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Machine learning for target discovery in drug development

2020Journal article Restricted access
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dc.contributor.authorRodrigues, Tiago
dc.contributor.authorBernardes, Gonçalo J. L.
dc.date.accessioned2022-01-21T16:37:20Z
dc.date.available2022-01-21T16:37:20Z
dc.date.issued2020
dc.description© 2019 Elsevier Ltd. All rights reserved.pt_PT
dc.description.abstractThe discovery of macromolecular targets for bioactive agents is currently a bottleneck for the informed design of chemical probes and drug leads. Typically, activity profiling against genetically manipulated cell lines or chemical proteomics is pursued to shed light on their biology and deconvolute drug-target networks. By taking advantage of the ever-growing wealth of publicly available bioactivity data, learning algorithms now provide an attractive means to generate statistically motivated research hypotheses and thereby prioritize biochemical screens. Here, we highlight recent successes in machine intelligence for target identification and discuss challenges and opportunities for drug discovery.pt_PT
dc.description.sponsorshipT.R. is an Investigador Auxiliar supported by FCT Portugal (CEECIND/00887/2017). T.R. acknowledges the H2020 (TWINN-2017 ACORN, Grant 807281) and FCT / FEDER (02/SAICT/2017, Grant 28333) for funding. G.J.L.B. is a Royal Society University Research Fellow (URF∖R∖180019) and a FCT Investigator (IF/00624/2015).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationCurrent opinion in chemical biology, 56, 16-22pt_PT
dc.identifier.doi10.1016/j.cbpa.2019.10.003pt_PT
dc.identifier.eissn1879-0402
dc.identifier.issn1367-5931
dc.identifier.urihttp://hdl.handle.net/10451/50919
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationCEECIND/00887/2017pt_PT
dc.relationNanoparticle-Based Therapeutic Applications and Detection of Carbon Monoxide Releasing Molecules
dc.relation.publisherversionhttps://www.sciencedirect.com/journal/current-opinion-in-chemical-biologypt_PT
dc.subjectChemical probespt_PT
dc.subjectChemical proteomicspt_PT
dc.subjectDrug discoverypt_PT
dc.subjectMachine learningpt_PT
dc.subjectTarget identificationpt_PT
dc.titleMachine learning for target discovery in drug developmentpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleNanoparticle-Based Therapeutic Applications and Detection of Carbon Monoxide Releasing Molecules
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/807281/EU
oaire.citation.endPage22pt_PT
oaire.citation.startPage16pt_PT
oaire.citation.titleCurrent Opinion in Chemical Biologypt_PT
oaire.citation.volume56pt_PT
oaire.fundingStreamH2020
person.familyNameRodrigues
person.familyNameBernardes
person.givenNameTiago
person.givenNameGonçalo
person.identifier1357049
person.identifier.ciencia-id6219-8658-2307
person.identifier.orcid0000-0002-1581-5654
person.identifier.orcid0000-0001-6594-8917
person.identifier.scopus-author-id57226266154
person.identifier.scopus-author-id14046757500
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.nameEuropean Commission
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublicationd1a48067-77b1-4413-b1c7-602fb18c62c0
relation.isAuthorOfPublication.latestForDiscovery8c21143c-1085-42f7-aa23-c313a6a6bbc9
relation.isProjectOfPublication842e9afc-122e-4eb4-917a-cb387e924316
relation.isProjectOfPublication.latestForDiscovery842e9afc-122e-4eb4-917a-cb387e924316

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