{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T03:19:56Z","timestamp":1774840796628,"version":"3.50.1"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,11,25]],"date-time":"2020-11-25T00:00:00Z","timestamp":1606262400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2020,11,25]],"date-time":"2020-11-25T00:00:00Z","timestamp":1606262400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Cheminform"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Biomedical information mining is increasingly recognized as a promising technique to accelerate drug discovery and development. Especially, integrative approaches which mine data from several (open) data sources have become more attractive with the increasing possibilities to programmatically access data through Application Programming Interfaces (APIs). The use of open data in conjunction with free, platform-independent analytic tools provides the additional advantage of flexibility, re-usability, and transparency. Here, we present a strategy for performing ligand-based in silico drug repurposing with the analytics platform KNIME. We demonstrate the usefulness of the developed workflow on the basis of two different use cases: a rare disease (here: Glucose Transporter Type 1 (GLUT-1) deficiency), and a new disease (here: COVID 19). The workflow includes a targeted download of data through web services, data curation, detection of enriched structural patterns, as well as substructure searches in DrugBank and a recently deposited data\u00a0set of antiviral drugs provided by Chemical Abstracts Service. Developed workflows, tutorials with detailed step-by-step instructions, and the information gained by the analysis of data for GLUT-1 deficiency syndrome and COVID-19 are made freely available to the scientific community. The provided framework can be reused by researchers for other in silico drug repurposing projects, and it should serve as a valuable teaching resource for conveying integrative data mining strategies.<\/jats:p>","DOI":"10.1186\/s13321-020-00474-z","type":"journal-article","created":{"date-parts":[[2020,11,25]],"date-time":"2020-11-25T05:03:03Z","timestamp":1606280583000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["A ligand-based computational drug repurposing pipeline using KNIME and Programmatic Data Access: case studies for rare diseases and COVID-19"],"prefix":"10.1186","volume":"12","author":[{"given":"Alzbeta","family":"Tuerkova","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9395-1515","authenticated-orcid":false,"given":"Barbara","family":"Zdrazil","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,11,25]]},"reference":[{"issue":"28","key":"474_CR1","doi-asserted-by":"crossref","first-page":"5389","DOI":"10.2174\/0929867325666180530100332","volume":"26","author":"B Karaman","year":"2019","unstructured":"Karaman B, Sippl W (2019) Computational drug repurposing: current trends. Curr Med Chem 26(28):5389\u20135409 [cito:citesAsAuthority][cito:agreesWith]","journal-title":"Curr Med Chem"},{"key":"474_CR2","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1007\/978-1-4939-6613-4_14","volume-title":"Bioinformatics: volume II: structure, function, and applications","author":"J Bajorath","year":"2017","unstructured":"Bajorath J (2017) Compound data mining for drug discovery. In: Keith JM (ed) Bioinformatics: volume II: structure, function, and applications. Springer, New York, NY, pp 247\u2013256"},{"key":"474_CR3","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/B978-0-12-801559-9.00009-0","volume-title":"Artificial neural network for drug design, delivery and disposition","author":"S Agatonovic-Kustrin","year":"2016","unstructured":"Agatonovic-Kustrin S, Morton D (2016) Chapter 9\u2014data mining in drug discovery and design. In: Puri M, Pathak Y, Sutariya VK, Tipparaju S, Moreno W (eds) Artificial neural network for drug design, delivery and disposition. Academic Press, Boston, pp 181\u2013193 [cito:citesAsAuthority][cito:agreesWith]"},{"issue":"D1","key":"474_CR4","doi-asserted-by":"crossref","first-page":"D930","DOI":"10.1093\/nar\/gky1075","volume":"47","author":"D Mendez","year":"2019","unstructured":"Mendez D, Gaulton A, Bento AP, Chambers J, De Veij M, F\u00e9lix E et al (2019) ChEMBL: towards direct deposition of bioassay data. Nucleic Acids Res. 47(D1):D930\u2013D940 [cito:usesDataFrom][cito:citesAsDataSource]","journal-title":"Nucleic Acids Res."},{"issue":"D1","key":"474_CR5","doi-asserted-by":"crossref","first-page":"D1102","DOI":"10.1093\/nar\/gky1033","volume":"47","author":"S Kim","year":"2019","unstructured":"Kim S, Chen J, Cheng T, Gindulyte A, He J, He S et al (2019) PubChem 2019 update: improved access to chemical data. Nucleic Acids Res 47(D1):D1102\u2013D1109 [cito:usesDataFrom][cito:citesAsDataSource]","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"474_CR6","doi-asserted-by":"crossref","first-page":"D506","DOI":"10.1093\/nar\/gky1049","volume":"47","author":"Consortium TU","year":"2019","unstructured":"Consortium TU (2019) UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res 47(D1):D506\u2013D515 [cito:usesDataFrom][cito:citesAsDataSource]","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"474_CR7","doi-asserted-by":"crossref","first-page":"D1074","DOI":"10.1093\/nar\/gkx1037","volume":"46","author":"DS Wishart","year":"2018","unstructured":"Wishart DS, Feunang YD, Guo AC, Lo EJ, Marcu A, Grant JR et al (2018) DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 46(D1):D1074\u2013D1082 [cito:usesDataFrom][cito:citesAsDataSource]","journal-title":"Nucleic Acids Res."},{"issue":"3","key":"474_CR8","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1080\/23808993.2019.1617632","volume":"4","author":"T Qian","year":"2019","unstructured":"Qian T, Zhu S, Hoshida Y (2019) Use of big data in drug development for precision medicine: an update. Expert Rev Precis Med Drug Dev 4(3):189\u2013200 [cito:citesAsAuthority][cito:agreesWith]","journal-title":"Expert Rev Precis Med Drug Dev"},{"issue":"1","key":"474_CR9","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1145\/1656274.1656280","volume":"11","author":"MR Berthold","year":"2009","unstructured":"Berthold MR, Cebron N, Dill F, Gabriel TR, K\u00f6tter T, Meinl T et al (2009) KNIME\u2014the Konstanz information miner: version 2.0 and beyond. ACM SIGKDD Explor Newsl. 11(1):26\u201331 [cito:usesMethodIn]","journal-title":"ACM SIGKDD Explor Newsl."},{"key":"474_CR10","unstructured":"Landrum G. RDKit Documentation. p 159. [cito:usesMethodIn]"},{"issue":"1","key":"474_CR11","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1186\/1471-2105-14-257","volume":"14","author":"S Beisken","year":"2013","unstructured":"Beisken S, Meinl T, Wiswedel B, de Figueiredo LF, Berthold M, Steinbeck C (2013) KNIME-CDK: Workflow-driven cheminformatics. BMC Bioinform. 14(1):257 [cito:usesMethodIn]","journal-title":"BMC Bioinform."},{"issue":"Suppl 1","key":"474_CR12","doi-asserted-by":"crossref","first-page":"P4","DOI":"10.1186\/1758-2946-3-S1-P4","volume":"3","author":"D Pavlov","year":"2011","unstructured":"Pavlov D, Rybalkin M, Karulin B, Kozhevnikov M, Savelyev A, Churinov A (2011) Indigo: universal cheminformatics API. J Cheminformatics. 3(Suppl 1):P4 [cito:citesAsAuthority]","journal-title":"J Cheminformatics."},{"key":"474_CR13","unstructured":"Roughley S. Five Years of the KNIME Vernalis Cheminformatics Community Contribution. Curr Med Chem. 2018; [cito:citesAsAuthority]"},{"issue":"1","key":"474_CR14","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1038\/nrd.2018.168","volume":"18","author":"S Pushpakom","year":"2019","unstructured":"Pushpakom S, Iorio F, Eyers PA, Escott KJ, Hopper S, Wells A et al (2019) Drug repurposing: progress, challenges and recommendations. Nat Rev Drug Discov 18(1):41\u201358 [cito:citesAsAuthority][cito:discusses]","journal-title":"Nat Rev Drug Discov"},{"issue":"2","key":"474_CR15","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.therap.2020.02.006","volume":"75","author":"C Fetro","year":"2020","unstructured":"Fetro C, Scherman D (2020) Drug repurposing in rare diseases: myths and reality. Therapies 75(2):157\u2013160 [cito:citesAsAuthority][cito:discusses]","journal-title":"Therapies"},{"issue":"1","key":"474_CR16","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1186\/s13321-020-00450-7","volume":"12","author":"TN Jarada","year":"2020","unstructured":"Jarada TN, Rokne JG, Alhajj R (2020) A review of computational drug repositioning: strategies, approaches, opportunities, challenges, and directions. J Cheminform. 12(1):46 [cito:citesAsAuthority][cito:discusses]","journal-title":"J Cheminform."},{"issue":"7","key":"474_CR17","doi-asserted-by":"crossref","first-page":"1000450","DOI":"10.1371\/journal.pcbi.1000450","volume":"5","author":"J Li","year":"2009","unstructured":"Li J, Zhu X, Chen JY (2009) Building disease-specific drug-protein connectivity maps from molecular interaction networks and PubMed abstracts. PLOS Comput Biol. 5(7):1000450 [cito:citesAsAuthority][cito:discusses]","journal-title":"PLOS Comput Biol."},{"key":"474_CR18","doi-asserted-by":"crossref","unstructured":"Shawe-Taylor J, Cristianini N, editors. Support Vector Machines. In: An introduction to support vector machines and other kernel-based learning methods. Cambridge: Cambridge University Press; 2000. p. 93\u2013124. https:\/\/www.cambridge.org\/core\/books\/an-introduction-to-support-vector-machines-and-other-kernelbased-learning-methods\/support-vector-machines\/DD4EA48AA6C383944EA67BF8A7BEC6CC[cito:citesAsAuthority][cito:discusses]","DOI":"10.1017\/CBO9780511801389.008"},{"issue":"4","key":"474_CR19","doi-asserted-by":"crossref","first-page":"1308","DOI":"10.1021\/ci030283p","volume":"43","author":"RG Susnow","year":"2003","unstructured":"Susnow RG, Dixon SL (2003) Use of robust classification techniques for the prediction of human cytochrome P450 2D6 inhibition. J Chem Inf Comput Sci 43(4):1308\u20131315 [cito:citesAsAuthority][cito:discusses]","journal-title":"J Chem Inf Comput Sci"},{"issue":"6","key":"474_CR20","doi-asserted-by":"crossref","first-page":"1241","DOI":"10.1016\/j.drudis.2018.01.039","volume":"23","author":"H Chen","year":"2018","unstructured":"Chen H, Engkvist O, Wang Y, Olivecrona M, Blaschke T (2018) The rise of deep learning in drug discovery. Drug Discov Today 23(6):1241\u20131250 [cito:citesAsAuthority][cito:discusses]","journal-title":"Drug Discov Today"},{"issue":"5","key":"474_CR21","doi-asserted-by":"crossref","first-page":"S6","DOI":"10.1186\/1752-0509-7-S5-S6","volume":"7","author":"C Wu","year":"2013","unstructured":"Wu C, Gudivada RC, Aronow BJ, Jegga AG (2013) Computational drug repositioning through heterogeneous network clustering. BMC Syst Biol 7(5):S6 [cito:citesAsAuthority][cito:discusses]","journal-title":"BMC Syst Biol"},{"issue":"1","key":"474_CR22","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1186\/s13321-019-0394-z","volume":"11","author":"F Wang","year":"2019","unstructured":"Wang F, Wu F-X, Li C-Z, Jia C-Y, Su S-W, Hao G-F et al (2019) ACID: a free tool for drug repurposing using consensus inverse docking strategy. J Cheminform. 11(1):73 [cito:citesAsAuthority][cito:discusses]","journal-title":"J Cheminform."},{"issue":"2\u20133","key":"474_CR23","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1002\/minf.201400188","volume":"34","author":"FP Steinmetz","year":"2015","unstructured":"Steinmetz FP, Mellor CL, Meinl T, Cronin MTD (2015) Screening chemicals for receptor-mediated toxicological and pharmacological endpoints: using public data to build screening tools within a KNIME Workflow. Mol Inform 34(2\u20133):171\u2013178 [cito:citesAsAuthority][cito:agreesWith]","journal-title":"Mol Inform"},{"key":"474_CR24","first-page":"1","volume":"30","author":"DE Gordon","year":"2020","unstructured":"Gordon DE, Jang GM, Bouhaddou M, Xu J, Obernier K, White KM et al (2020) A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature 30:1\u201313 [cito:citesAsAuthority][cito:discusses][cito:agreesWith]","journal-title":"Nature"},{"issue":"D1","key":"474_CR25","doi-asserted-by":"crossref","first-page":"D1056","DOI":"10.1093\/nar\/gky1133","volume":"47","author":"D Carvalho-Silva","year":"2019","unstructured":"Carvalho-Silva D, Pierleoni A, Pignatelli M, Ong C, Fumis L, Karamanis N et al (2019) Open Targets Platform: new developments and updates two years on. Nucleic Acids Res 47(D1):D1056\u2013D1065 [cito:usesDataFrom][cito:citesAsDataSource][cito:discusses]","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"474_CR26","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1002\/pro.3730","volume":"29","author":"DS Goodsell","year":"2020","unstructured":"Goodsell DS, Zardecki C, Costanzo LD, Duarte JM, Hudson BP, Persikova I et al (2020) RCSB Protein Data Bank: enabling biomedical research and drug discovery. Protein Sci 29(1):52\u201365 [cito:usesDataFrom][cito:citesAsDataSource]","journal-title":"Protein Sci"},{"issue":"D1","key":"474_CR27","doi-asserted-by":"crossref","first-page":"D1098","DOI":"10.1093\/nar\/gkt1143","volume":"42","author":"AJ Pawson","year":"2014","unstructured":"Pawson AJ, Sharman JL, Benson HE, Faccenda E, Alexander SPH, Buneman OP et al (2014) The IUPHAR\/BPS Guide to PHARMACOLOGY: an expert-driven knowledgebase of drug targets and their ligands. Nucleic Acids Res 42(D1):D1098\u2013D1106 [cito:usesDataFrom][cito:citesAsDataSource]","journal-title":"Nucleic Acids Res"},{"issue":"15","key":"474_CR28","doi-asserted-by":"crossref","first-page":"2887","DOI":"10.1021\/jm9602928","volume":"39","author":"GW Bemis","year":"1996","unstructured":"Bemis GW, Murcko MA (1996) The properties of known drugs. 1. Molecular frameworks. J Med Chem 39(15):2887\u20132893 [cito:usesMethodIn]","journal-title":"J Med Chem"},{"issue":"D1","key":"474_CR29","doi-asserted-by":"crossref","first-page":"D464","DOI":"10.1093\/nar\/gky1004","volume":"47","author":"SK Burley","year":"2019","unstructured":"Burley SK, Berman HM, Bhikadiya C, Bi C, Chen L, Di Costanzo L et al (2019) RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy. Nucleic Acids Res 47(D1):D464\u2013D474 [cito:usesDataFrom][cito:citesAsDataSource]","journal-title":"Nucleic Acids Res"},{"issue":"2","key":"474_CR30","doi-asserted-by":"crossref","first-page":"W612","DOI":"10.1093\/nar\/gkv352","volume":"43","author":"M Davies","year":"2015","unstructured":"Davies M, Nowotka M, Papadatos G, Dedman N, Gaulton A, Atkinson F et al (2015) ChEMBL web services: streamlining access to drug discovery data and utilities. Nucleic Acids Res 43(2):W612\u2013W620 [cito:usesMethodIn]","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"474_CR31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13321-018-0315-6","volume":"10","author":"D Gadaleta","year":"2018","unstructured":"Gadaleta D, Lombardo A, Toma C, Benfenati E (2018) A new semi-automated workflow for chemical data retrieval and quality checking for modeling applications. J Cheminformatics 10(1):1\u201313 [cito:usesMethodIn]","journal-title":"J Cheminformatics"},{"issue":"D1","key":"474_CR32","doi-asserted-by":"crossref","first-page":"D94","DOI":"10.1093\/nar\/gky989","volume":"47","author":"EW Sayers","year":"2019","unstructured":"Sayers EW, Cavanaugh M, Clark K, Ostell J, Pruitt KD, Karsch-Mizrachi I (2019) GenBank. Nucleic Acids Res 47(D1):D94\u2013D99 [cito:citesAsAuthority]","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"474_CR33","doi-asserted-by":"crossref","first-page":"D221","DOI":"10.1093\/nar\/gkx1031","volume":"46","author":"S Pujar","year":"2018","unstructured":"Pujar S, O\u2019Leary NA, Farrell CM, Loveland JE, Mudge JM, Wallin C et al (2018) Consensus coding sequence (CCDS) database: a standardized set of human and mouse protein-coding regions supported by expert curation. Nucleic Acids Res 46(D1):D221\u2013D228 [cito:citesAsAuthority]","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"474_CR34","doi-asserted-by":"crossref","first-page":"D336","DOI":"10.1093\/nar\/gkt1144","volume":"42","author":"U Pieper","year":"2014","unstructured":"Pieper U, Webb BM, Dong GQ, Schneidman-Duhovny D, Fan H, Kim SJ et al (2014) ModBase, a database of annotated comparative protein structure models and associated resources. Nucleic Acids Res 42(D1):D336\u2013D346 [cito:citesAsAuthority]","journal-title":"Nucleic Acids Res"},{"issue":"W1","key":"474_CR35","doi-asserted-by":"crossref","first-page":"W296","DOI":"10.1093\/nar\/gky427","volume":"46","author":"A Waterhouse","year":"2018","unstructured":"Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R et al (2018) SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res 46(W1):W296-303 [cito:citesAsAuthority]","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"474_CR36","doi-asserted-by":"crossref","first-page":"D529","DOI":"10.1093\/nar\/gky1079","volume":"47","author":"R Oughtred","year":"2019","unstructured":"Oughtred R, Stark C, Breitkreutz B-J, Rust J, Boucher L, Chang C et al (2019) The BioGRID interaction database: 2019 update. Nucleic Acids Res 47(D1):D529\u2013D541 [cito:citesAsAuthority]","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"474_CR37","doi-asserted-by":"crossref","first-page":"D358","DOI":"10.1093\/nar\/gkt1115","volume":"42","author":"S Orchard","year":"2014","unstructured":"Orchard S, Ammari M, Aranda B, Breuza L, Briganti L, Broackes-Carter F et al (2014) The MIntAct project\u2014IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res 42(D1):D358\u2013D363 [cito:citesAsAuthority]","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"474_CR38","doi-asserted-by":"crossref","first-page":"D607","DOI":"10.1093\/nar\/gky1131","volume":"47","author":"D Szklarczyk","year":"2019","unstructured":"Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J et al (2019) STRING v11: protein\u2013protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res 47(D1):D607\u2013D613 [cito:citesAsAuthority]","journal-title":"Nucleic Acids Res"},{"issue":"D1","key":"474_CR39","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 (2016) BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology. Nucleic Acids Res 44(D1):D1045\u2013D1053 [cito:citesAsAuthority]","journal-title":"Nucleic Acids Res"},{"issue":"7","key":"474_CR40","doi-asserted-by":"crossref","first-page":"101258","DOI":"10.1016\/j.isci.2020.101258","volume":"23","author":"DR Littler","year":"2020","unstructured":"Littler DR, Gully BS, Colson RN, Rossjohn J (2020) Crystal structure of the SARS-CoV-2 non-structural protein 9, Nsp9. iScience 23(7):101258 [cito:citesAsAuthority]","journal-title":"iScience"},{"issue":"6489","key":"474_CR41","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1126\/science.abb3405","volume":"368","author":"L Zhang","year":"2020","unstructured":"Zhang L, Lin D, Sun X, Curth U, Drosten C, Sauerhering L et al (2020) Crystal structure of SARS-CoV-2 main protease provides a basis for design of improved \u03b1-ketoamide inhibitors. Science 368(6489):409\u2013412 [cito:citesAsAuthority][cito:discusses]","journal-title":"Science"},{"issue":"1","key":"474_CR42","doi-asserted-by":"crossref","first-page":"4541","DOI":"10.1038\/s41467-020-18319-6","volume":"11","author":"J Yang","year":"2020","unstructured":"Yang J, Petitjean SJL, Koehler M, Zhang Q, Dumitru AC, Chen W et al (2020) Molecular interaction and inhibition of SARS-CoV-2 binding to the ACE2 receptor. Nat Commun. 11(1):4541 [cito:citesAsAuthority][cito:discusses]","journal-title":"Nat Commun."},{"issue":"2","key":"474_CR43","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.virol.2008.06.038","volume":"379","author":"SG Fang","year":"2008","unstructured":"Fang SG, Shen H, Wang J, Tay FPL, Liu DX (2008) Proteolytic processing of polyproteins 1a and 1ab between non-structural proteins 10 and 11\/12 of Coronavirus infectious bronchitis virus is dispensable for viral replication in cultured cells. Virology 379(2):175\u2013180 [cito:citesAsAuthority][cito:discusses]","journal-title":"Virology"},{"key":"474_CR44","doi-asserted-by":"crossref","first-page":"104759","DOI":"10.1016\/j.antiviral.2020.104759","volume":"177","author":"CJ Sigrist","year":"2020","unstructured":"Sigrist CJ, Bridge A, Le Mercier P (2020) A potential role for integrins in host cell entry by SARS-CoV-2. Antiviral Res 177:104759 [cito:citesAsAuthority][cito:discusses]","journal-title":"Antiviral Res"},{"key":"474_CR45","first-page":"420","volume-title":"Concepts and applications of molecular similarity","author":"MA Johnson","year":"1990","unstructured":"Johnson MA, Maggiora GM (1990) Concepts and applications of molecular similarity. Wiley, New York, p 420 [cito:citesAsAuthority][cito:discusses]"},{"issue":"19","key":"474_CR46","doi-asserted-by":"crossref","first-page":"4350","DOI":"10.1021\/jm020155c","volume":"45","author":"YC Martin","year":"2002","unstructured":"Martin YC, Kofron JL, Traphagen LM (2002) Do structurally similar molecules have similar biological activity? J Med Chem 45(19):4350\u20134358 [cito:citesAsAuthority][cito:discusses]","journal-title":"J Med Chem"},{"issue":"13","key":"474_CR47","doi-asserted-by":"crossref","first-page":"i366","DOI":"10.1093\/bioinformatics\/btn186","volume":"24","author":"Y Cao","year":"2008","unstructured":"Cao Y, Jiang T, Girke T (2008) A maximum common substructure-based algorithm for searching and predicting drug-like compounds. Bioinformatics 24(13):i366\u2013i374 [cito:usesMethodIn][cito:discusses]","journal-title":"Bioinformatics"},{"issue":"1","key":"474_CR48","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1079\/BJN2002763","volume":"89","author":"IS Wood","year":"2003","unstructured":"Wood IS, Trayhurn P (2003) Glucose transporters (GLUT and SGLT): expanded families of sugar transport proteins. Br J Nutr 89(1):3\u20139 [cito:citesAsAuthority][cito:discusses]","journal-title":"Br J Nutr"},{"issue":"6","key":"474_CR49","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1023\/A:1021238900470","volume":"25","author":"J Klepper","year":"2002","unstructured":"Klepper J, Leiendecker B, Bredahl R, Athanassopoulos S, Heinen F, Gertsen E et al (2002) Introduction of a ketogenic diet in young infants. J Inherit Metab Dis 25(6):449\u2013460 [cito:citesAsAuthority][cito:discusses]","journal-title":"J Inherit Metab Dis"},{"issue":"1","key":"474_CR50","first-page":"211","volume":"21","author":"Z Tanoli","year":"2020","unstructured":"Tanoli Z, Alam Z, Ianevski A, Wennerberg K, V\u00e4h\u00e4-Koskela M, Aittokallio T (2020) Interactive visual analysis of drug\u2013target interaction networks using Drug Target Profiler, with applications to precision medicine and drug repurposing. Brief Bioinform 21(1):211\u2013220 [cito:citesAsAuthority][cito:discusses]","journal-title":"Brief Bioinform"},{"issue":"11","key":"474_CR51","doi-asserted-by":"crossref","first-page":"20741","DOI":"10.3390\/molecules201119714","volume":"20","author":"C-X Wei","year":"2015","unstructured":"Wei C-X, Bian M, Gong G-H (2015) Current research on antiepileptic compounds. Molecules 20(11):20741\u201320776 [cito:citesAsAuthority][cito:agreesWith]","journal-title":"Molecules"},{"issue":"80","key":"474_CR52","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/j.ejmech.2014.04.072","volume":"10","author":"VG Ugale","year":"2014","unstructured":"Ugale VG, Bari SB (2014) Quinazolines: new horizons in anticonvulsant therapy. Eur J Med Chem 10(80):447\u2013501 [cito:citesAsAuthority][cito:agreesWith]","journal-title":"Eur J Med Chem"},{"issue":"7","key":"474_CR53","doi-asserted-by":"crossref","first-page":"1216","DOI":"10.1248\/bpb.28.1216","volume":"28","author":"L-J Cui","year":"2005","unstructured":"Cui L-J, Xie Z-F, Piao H-R, Li G, Chai K-Y, Quan Z-S (2005) Synthesis and anticonvulsant activity of 1-substituted-7-Benzyloxy-4,5-dihydro-[1,2,4]triazolo[4,3-a]quinoline. Biol Pharm Bull 28(7):1216\u20131220 [cito:citesAsAuthority][cito:agreesWith]","journal-title":"Biol Pharm Bull"},{"issue":"21","key":"474_CR54","doi-asserted-by":"crossref","first-page":"4803","DOI":"10.1016\/j.bmcl.2005.07.051","volume":"15","author":"Z-F Xie","year":"2005","unstructured":"Xie Z-F, Chai K-Y, Piao H-R, Kwak K-C, Quan Z-S (2005) Synthesis and anticonvulsant activity of 7-alkoxyl-4,5-dihydro-[1,2,4]triazolo[4,3-a]quinolines. Bioorg Med Chem Lett 15(21):4803\u20134805 [cito:citesAsAuthority][cito:agreesWith]","journal-title":"Bioorg Med Chem Lett"},{"issue":"20","key":"474_CR55","doi-asserted-by":"crossref","first-page":"6868","DOI":"10.1016\/j.bmc.2006.06.044","volume":"14","author":"H-G Jin","year":"2006","unstructured":"Jin H-G, Sun X-Y, Chai K-Y, Piao H-R, Quan Z-S (2006) Anticonvulsant and toxicity evaluation of some 7-alkoxy-4,5-dihydro-[1,2,4]triazolo[4,3-a]quinoline-1(2H)-ones. Bioorg Med Chem 14(20):6868\u20136873 [cito:citesAsAuthority][cito:agreesWith]","journal-title":"Bioorg Med Chem"}],"container-title":["Journal of Cheminformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s13321-020-00474-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s13321-020-00474-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s13321-020-00474-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,21]],"date-time":"2020-12-21T05:07:34Z","timestamp":1608527254000},"score":1,"resource":{"primary":{"URL":"https:\/\/jcheminf.biomedcentral.com\/articles\/10.1186\/s13321-020-00474-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,25]]},"references-count":55,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["474"],"URL":"https:\/\/doi.org\/10.1186\/s13321-020-00474-z","relation":{"has-preprint":[{"id-type":"doi","id":"10.26434\/chemrxiv.12678488.v1","asserted-by":"object"}]},"ISSN":["1758-2946"],"issn-type":[{"value":"1758-2946","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,25]]},"assertion":[{"value":"6 July 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 November 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 November 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"71"}}