{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T17:13:22Z","timestamp":1774890802647,"version":"3.50.1"},"reference-count":73,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2021,3,31]],"date-time":"2021-03-31T00:00:00Z","timestamp":1617148800000},"content-version":"vor","delay-in-days":89,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U24CA224260, U54HL127624, OT2OD030160"],"award-info":[{"award-number":["U24CA224260, U54HL127624, OT2OD030160"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,3,31]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Understanding the underlying molecular and structural similarities between seemingly heterogeneous sets of drugs can aid in identifying drug repurposing opportunities and assist in the discovery of novel properties of preclinical small molecules. A wealth of information about drug and small molecule structure, targets, indications and side effects; induced gene expression signatures; and other attributes are publicly available through web-based tools, databases and repositories. By processing, abstracting and aggregating information from these resources into drug set libraries, knowledge about novel properties of drugs and small molecules can be systematically imputed with machine learning. In addition, drug set libraries can be used as the underlying database for drug set enrichment analysis. Here, we present Drugmonizome, a database with a search engine for querying annotated sets of drugs and small molecules for performing drug set enrichment analysis. Utilizing the data within Drugmonizome, we also developed Drugmonizome-ML. Drugmonizome-ML enables users to construct customized machine learning pipelines using the drug set libraries from Drugmonizome. To demonstrate the utility of Drugmonizome, drug sets from 12 independent SARS-CoV-2 in vitro screens were subjected to consensus enrichment analysis. Despite the low overlap among these 12 independent in vitro screens, we identified common biological processes critical for blocking viral replication. To demonstrate Drugmonizome-ML, we constructed a machine learning pipeline to predict whether approved and preclinical drugs may induce peripheral neuropathy as a potential side effect. Overall, the Drugmonizome and Drugmonizome-ML resources provide rich and diverse knowledge about drugs and small molecules for direct systems pharmacology applications.<\/jats:p><jats:p>Database URL: https:\/\/maayanlab.cloud\/drugmonizome\/.<\/jats:p>","DOI":"10.1093\/database\/baab017","type":"journal-article","created":{"date-parts":[[2021,3,19]],"date-time":"2021-03-19T20:12:12Z","timestamp":1616184732000},"source":"Crossref","is-referenced-by-count":28,"title":["Drugmonizome and Drugmonizome-ML: integration and abstraction of small molecule attributes for drug enrichment analysis and machine learning"],"prefix":"10.1093","volume":"2021","author":[{"given":"Eryk","family":"Kropiwnicki","sequence":"first","affiliation":[{"name":"Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-Based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG); Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, Box 1603, New York, NY 10029, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4836-0518","authenticated-orcid":false,"given":"John E","family":"Evangelista","sequence":"additional","affiliation":[{"name":"Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-Based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG); Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, Box 1603, New York, NY 10029, USA"}]},{"given":"Daniel J","family":"Stein","sequence":"additional","affiliation":[{"name":"Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-Based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG); Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, Box 1603, New York, NY 10029, USA"}]},{"given":"Daniel J B","family":"Clarke","sequence":"additional","affiliation":[{"name":"Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-Based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG); Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, Box 1603, New York, NY 10029, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1982-7652","authenticated-orcid":false,"given":"Alexander","family":"Lachmann","sequence":"additional","affiliation":[{"name":"Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-Based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG); Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, Box 1603, New York, NY 10029, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7812-7752","authenticated-orcid":false,"given":"Maxim V","family":"Kuleshov","sequence":"additional","affiliation":[{"name":"Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-Based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG); Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, Box 1603, New York, NY 10029, USA"}]},{"given":"Minji","family":"Jeon","sequence":"additional","affiliation":[{"name":"Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-Based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG); Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, Box 1603, New York, NY 10029, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2755-2097","authenticated-orcid":false,"given":"Kathleen M","family":"Jagodnik","sequence":"additional","affiliation":[{"name":"Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-Based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG); Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, Box 1603, New York, NY 10029, USA"}]},{"given":"Avi","family":"Ma\u2019ayan","sequence":"additional","affiliation":[{"name":"Department of Pharmacological Sciences; Mount Sinai Center for Bioinformatics; Big Data to Knowledge, Library of Integrated Network-Based Cellular Signatures, Data Coordination and Integration Center (BD2K-LINCS DCIC); Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG); Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, Box 1603, New York, NY 10029, USA"}]}],"member":"286","published-online":{"date-parts":[[2021,3,31]]},"reference":[{"key":"2021070818434758000_R1","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1038\/nrd3681","article-title":"Diagnosing the decline in pharmaceutical R&D efficiency","volume":"11","author":"Scannell","year":"2012","journal-title":"Nat. Rev. Drug Discov."},{"key":"2021070818434758000_R2","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1038\/nrd4609","article-title":"An analysis of the attrition of drug candidates from four major pharmaceutical companies","volume":"14","author":"Waring","year":"2015","journal-title":"Nat. Rev. Drug Discov."},{"key":"2021070818434758000_R3","first-page":"277","volume-title":"Progress in Medicinal Chemistry","author":"Brown","year":"2018"},{"key":"2021070818434758000_R4","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1080\/23808993.2019.1617632","article-title":"Use of big data in drug development for precision medicine: an update","volume":"4","author":"Qian","year":"2019","journal-title":"Expert Rev. Precis. Med. 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Agents Chemother"},{"key":"2021070818434758000_R54","article-title":"Morphological cell profiling of SARS-CoV-2 infection identifies drug repurposing candidates for COVID-19","author":"Mirabelli","year":"2020","journal-title":"bioRxiv"},{"key":"2021070818434758000_R55","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1038\/s41586-020-2577-1","article-title":"Discovery of SARS-CoV-2 antiviral drugs through large-scale compound repurposing","volume":"586","author":"Riva","year":"2020","journal-title":"Nature"},{"key":"2021070818434758000_R56","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-020-70143-6","article-title":"In vitro screening of a FDA approved chemical library reveals potential inhibitors of SARS-CoV-2 replication","volume":"10","author":"Touret","year":"2020","journal-title":"Sci. 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