{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,22]],"date-time":"2026-02-22T09:06:41Z","timestamp":1771751201273,"version":"3.50.1"},"reference-count":70,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T00:00:00Z","timestamp":1646006400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T00:00:00Z","timestamp":1646006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Cheminform"],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>A key concept in drug design is how natural variants, especially the ones occurring in the binding site of drug targets, affect the inter-individual drug response and efficacy by altering binding affinity. These effects have been studied on very limited and small datasets while, ideally, a large dataset of binding affinity changes due to binding site single-nucleotide polymorphisms (SNPs) is needed for evaluation. However, to the best of our knowledge, such a dataset does not exist. Thus, a reference dataset of ligands binding affinities to proteins with all their reported binding sites\u2019 variants was constructed using a molecular docking approach. Having a large database of protein\u2013ligand complexes covering a wide range of binding pocket mutations and a large small molecules\u2019 landscape is of great importance for several types of studies. For example, developing machine learning algorithms to predict protein\u2013ligand affinity or a SNP effect on it requires an extensive amount of data. In this work, we present PSnpBind: A large database of 0.6 million mutated binding site protein\u2013ligand complexes constructed using a multithreaded virtual screening workflow. It provides a web interface to explore and visualize the protein\u2013ligand complexes and a REST API to programmatically access the different aspects of the database contents. PSnpBind is open source and freely available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/psnpbind.org\">https:\/\/psnpbind.org<\/jats:ext-link>.<\/jats:p>","DOI":"10.1186\/s13321-021-00573-5","type":"journal-article","created":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T14:03:58Z","timestamp":1646057038000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["PSnpBind: a database of mutated binding site protein\u2013ligand complexes constructed using a multithreaded virtual screening workflow"],"prefix":"10.1186","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8399-8990","authenticated-orcid":false,"given":"Ammar","family":"Ammar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3796-1687","authenticated-orcid":false,"given":"Rachel","family":"Cavill","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5301-3142","authenticated-orcid":false,"given":"Chris","family":"Evelo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7542-0286","authenticated-orcid":false,"given":"Egon","family":"Willighagen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,2,28]]},"reference":[{"issue":"3","key":"573_CR1","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1042\/bj20100522","volume":"429","author":"A Daly","year":"2010","unstructured":"Daly A (2010) Pharmacogenetics and human genetic polymorphisms. Biochem J. 429(3):435\u2013449. https:\/\/doi.org\/10.1042\/bj20100522","journal-title":"Biochem J"},{"key":"573_CR2","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1001\/jama.2011.998","volume":"306","author":"RA Wilke","year":"2011","unstructured":"Wilke RA, Dolan ME (2011) Genetics and variable drug response. JAMA. 306:3. https:\/\/doi.org\/10.1001\/jama.2011.998","journal-title":"JAMA."},{"key":"573_CR3","doi-asserted-by":"publisher","DOI":"10.1186\/s13073-017-0502-5","author":"CPI Sch\u00e4rfe","year":"2017","unstructured":"Sch\u00e4rfe CPI, Tremmel R, Schwab M, Kohlbacher O, Marks DS (2017) Genetic variation in human drug-related genes. Genome Med. https:\/\/doi.org\/10.1186\/s13073-017-0502-5","journal-title":"Genome Med"},{"key":"573_CR4","doi-asserted-by":"publisher","unstructured":"Rosello OP, Vlasova AV, Shichkova PA, Markov Y, Vlasov PK, Kondrashov FA (2017). Genomic analysis of human polymorphisms affecting drug-protein interactions. BoRxiv. https:\/\/doi.org\/10.1101\/119933","DOI":"10.1101\/119933"},{"key":"573_CR5","doi-asserted-by":"publisher","first-page":"157","DOI":"10.2142\/biophysico.13.0_157","volume":"13","author":"KD Yamada","year":"2016","unstructured":"Yamada KD, Nishi H, Nakata J, Kinoshita K (2016) Structural characterization of single nucleotide variants at ligand binding sites and enzyme active sites of human proteins. Biophys Physicobiol. 13:157\u2013163. https:\/\/doi.org\/10.2142\/biophysico.13.0_157","journal-title":"Biophys Physicobiol"},{"issue":"13","key":"573_CR6","doi-asserted-by":"publisher","first-page":"3513","DOI":"10.1080\/07391102.2018.1520649","volume":"37","author":"R Kumar","year":"2019","unstructured":"Kumar R, Bansal A, Shukla R, Singh T, Ramteke P, Singh S et al (2019) In silico screening of deleterious single nucleotide polymorphisms (SNPs) and molecular dynamics simulation of disease associated mutations in gene responsible for oculocutaneous albinism type 6 (OCA 6) disorder. J Biomol Struct Dyn. 37(13):3513\u20133523. https:\/\/doi.org\/10.1080\/07391102.2018.1520649","journal-title":"J Biomol Struct Dyn."},{"issue":"4","key":"573_CR7","doi-asserted-by":"publisher","first-page":"0195971","DOI":"10.1371\/journal.pone.0195971","volume":"13","author":"M Seifi","year":"2018","unstructured":"Seifi M, Walter MA (2018) Accurate prediction of functional, structural, and stability changes in PITX2 mutations using in silico bioinformatics algorithms. PLoS ONE. 13(4):0195971. https:\/\/doi.org\/10.1371\/journal.pone.0195971","journal-title":"PLoS ONE."},{"issue":"1","key":"573_CR8","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1007\/s12013-017-0818-1","volume":"76","author":"I Khan","year":"2018","unstructured":"Khan I, Ansari IA, Singh P, Dass JFP, Khan F (2018) Identification and characterization of functional single nucleotide polymorphisms (SNPs) in Axin 1 gene: a molecular dynamics approach. Cell Biochem Biophys. 76(1):173\u2013185. https:\/\/doi.org\/10.1007\/s12013-017-0818-1","journal-title":"Cell Biochem Biophys"},{"issue":"3","key":"573_CR9","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1039\/C3MB70427K","volume":"10","author":"C George Priya Doss","year":"2014","unstructured":"George Priya Doss C, Rajith B, Chakraboty C, Balaji V, Magesh R, Gowthami B et al (2014) In silico profiling and structural insights of missense mutations in RET protein kinase domain by molecular dynamics and docking approach. Mol BioSyst. 10(3):421\u2013436. https:\/\/doi.org\/10.1039\/C3MB70427K","journal-title":"Mol BioSyst."},{"key":"573_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2014\/895831","volume":"1","author":"CG Priya Doss","year":"2014","unstructured":"Priya Doss CG, Chakraborty C, Chen L, Zhu H (2014) Integrating in silico prediction methods, molecular docking, and molecular dynamics simulation to predict the impact of ALK Missense Mutations in structural perspective. BioMed Res Int. 1:1\u201314. https:\/\/doi.org\/10.1155\/2014\/895831","journal-title":"BioMed Res Int."},{"key":"573_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0188143","volume":"13","author":"M Arshad","year":"2018","unstructured":"Arshad M, Bhatti A, John P (2018) Identification and in silico analysis of functional SNPs of human TAGAP protein: a comprehensive study. PLoS ONE. 13:1. https:\/\/doi.org\/10.1371\/journal.pone.0188143","journal-title":"PLoS ONE."},{"issue":"3","key":"573_CR12","doi-asserted-by":"publisher","first-page":"3583","DOI":"10.1002\/jcb.27636","volume":"120","author":"GRC Pereira","year":"2019","unstructured":"Pereira GRC, Da Silva ANR, Do Nascimento SS, De Mesquita JF (2019) In silico analysis and molecular dynamics simulation of human superoxide dismutase 3 (SOD3) genetic variants. J Cell Biochem. 120(3):3583\u20133598. https:\/\/doi.org\/10.1002\/jcb.27636","journal-title":"J Cell Biochem"},{"key":"573_CR13","doi-asserted-by":"crossref","unstructured":"Dakal TC, Kala D, Dhiman G, Yadav V, Krokhotin A, Dokholyan NV (2017). Predicting the functional consequences of non-synonymous single nucleotide polymorphisms in IL8 gene. Sci Rep. 7(1). http:\/\/www.nature.com\/articles\/s41598-017-06575-4","DOI":"10.1038\/s41598-017-06575-4"},{"issue":"1","key":"573_CR14","doi-asserted-by":"publisher","first-page":"bas018","DOI":"10.1093\/database\/bas018","volume":"2012","author":"TD Luu","year":"2012","unstructured":"Luu TD, Rusu AM, Walter V, Ripp R, Moulinier L, Muller J et al (2012) MSV3d: database of human MisSense variants mapped to 3D protein structure. Database. 2012(1):bas018. https:\/\/doi.org\/10.1093\/database\/bas018","journal-title":"Database."},{"issue":"16","key":"573_CR15","doi-asserted-by":"publisher","first-page":"2534","DOI":"10.1093\/bioinformatics\/btw153","volume":"32","author":"HC Lu","year":"2016","unstructured":"Lu HC, Herrera Braga J, Fraternali F (2016) PinSnps: structural and functional analysis of SNPs in the context of protein interaction networks. Bioinformatics. 32(16):2534\u20132536. https:\/\/doi.org\/10.1093\/bioinformatics\/btw153","journal-title":"Bioinformatics."},{"issue":"11","key":"573_CR16","doi-asserted-by":"publisher","first-page":"1431","DOI":"10.1093\/bioinformatics\/btp242","volume":"25","author":"M Ryan","year":"2009","unstructured":"Ryan M, Diekhans M, Lien S, Liu Y, Karchin R (2009) LS-SNP\/PDB: annotated non-synonymous SNPs mapped to Protein Data Bank structures. Bioinformatics. 25(11):1431\u20131432. https:\/\/doi.org\/10.1093\/bioinformatics\/btp242","journal-title":"Bioinformatics."},{"key":"573_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12864-016-3028-0","volume":"17","author":"O Solomon","year":"2016","unstructured":"Solomon O, Kunik V, Simon A, Kol N, Barel O, Lev A et al (2016) G23D: Online tool for mapping and visualization of genomic variants on 3D protein structures. BMC Genomics. 17:1. https:\/\/doi.org\/10.1186\/s12864-016-3028-0","journal-title":"BMC Genomics."},{"key":"573_CR18","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1186\/1471-2105-7-166","volume":"7","author":"P Yue","year":"2006","unstructured":"Yue P, Melamud E, Moult J (2006) SNPs3D: candidate gene and SNP selection for association studies. BMC Bioinform. 7:166. https:\/\/doi.org\/10.1186\/1471-2105-7-166","journal-title":"BMC Bioinform"},{"issue":"4","key":"573_CR19","doi-asserted-by":"publisher","first-page":"616","DOI":"10.1002\/humu.20898","volume":"30","author":"JM Hurst","year":"2009","unstructured":"Hurst JM, McMillan LEM, Porter CT, Allen J, Fakorede A, Martin ACR (2009) The SAAPdb web resource: a large-scale structural analysis of mutant proteins. Human Mutat. 30(4):616\u2013624. https:\/\/doi.org\/10.1002\/humu.20898","journal-title":"Human Mutat"},{"key":"573_CR20","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1016\/j.csbj.2015.09.002","volume":"13","author":"D Wang","year":"2015","unstructured":"Wang D, Song L, Singh V, Rao S, An L, Madhavan S (2015) SNP2Structure: a public and versatile Resource for Mapping and Three-Dimensional Modeling of Missense SNPs on Human Protein Structures. Comput Struct Biotechnol J. 13:514\u2013519. https:\/\/doi.org\/10.1016\/j.csbj.2015.09.002","journal-title":"Comput Struct Biotechnol J."},{"issue":"90001","key":"573_CR21","doi-asserted-by":"publisher","first-page":"520D","DOI":"10.1093\/nar\/gkh104","volume":"32","author":"NO Stitziel","year":"2004","unstructured":"Stitziel NO (2004) topoSNP: a topographic database of non-synonymous single nucleotide polymorphisms with and without known disease association. Nucleic Acids Res. 32(90001):520D \u2013 522. https:\/\/doi.org\/10.1093\/nar\/gkh104","journal-title":"Nucleic Acids Res"},{"key":"573_CR22","doi-asserted-by":"publisher","first-page":"D409","DOI":"10.1093\/nar\/gkm801","volume":"36","author":"H Kono","year":"2007","unstructured":"Kono H, Yuasa T, Nishiue S, Yura K (2007) coliSNP database server mapping nsSNPs on protein structures. Nucleic Acids Res. 36:D409\u2013D413. https:\/\/doi.org\/10.1093\/nar\/gkm801","journal-title":"Nucleic Acids Res"},{"key":"573_CR23","doi-asserted-by":"publisher","first-page":"W463","DOI":"10.1093\/nar\/gkw364","volume":"44","author":"A Gress","year":"2016","unstructured":"Gress A, Ramensky V, B\u00fcch J (2016) StructMAn: annotation of single-nucleotide polymorphisms in the structural context. Nucleic Acids Res. 44:W463\u2013W468. https:\/\/doi.org\/10.1093\/nar\/gkw364","journal-title":"Nucleic Acids Res"},{"issue":"13","key":"573_CR24","doi-asserted-by":"publisher","first-page":"2460","DOI":"10.1016\/j.jmb.2019.04.043","volume":"431","author":"TC Ofoegbu","year":"2019","unstructured":"Ofoegbu TC, David A, Kelley LA, Mezulis S, Islam SA, Mersmann SF et al (2019) PhyreRisk: a dynamic web application to bridge genomics, proteomics and 3D structural data to guide interpretation of human genetic variants. J Mol Biol. 431(13):2460\u20132466. https:\/\/doi.org\/10.1016\/j.jmb.2019.04.043","journal-title":"J Mol Biol"},{"issue":"12","key":"573_CR25","doi-asserted-by":"publisher","first-page":"4111","DOI":"10.1021\/jm048957q","volume":"48","author":"R Wang","year":"2005","unstructured":"Wang R, Fang X, Lu Y, Yang CY, Wang S (2005) The PDBbind aatabase: methodologies and updates. J Med Chem. 48(12):4111\u20134119. https:\/\/doi.org\/10.1021\/jm048957q[cito:usesDataFrom]","journal-title":"J Med Chem"},{"issue":"1","key":"573_CR26","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1093\/nar\/28.1.235","volume":"28","author":"HM Berman","year":"2000","unstructured":"Berman HM (2000) The Protein Data Bank. Nucleic Acids Res. 28(1):235\u2013242. https:\/\/doi.org\/10.1093\/nar\/28.1.235[cito:usesDataFrom]","journal-title":"Nucleic Acids Res."},{"issue":"90001","key":"573_CR27","doi-asserted-by":"publisher","first-page":"115D","DOI":"10.1093\/nar\/gkh131","volume":"32","author":"R Apweiler","year":"2004","unstructured":"Apweiler R (2004) UniProt: the Universal Protein knowledgebase. Nucleic Acids Res. 32(90001):115D \u2013 119. https:\/\/doi.org\/10.1093\/nar\/gkh131[cito:usesDataFrom]","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"573_CR28","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1186\/1471-2164-11-293","volume":"11","author":"Y Chen","year":"2010","unstructured":"Chen Y, Cunningham F, Rios D, McLaren WM, Smith J, Pritchard B et al (2010) Ensembl variation resources. BMC Genom. 11(1):293. https:\/\/doi.org\/10.1186\/1471-2164-11-293[cito:citesAsDataSource]","journal-title":"BMC Genom"},{"key":"573_CR29","doi-asserted-by":"publisher","first-page":"D1062","DOI":"10.1093\/nar\/gkx1153","volume":"46","author":"MJ Landrum","year":"2018","unstructured":"Landrum MJ, Lee JM, Benson M, Brown GR, Chao C, Chitipiralla S et al (2018) ClinVar: improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 46:D1062\u2013D1067. https:\/\/doi.org\/10.1093\/nar\/gkx1153[cito:citesAsDataSource]","journal-title":"Nucleic Acids Res"},{"key":"573_CR30","doi-asserted-by":"publisher","first-page":"D483","DOI":"10.1093\/nar\/gks1258","volume":"41","author":"S Velankar","year":"2012","unstructured":"Velankar S, Dana JM, Jacobsen J, van Ginkel G, Gane PJ, Luo J et al (2012) SIFTS: Structure Integration with Function, Taxonomy and Sequences resource. Nucleic Acids Res. 41:D483\u2013D489. https:\/\/doi.org\/10.1093\/nar\/gks1258[cito:usesDataFrom]","journal-title":"Nucleic Acids Res"},{"key":"573_CR31","doi-asserted-by":"publisher","first-page":"D1100","DOI":"10.1093\/nar\/gkr777","volume":"40","author":"A Gaulton","year":"2012","unstructured":"Gaulton A, Bellis LJ, Bento AP, Chambers J, Davies M, Hersey A et al (2012) ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res. 40:D1100\u2013D1107. https:\/\/doi.org\/10.1093\/nar\/gkr777[cito:usesDataFrom]","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"573_CR32","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1002\/prot.20491","volume":"60","author":"SO Garbuzynskiy","year":"2005","unstructured":"Garbuzynskiy SO, Melnik BS, Lobanov MY, Finkelstein AV, Galzitskaya OV (2005) Comparison of X-ray and NMR structures: is there a systematic difference in residue contacts between X-ray- and NMR-resolved protein structures? Proteins. 60(1):139\u2013147. https:\/\/doi.org\/10.1002\/prot.20491","journal-title":"Proteins"},{"issue":"2","key":"573_CR33","doi-asserted-by":"publisher","first-page":"895","DOI":"10.1021\/acs.jcim.8b00545","volume":"59","author":"M Su","year":"2019","unstructured":"Su M, Yang Q, Du Y, Feng G, Liu Z, Li Y et al (2019) Comparative assessment of scoring functions: the CASF-2016 update. J Chem Inform Model. 59(2):895\u2013913. https:\/\/doi.org\/10.1021\/acs.jcim.8b00545","journal-title":"J Chem Inform Model"},{"issue":"11","key":"573_CR34","doi-asserted-by":"publisher","first-page":"2109","DOI":"10.1002\/jcc.21498","volume":"31","author":"X Li","year":"2010","unstructured":"Li X, Li Y, Cheng T, Liu Z, Wang R (2010) Evaluation of the performance of four molecular docking programs on a diverse set of protein-ligand complexes. J Comput Chem. 31(11):2109\u20132125. https:\/\/doi.org\/10.1002\/jcc.21498","journal-title":"J Comput Chem"},{"issue":"20","key":"573_CR35","doi-asserted-by":"publisher","first-page":"2693","DOI":"10.1093\/bioinformatics\/bts494","volume":"28","author":"A Prlic","year":"2012","unstructured":"Prlic A, Yates A, Bliven SE, Rose PW, Jacobsen J, Troshin PV et al (2012) BioJava: an open-source framework for bioinformatics in 2012. Bioinformatics. 28(20):2693\u20132695. https:\/\/doi.org\/10.1093\/bioinformatics\/bts494[cito:usesMethodIn]","journal-title":"Bioinformatics."},{"issue":"18","key":"573_CR36","doi-asserted-by":"publisher","first-page":"2847","DOI":"10.1093\/bioinformatics\/btw313","volume":"32","author":"Z Gu","year":"2016","unstructured":"Gu Z, Eils R, Schlesner M (2016) Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 32(18):2847\u20132849. https:\/\/doi.org\/10.1093\/bioinformatics\/btw313[cito:usesMethodIn]","journal-title":"Bioinformatics."},{"key":"573_CR37","doi-asserted-by":"publisher","first-page":"W382","DOI":"10.1093\/nar\/gki387","volume":"33","author":"J Schymkowitz","year":"2005","unstructured":"Schymkowitz J, Borg J, Stricher F, Nys R, Rousseau F, Serrano L (2005) The FoldX web server: an online force field. Nucleic Acids Res. 33:W382\u2013W388. https:\/\/doi.org\/10.1093\/nar\/gki387[cito:usesMethodIn]","journal-title":"Nucleic Acids Res"},{"issue":"6","key":"573_CR38","doi-asserted-by":"publisher","first-page":"675","DOI":"10.1002\/humu.21242","volume":"31","author":"S Khan","year":"2010","unstructured":"Khan S, Vihinen M (2010) Performance of protein stability predictors. Human Mutat. 31(6):675\u2013684. https:\/\/doi.org\/10.1002\/humu.21242","journal-title":"Human Mutat"},{"issue":"9","key":"573_CR39","doi-asserted-by":"publisher","first-page":"553","DOI":"10.1093\/protein\/gzp030","volume":"22","author":"V Potapov","year":"2009","unstructured":"Potapov V, Cohen M, Schreiber G (2009) Assessing computational methods for predicting protein stability upon mutation: good on average but not in the details. Protein Eng Des Select. 22(9):553\u2013560. https:\/\/doi.org\/10.1093\/protein\/gzp030","journal-title":"Protein Eng Des Select"},{"key":"573_CR40","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.softx.2015.06.001","volume":"1\u20132","author":"MJ Abraham","year":"2015","unstructured":"Abraham MJ, Murtola T, Schulz R, P\u00e1ll S, Smith JC, Hess B et al (2015) GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX. 1\u20132:19\u201325. https:\/\/doi.org\/10.1016\/j.softx.2015.06.001[cito:usesMethodIn]","journal-title":"SoftwareX."},{"issue":"18","key":"573_CR41","doi-asserted-by":"publisher","first-page":"3586","DOI":"10.1021\/jp973084f","volume":"102","author":"AD MacKerell","year":"1998","unstructured":"MacKerell AD, Bashford D, Bellott M, Dunbrack RL, Evanseck JD, Field MJ et al (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. J Phys Chem B. 102(18):3586\u20133616. https:\/\/doi.org\/10.1021\/jp973084f","journal-title":"J Phys Chem B."},{"issue":"2","key":"573_CR42","doi-asserted-by":"publisher","first-page":"926","DOI":"10.1063\/1.445869","volume":"79","author":"WL Jorgensen","year":"1983","unstructured":"Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys. 79(2):926\u2013935. https:\/\/doi.org\/10.1063\/1.445869","journal-title":"J Chem Phys."},{"issue":"3","key":"573_CR43","doi-asserted-by":"publisher","first-page":"773","DOI":"10.1021\/cr020467n","volume":"103","author":"T Dudev","year":"2003","unstructured":"Dudev T, Lim C (2003) Principles governing Mg, Ca, Zn binding and selectivity in proteins. Chem Rev. 103(3):773\u2013788. https:\/\/doi.org\/10.1021\/cr020467n","journal-title":"Chem Rev"},{"key":"573_CR44","unstructured":"Astuti AD, Mutiara AB (2009). Performance analysis on molecular dynamics simulation of protein using GROMACS. arXivorg. 2009; arXiv: 0912.0893v1"},{"key":"573_CR45","doi-asserted-by":"crossref","unstructured":"Gajula M, Kumar A, Ijaq J (2016). Protocol for Molecular Dynamics Simulations of Proteins. BIO-PROTOCOL. 6(23). https:\/\/bio-protocol.org\/e2051","DOI":"10.21769\/BioProtoc.2051"},{"key":"573_CR46","doi-asserted-by":"publisher","DOI":"10.1186\/s12900-015-0046-0","author":"S Moreira","year":"2015","unstructured":"Moreira S, Noutahi E, Lamoureux G, Burger G (2015) Three-dimensional structure model and predicted ATP interaction rewiring of a deviant RNA ligase 2. BMC Struct Biol. https:\/\/doi.org\/10.1186\/s12900-015-0046-0","journal-title":"BMC Struct Biol"},{"issue":"6","key":"573_CR47","doi-asserted-by":"publisher","first-page":"e0215723","DOI":"10.1371\/journal.pone.0215723","volume":"14","author":"GRC Pereira","year":"2019","unstructured":"Pereira GRC, Tellini GHAS, De Mesquita JF (2019) In silico analysis of PFN1 related to amyotrophic lateral sclerosis. PLoS ONE. 14(6):e0215723. https:\/\/doi.org\/10.1371\/journal.pone.0215723","journal-title":"PLoS ONE."},{"key":"573_CR48","first-page":"1","volume":"1","author":"TT Nguyen","year":"2014","unstructured":"Nguyen TT, Viet MH, Li MS (2014) Effects of water models on binding affinity: evidence from all-atom simulation of binding of Tamiflu to A\/H5N1 neuraminidase. Sci World J. 1:1\u201314","journal-title":"Sci World J."},{"key":"573_CR49","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1758-2946-3-33","volume":"3","author":"NM O\u2019Boyle","year":"2011","unstructured":"O\u2019Boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchison GR (2011) Open Babel: an open chemical toolbox. J Cheminform. 3:1. https:\/\/doi.org\/10.1186\/1758-2946-3-33[cito:usesMethodIn]","journal-title":"J Cheminform."},{"key":"573_CR50","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13321-015-0069-3","volume":"7","author":"D Bajusz","year":"2015","unstructured":"Bajusz D, R\u00e1cz A, H\u00e9berger K (2015) Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations? J Cheminform. 7:1. https:\/\/doi.org\/10.1186\/s13321-015-0069-3[cito:usesMethodIn]","journal-title":"J Cheminform"},{"issue":"5","key":"573_CR51","doi-asserted-by":"publisher","first-page":"490","DOI":"10.1002\/(SICI)1096-987X(199604)17:5\/6<490::AID-JCC1>3.0.CO;2-P","volume":"17","author":"TA Halgren","year":"1996","unstructured":"Halgren TA (1996) Merck molecular force field. I, Basis, form, scope, parameterization, and performance of MMFF94. J Comput Chem. 17(5):490\u2013519","journal-title":"J Comput Chem."},{"issue":"42","key":"573_CR52","doi-asserted-by":"publisher","first-page":"10656","DOI":"10.1002\/anie.201204268","volume":"51","author":"SAI Seidel","year":"2012","unstructured":"Seidel SAI, Wienken CJ, Geissler S, Jerabek-Willemsen M, Duhr S, Reiter A et al (2012) Label-free microscale thermophoresis discriminates sites and affinity of protein-ligand binding. Wiley. 51(42):10656\u201310659. https:\/\/doi.org\/10.1002\/anie.201204268","journal-title":"Wiley."},{"key":"573_CR53","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1016\/j.molstruc.2014.03.009","volume":"1077","author":"M Jerabek-Willemsen","year":"2014","unstructured":"Jerabek-Willemsen M, Andr\u00e9 T, Wanner R, Roth HM, Duhr S, Baaske P et al (2014) MicroScale thermophoresis: interaction analysis and beyond. Elsevier BV. 1077:101\u2013113. https:\/\/doi.org\/10.1016\/j.molstruc.2014.03.009","journal-title":"Elsevier BV."},{"key":"573_CR54","doi-asserted-by":"publisher","unstructured":"Huang R, Bonnichon A, Claridge TDW, Leung IKH (2017). Protein-ligand binding affinity determination by the waterLOGSY method: An optimised approach considering ligand rebinding. Springer Science and Business Media LLC. 2017;7(1). https:\/\/doi.org\/10.1038\/srep43727","DOI":"10.1038\/srep43727"},{"issue":"9","key":"573_CR55","doi-asserted-by":"publisher","first-page":"1399","DOI":"10.3390\/molecules22091399","volume":"22","author":"Y Li","year":"2017","unstructured":"Li Y, Kang C (2017) Solution NMR spectroscopy in target-based drug discovery. MDPI AG. 22(9):1399. https:\/\/doi.org\/10.3390\/molecules22091399","journal-title":"MDPI AG."},{"issue":"5292","key":"573_CR56","doi-asserted-by":"publisher","first-page":"1531","DOI":"10.1126\/science.274.5292.1531","volume":"274","author":"SB Shuker","year":"1996","unstructured":"Shuker SB, Hajduk PJ, Meadows RP, Fesik SW (1996) Discovering high-affinity ligands for proteins: SAR by NMR. Am Assoc Adv Sci. 274(5292):1531\u20131534. https:\/\/doi.org\/10.1126\/science.274.5292.1531","journal-title":"Am Assoc Adv Sci."},{"key":"573_CR57","doi-asserted-by":"crossref","unstructured":"Rezaei M, Li Y, Li X, Li C (2019). Improving the Accuracy of Protein-Ligand Binding Affinity Prediction by Deep Learning Models: Benchmark and Model. figshare. 2019;Available from: https:\/\/chemrxiv.org\/articles\/Improving_the_Accuracy_of_Protein-Ligand_Binding_Affinity_Prediction_by_Deep_Learning_Models_Benchmark_and_Model\/9866912","DOI":"10.26434\/chemrxiv.9866912"},{"issue":"22","key":"573_CR58","doi-asserted-by":"publisher","first-page":"12127","DOI":"10.1039\/C8RA00003D","volume":"8","author":"I Kundu","year":"2018","unstructured":"Kundu I, Paul G, Banerjee R (2018) A machine learning approach towards the prediction of protein-ligand binding affinity based on fundamental molecular properties. RSC Adv 8(22):12127\u201312137. https:\/\/doi.org\/10.1039\/C8RA00003D","journal-title":"RSC Adv"},{"key":"573_CR59","doi-asserted-by":"publisher","DOI":"10.1002\/jcc.21334","author":"O Trott","year":"2009","unstructured":"Trott O, Olson AJ (2009) AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. https:\/\/doi.org\/10.1002\/jcc.21334[cito:usesMethodIn]","journal-title":"J Comput Chem."},{"issue":"1","key":"573_CR60","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1021\/ci00057a005","volume":"28","author":"D Weininger","year":"1988","unstructured":"Weininger D (1988) a chemical language and information System. 1. Introduction to methodology and encoding rules. J Chem Inf Comput Sci. 28(1):31\u201336. https:\/\/doi.org\/10.1021\/ci00057a005","journal-title":"J Chem Inf Comput Sci."},{"issue":"5","key":"573_CR61","doi-asserted-by":"publisher","first-page":"905","DOI":"10.1038\/nprot.2016.051","volume":"11","author":"S Forli","year":"2016","unstructured":"Forli S, Huey R, Pique ME, Sanner MF, Goodsell DS, Olson AJ (2016) Computational protein-ligand docking and virtual drug screening with the AutoDock suite. Nature Protocols. 11(5):905\u2013919. https:\/\/doi.org\/10.1038\/nprot.2016.051","journal-title":"Nature Protocols."},{"issue":"3","key":"573_CR62","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1007\/s10822-016-9900-9","volume":"30","author":"MM Jaghoori","year":"2016","unstructured":"Jaghoori MM, Bleijlevens B, Olabarriaga SD (2016) 1001 Ways to run AutoDock Vina for virtual screening. J Comput Aided Mol Des. 30(3):237\u2013249. https:\/\/doi.org\/10.1007\/s10822-016-9900-9","journal-title":"J Comput Aided Mol Des"},{"key":"573_CR63","doi-asserted-by":"crossref","unstructured":"Abdollahi\u00a0Vayghan L, Saied MA, Toeroe M, Khendek F (2018). Deploying Microservice Based Applications with Kubernetes: Experiments and Lessons Learned. In: IEEE 11th International Conference on Cloud Computing (CLOUD). IEEE; . p. 970\u2013973. https:\/\/ieeexplore.ieee.org\/document\/8457916\/","DOI":"10.1109\/CLOUD.2018.00148"},{"key":"573_CR64","unstructured":"European Organization For Nuclear Research, OpenAIRE (2013). European Organization For Nuclear Research, OpenAIRE, editors. Zenodo. CERN; . https:\/\/www.zenodo.org\/"},{"key":"573_CR65","unstructured":"W3. W3, editor. HTML5, A vocabulary and associated APIs for HTML and XHTML. W3; 2011. https:\/\/dev.w3.org\/html5\/spec-LC\/"},{"key":"573_CR66","unstructured":"W3. W3, editor. Introduction to CSS3. W3; 2001. https:\/\/www.w3.org\/TR\/2001\/WD-css3-roadmap-20010523"},{"issue":"4","key":"573_CR67","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1002\/bmb.2006.494034042644","volume":"34","author":"A Herr\u00e1ez","year":"2006","unstructured":"Herr\u00e1ez A (2006) Biomolecules in the computer: Jmol to the rescue. Biochem Mol Biol Educ. 34(4):255\u2013261. https:\/\/doi.org\/10.1002\/bmb.2006.494034042644[cito:usesMethodIn]","journal-title":"Biochem Mol Biol Educ"},{"issue":"2","key":"573_CR68","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1021\/ci025584y","volume":"43","author":"C Steinbeck","year":"2003","unstructured":"Steinbeck C, Han Y, Kuhn S, Horlacher O, Luttmann E, Willighagen E (2003) The Chemistry Development Kit (CDK): an open-source java Library for Chemo- and Bioinformatics. J Chem Inform Comput Sci. 43(2):493\u2013500. https:\/\/doi.org\/10.1021\/ci025584y","journal-title":"J Chem Inform Comput Sci"},{"issue":"3","key":"573_CR69","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1002\/ijch.201300024","volume":"53","author":"RM Hanson","year":"2013","unstructured":"Hanson RM, Prilusky J, Renjian Z, Nakane T, Sussman JL (2013) JSmol and the Next-Generation Web-Based representation of 3D molecular structure as applied toproteopedia. Israel J Chem. 53(3):207\u2013216. https:\/\/doi.org\/10.1002\/ijch.201300024","journal-title":"Israel J Chem"},{"key":"573_CR70","unstructured":"Gray CA A J G\u00a0Goble, R J. Bioschemas (2017): From Potato Salad to Protein Annotation. In: In International Semantic Web Conference (Posters, Demos & Industry Tracks). In International Semantic Web Conference (Posters, Demos & Industry Tracks). p. 1\u201310. https:\/\/bioschemas.org"}],"container-title":["Journal of Cheminformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13321-021-00573-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13321-021-00573-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13321-021-00573-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T14:07:40Z","timestamp":1646057260000},"score":1,"resource":{"primary":{"URL":"https:\/\/jcheminf.biomedcentral.com\/articles\/10.1186\/s13321-021-00573-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,28]]},"references-count":70,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["573"],"URL":"https:\/\/doi.org\/10.1186\/s13321-021-00573-5","relation":{},"ISSN":["1758-2946"],"issn-type":[{"value":"1758-2946","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,28]]},"assertion":[{"value":"11 August 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 November 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 February 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"8"}}