","DOI":"10.1021\/ci2002268","volume":"51","author":"S Avram","year":"2011","unstructured":"Avram S, Pacureanu LM, Seclaman E, Bora A, Kurunczi L. PLS-DA - docking optimized combined energetic terms (PLSDA-DOCET) protocol: a brief evaluation. J Chem Inf Model. 2011;51:3169\u201379.","journal-title":"J Chem Inf Model"},{"key":"1750_CR33","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1021\/ci100436p","volume":"51","author":"M McGann","year":"2011","unstructured":"McGann M. FRED pose prediction and virtual screening accuracy. J Chem Inf Model. 2011;51:578\u201396.","journal-title":"J Chem Inf Model"},{"key":"1750_CR34","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1186\/1471-2105-11-193","volume":"11","author":"T Cheng","year":"2010","unstructured":"Cheng T, Liu Z, Wang R. A knowledge-guided strategy for improving the accuracy of scoring functions in binding affinity prediction. BMC Bioinf. 2010;11:193\u2013208.","journal-title":"BMC Bioinf"},{"key":"1750_CR35","first-page":"356","volume":"11","author":"SC Brewerton","year":"2008","unstructured":"Brewerton SC. The use of protein-ligand interaction fingerprints in docking. Curr Opin Drug Dis Develop. 2008;11:356\u201364.","journal-title":"Curr Opin Drug Dis Develop"},{"key":"1750_CR36","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1021\/jm030331x","volume":"47","author":"Z Deng","year":"2004","unstructured":"Deng Z, Chuaqui C, Singh J. Structural interaction fingerprint (SIFT): a novel method for analyzing three-dimensional protein-ligand binding interactions. J Med Chem. 2004;47:337\u201344.","journal-title":"J Med Chem"},{"key":"1750_CR37","doi-asserted-by":"crossref","first-page":"1942","DOI":"10.1021\/ci049870g","volume":"44","author":"MD Kelly","year":"2004","unstructured":"Kelly MD, Mancera RL. Expanded interaction fingerprint method for analyzing ligand binding modes in docking and structure-based drug design. J Chem Inf Comput Sci. 2004;44:1942\u201351.","journal-title":"J Chem Inf Comput Sci"},{"key":"1750_CR38","doi-asserted-by":"crossref","first-page":"686","DOI":"10.1021\/ci050420d","volume":"46","author":"CP Mpamhanga","year":"2006","unstructured":"Mpamhanga CP, Chen B, McLay IM, Willett P. Knowledge-based interaction fingerprint scoring: a simple method for improving the effectiveness of fast scoring functions. J Chem Inf Model. 2006;46:686\u201398.","journal-title":"J Chem Inf Model"},{"key":"1750_CR39","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1021\/ci600342e","volume":"47","author":"G Marcou","year":"2007","unstructured":"Marcou G, Rognan D. Optimizing fragment and scaffold docking by use of molecular interaction fingerprints. J Chem Inf Model. 2007;47:195\u2013207.","journal-title":"J Chem Inf Model"},{"key":"1750_CR40","doi-asserted-by":"crossref","first-page":"3222","DOI":"10.1021\/jm8001058","volume":"51","author":"J Venhorst","year":"2008","unstructured":"Venhorst J, Nunez S, Terpstra JW, Kruse CG. Assessment of scaffold hopping efficiency by use of molecular interaction fingerprints. J Med Chem. 2008;51:3222\u20139.","journal-title":"J Med Chem"},{"key":"1750_CR41","doi-asserted-by":"crossref","first-page":"2308","DOI":"10.1021\/ci800322y","volume":"48","author":"L Tan","year":"2008","unstructured":"Tan L, Lounkine E, Bajorath J. Similarity searching using fingerprints of molecular fragments involved in protein\u2212ligand interactions. J Chem Inf Model. 2008;48:2308\u201312.","journal-title":"J Chem Inf Model"},{"key":"1750_CR42","doi-asserted-by":"crossref","first-page":"1245","DOI":"10.1021\/ci900043r","volume":"49","author":"VI Perez-Nueno","year":"2009","unstructured":"Perez-Nueno VI, Rabal O, Borrell JI, Teixido J. APIF: a new interaction fingerprint based on atom pairs and its application to virtual screening. J Chem Inf Model. 2009;49:1245\u201360.","journal-title":"J Chem Inf Model"},{"key":"1750_CR43","doi-asserted-by":"crossref","unstructured":"Nandigam RK, Kim S, Singh J, Chuaqui S. Position specific interaction dependent scoring technique for virtual screening based on weighted protein\u2212ligand interaction fingerprint profiles. J Chem Inf Model. 2009;49:1185\u201392.","DOI":"10.1021\/ci800466n"},{"key":"1750_CR44","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1021\/ci900382e","volume":"50","author":"T Sato","year":"2010","unstructured":"Sato T, Honma T, Yokoyama S. Combining machine learning and pharmacophore-based interaction fingerprint for in silico screening. J Chem Inf Model. 2010;50:170\u201385.","journal-title":"J Chem Inf Model"},{"key":"1750_CR45","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1021\/ci600253e","volume":"47","author":"M Baroni","year":"2007","unstructured":"Baroni M, Cruciani G, Sciabola S, Perruccio F, Mason JS. A common reference framework for analyzing\/comparing proteins and ligands fingerprints for ligands and proteins (FLAP): theory and application. J Chem Inf Model. 2007;47:279\u201394.","journal-title":"J Chem Inf Model"},{"key":"1750_CR46","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1021\/ci300566n","volume":"53","author":"J Desaphy","year":"2013","unstructured":"Desaphy J, Raimbaud E, Ducrot P, Rognan D. Encoding protein\u2013ligand interaction patterns in fingerprints and graphs. J Chem Inf Model. 2013;53:623\u201337.","journal-title":"J Chem Inf Model"},{"key":"1750_CR47","doi-asserted-by":"crossref","first-page":"2555","DOI":"10.1021\/ci500319f","volume":"54","author":"C Da","year":"2014","unstructured":"Da C, Kireev D. Structural protein\u2013ligand interaction fingerprints (SPLIF) for structure-based virtual screening: method and benchmark study. J Chem Inf Model. 2014;54:2555\u201361.","journal-title":"J Chem Inf Model"},{"key":"1750_CR48","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.chembiol.2007.03.011","volume":"14","author":"L Peltason","year":"2007","unstructured":"Peltason L, Bajorath J. Molecular similarity analysis uncovers heterogeneous structure-activity relationships and variable activity landscapes. Chem Biol. 2007;14:489\u201397.","journal-title":"Chem Biol"},{"key":"1750_CR49","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1021\/acs.jcim.5b00745","volume":"56","author":"A Anighoro","year":"2016","unstructured":"Anighoro A, Bajorath J. Three-dimensional similarity in molecular docking: prioritizing ligand poses on the basis of experimental binding modes. J Chem Inf Model. 2016;56:580\u20137.","journal-title":"J Chem Inf Model"},{"key":"1750_CR50","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1007\/s10822-016-9918-z","volume":"30","author":"A Anighoro","year":"2016","unstructured":"Anighoro A, Bajorath J. Binding mode similarity measures for ranking of docking poses: a case study on the adenosine A2A receptor. J Comput Aided Mol Des. 2016;30:447\u201356.","journal-title":"J Comput Aided Mol Des"},{"key":"1750_CR51","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1021\/ci300377f","volume":"53","author":"K Kasahara","year":"2013","unstructured":"Kasahara K, Shirota M, Kinoshita K. Comprehensive classification and diversity assessment of atomic contacts in protein\u2013small ligand interactions. J Chem Inf Model. 2013;53:241\u20138.","journal-title":"J Chem Inf Model"},{"key":"1750_CR52","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1093\/bioinformatics\/btu626","volume":"31","author":"Z Liu","year":"2015","unstructured":"Liu Z, Li Y, Han L, Li J, Liu J, Zhao Z, Nie W, Liu Y, Wang R. PDB-wide collection of binding data: current status of the pdbbind database. Bioinformatics. 2015;31:405\u201312.","journal-title":"Bioinformatics"},{"key":"1750_CR53","first-page":"21","volume-title":"Uncertainty in artificial intelligence, proceedings","author":"H Attias","year":"1999","unstructured":"Attias H. Inferring parameters and structure of latent variable models by variational bayes. In: Laskey KB, Prade H, editors. Uncertainty in artificial intelligence, proceedings. Sweden: Fifteenth conference on Uncertainty in artificial intelligence; 1999. p. 21\u201330."},{"key":"1750_CR54","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1023\/A:1027371810547","volume":"17","author":"VV Rantanen","year":"2003","unstructured":"Rantanen VV, Gyllenberg M, Koski T, Johnson MS. A Bayesian molecular interaction library. J Comput Aided Mol Des. 2003;17:435\u201361.","journal-title":"J Comput Aided Mol Des"},{"key":"1750_CR55","doi-asserted-by":"crossref","unstructured":"De Maesschalck R, Jouan-Rimbaud D, Massart DL. The Mahalanobis distance. Chemometr Intell Lab Syst. 2000;50:1\u201318.","DOI":"10.1016\/S0169-7439(99)00047-7"},{"key":"1750_CR56","doi-asserted-by":"crossref","first-page":"575","DOI":"10.1145\/362342.362367","volume":"16","author":"C Bron","year":"1973","unstructured":"Bron C, Kerbosch J. Algorithm 457: finding all cliques of an undirected graph. Commun ACM. 1973;16:575\u20137.","journal-title":"Commun ACM"},{"key":"1750_CR57","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1021\/ci9800211","volume":"38","author":"P Willett","year":"1998","unstructured":"Willett P, Barnard JM, Downs GM. Chemical similarity searching. J Chem Inf Comput Sci. 1998;38:983\u201396.","journal-title":"J Chem Inf Comput Sci"},{"key":"1750_CR58","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1093\/bioinformatics\/btq003","volume":"26","author":"Y Huang","year":"2010","unstructured":"Huang Y, Niu B, Gao Y, Fu L, Li W. CD-HIT suite: a web server for clustering and comparing biological sequences. Bioinformatics. 2010;26:680\u20132.","journal-title":"Bioinformatics"},{"key":"1750_CR59","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1021\/ci800298z","volume":"49","author":"O Korb","year":"2009","unstructured":"Korb O, St\u00fctzle T, Exner TE. Empirical scoring functions for advanced protein\u2013ligand docking with PLANTS. J Chem Inf Model. 2009;49:84\u201396.","journal-title":"J Chem Inf Model"},{"key":"1750_CR60","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1002\/prot.20588","volume":"61","author":"WTM Mooij","year":"2005","unstructured":"Mooij WTM, Verdonk ML. General and targeted statistical potentials for protein\u2013ligand interactions. Proteins: Struct Funct Bioinf. 2005;61:272\u201387.","journal-title":"Proteins: Struct Funct Bioinf"},{"key":"1750_CR61","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1006\/jmbi.1996.0897","volume":"267","author":"G Jones","year":"1997","unstructured":"Jones G, Willett P, Glen RC, Leach AR, Taylor R. Development and validation of a genetic algorithm for flexible docking. J Mol Biol. 1997;267:727\u201348.","journal-title":"J Mol Biol"},{"key":"1750_CR62","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1023\/A:1016357811882","volume":"16","author":"R Wang","year":"2002","unstructured":"Wang R, Lai L, Wang S. Further development and validation of empirical scoring functions for structure-based binding affinity prediction. J Comput Aided Mol Des. 2002;16:11\u201326.","journal-title":"J Comput Aided Mol Des"},{"key":"1750_CR63","doi-asserted-by":"crossref","first-page":"D1045","DOI":"10.1093\/nar\/gkv1072","volume":"44","author":"MK Gilson","year":"2016","unstructured":"Gilson MK, Liu T, Baitaluk M, Nicola G, Hwang L, Chong J. BindingDB in 2015: a public database for medicinal chemistry computational chemistry and systems pharmacology. Nucleic Acids Res. 2016;44:D1045\u201353.","journal-title":"Nucleic Acids Res"},{"key":"1750_CR64","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1002\/anie.200905597","volume":"49","author":"HJ Wu","year":"2010","unstructured":"Wu HJ, Ho CW, Ko TP, Popat SD, Lin CH, Wang AH. Structural basis of \u03b1-fucosidase inhibition by iminocyclitols with Ki values in the micro- to picomolar range. Angew Chem Int Ed Engl. 2010;49:337\u201340.","journal-title":"Angew Chem Int Ed Engl"},{"key":"1750_CR65","doi-asserted-by":"crossref","first-page":"36208","DOI":"10.1074\/jbc.M112.400705","volume":"287","author":"M Coincon","year":"2012","unstructured":"Coincon M, Wang W, Syqusch J, Seah SY. Crystal structure of reaction intermediates in pyruvate class II aldolase: substrate cleavage enolate stabilization and substrate specificity. J Biol Chem. 2012;287:36208\u201321.","journal-title":"J Biol Chem"},{"key":"1750_CR66","volume-title":"Mathematics of statistics: part 2","author":"JF Kenney","year":"1951","unstructured":"Kenney JF, Keeping ES. Mathematics of statistics: part 2. 2nd ed. Princeton: Van Nostrand; 1951.","edition":"2"},{"key":"1750_CR67","doi-asserted-by":"crossref","first-page":"2395","DOI":"10.1021\/cr00023a004","volume":"7","author":"P Kollman","year":"1993","unstructured":"Kollman P. Free energy calculations: application to chemical and biological phenomena. Chem Rev. 1993;7:2395\u2013417.","journal-title":"Chem Rev"},{"key":"1750_CR68","doi-asserted-by":"crossref","unstructured":"Wang L, Wu Y, Deng Y, Kim B, Pierce L, Krilov G, Lupyan D, Robinson S, Dahlgren MK, Greenwood J, Romero DL, Masse C, Knight JL, Steinbrecher T, Beuming T, Damm W, Harder E, Sherman W, Brewer M, Wester R, Murcko M, Frye L, Farid R, Lin T, Mobley DL, Jorgensen WL, Berne BJ, Friesner RA, Abel R. Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern free-energy calculation protocol and force field. J Am Chem Soc. 2015;137:2695\u2013703.","DOI":"10.1021\/ja512751q"},{"key":"1750_CR69","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1021\/ar000033j","volume":"33","author":"PA Kollman","year":"2000","unstructured":"Kollman PA, Massova I, Reyes C, Kuhn B, Huo S, Chong L, Lee M, Lee T, Duan Y, Wang W, Donini O, Cieplak P, Srinivasan J, Case DA, Cheatham TE. Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Acc Chem Res. 2000;33:889\u201397.","journal-title":"Acc Chem Res"},{"key":"1750_CR70","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1021\/ci300425v","volume":"53","author":"PA Greenidge","year":"2013","unstructured":"Greenidge PA, Kramer C, Mozziconacci JC, Wolf RM. MM\/GBSA binding energy prediction on the PDBbind data set: successes, failures, and directions for further improvement. J Chem Inf Model. 2013;53:201\u20139.","journal-title":"J Chem Inf Model"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-017-1750-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,30]],"date-time":"2019-09-30T19:44:17Z","timestamp":1569872657000},"score":1,"resource":{"primary":{"URL":"http:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-017-1750-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,7,18]]},"references-count":70,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2017,12]]}},"alternative-id":["1750"],"URL":"https:\/\/doi.org\/10.1186\/s12859-017-1750-5","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,7,18]]},"article-number":"343"}}