In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery

Detalhes bibliográficos
Autor(a) principal: Souza Neto, Lauro Ribeiro de
Data de Publicação: 2020
Outros Autores: Moreira Filho, José Teófilo, Neves, Bruno Junior, Maidana, Rocío Lucía Beatriz Riveros, Guimarães, Ana Carolina Ramos, Furnham, Nicholas, Andrade, Carolina Horta, Silva, Floriano Paes
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da FIOCRUZ (ARCA)
Texto Completo: https://www.arca.fiocruz.br/handle/icict/42426
Resumo: Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Bioquímica Experimental e Computacional de Fármacos. Rio de Janeiro, RJ, Brasil..
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spelling Souza Neto, Lauro Ribeiro deMoreira Filho, José TeófiloNeves, Bruno JuniorMaidana, Rocío Lucía Beatriz RiverosGuimarães, Ana Carolina RamosFurnham, NicholasAndrade, Carolina HortaSilva, Floriano Paes2020-07-28T18:28:16Z2020-07-28T18:28:16Z2020SOUZA NETO, Lauro Ribeiro de et al. In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery. Frontiers in Chemistry, v.8, Article 93, 18p, Feb. 2020.2296-2646https://www.arca.fiocruz.br/handle/icict/4242610.3389/fchem.2020.00093engFrontiers MediaFragmentosDescoberta de drogasDescoberta de chumboEm métodos silicoAprendizado de máquinaOtimizaçãoFragment-basedDrug discoveryLead discoveryin silico methodsMachine learningDe novo designOptimizationHot spot analysisIn silico Strategies to Support Fragment-to-Lead Optimization in Drug Discoveryinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleFundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Bioquímica Experimental e Computacional de Fármacos. Rio de Janeiro, RJ, Brasil..Universidade Federal de Goiás. Faculdade de Farmácia. LabMol-Laboratório de Modelagem Molecular e Design de Drogas. Goiânia, GO, Brasil.Universidade Federal de Goiás. Faculdade de Farmácia. LabMol-Laboratório de Modelagem Molecular e Design de Drogas. Goiânia, GO, Brasil / Centro Universitário de Anápolis. Laboratory of Cheminformatics. Anápolis, GO, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Bioquímica Experimental e Computacional de Fármacos. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Genômica Funcional e Bioinformática. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Genômica Funcional e Bioinformática. Rio de Janeiro, RJ, Brasil.London School of Hygiene and Tropical Medicine. Department of Infection Biology. London, United Kingdom.Universidade Federal de Goiás. Faculdade de Farmácia. LabMol-Laboratório de Modelagem Molecular e Design de Drogas. Goiânia, GO, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Bioquímica Experimental e Computacional de Fármacos. Rio de Janeiro, RJ, Brasil..Fragment-based drug (or lead) discovery (FBDD or FBLD) has developed in the last two decades to become a successful key technology in the pharmaceutical industry for early stage drug discovery and development. The FBDD strategy consists of screening low molecular weight compounds against macromolecular targets (usually proteins) of clinical relevance. These small molecular fragments can bind at one or more sites on the target and act as starting points for the development of lead compounds. In developing the fragments attractive features that can translate into compounds with favorable physical, pharmacokinetics and toxicity (ADMET-absorption, distribution, metabolism, excretion, and toxicity) properties can be integrated. Structure-enabled fragment screening campaigns use a combination of screening by a range of biophysical techniques, such as differential scanning fluorimetry, surface plasmon resonance, and thermophoresis, followed by structural characterization of fragment binding using NMR or X-ray crystallography. Structural characterization is also used in subsequent analysis for growing fragments of selected screening hits. The latest iteration of the FBDD workflow employs a high-throughput methodology of massively parallel screening by X-ray crystallography of individually soaked fragments. In this review we will outline the FBDD strategies and explore a variety of in silico approaches to support the follow-up fragment-to-lead optimization of either: growing, linking, and merging. These fragment expansion strategies include hot spot analysis, druggability prediction, SAR (structure-activity relationships) by catalog methods, application of machine learning/deep learning models for virtual screening and several de novo design methods for proposing synthesizable new compounds. Finally, we will highlight recent case studies in fragment-based drug discovery where in silico methods have successfully contributed to the development of lead compounds.info:eu-repo/semantics/openAccessreponame:Repositório Institucional da FIOCRUZ (ARCA)instname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZLICENSElicense.txtlicense.txttext/plain; charset=utf-82991https://www.arca.fiocruz.br/bitstream/icict/42426/1/license.txt5a560609d32a3863062d77ff32785d58MD51ORIGINALFlorianoPJR_LuciaR_Maidana_etal_IOC_2020.pdfFlorianoPJR_LuciaR_Maidana_etal_IOC_2020.pdfapplication/pdf1683853https://www.arca.fiocruz.br/bitstream/icict/42426/2/FlorianoPJR_LuciaR_Maidana_etal_IOC_2020.pdf83432d6fdf289749cc3ff6762f2a8a51MD52TEXTFlorianoPJR_LuciaR_Maidana_etal_IOC_2020.pdf.txtFlorianoPJR_LuciaR_Maidana_etal_IOC_2020.pdf.txtExtracted 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dc.title.pt_BR.fl_str_mv In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery
title In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery
spellingShingle In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery
Souza Neto, Lauro Ribeiro de
Fragmentos
Descoberta de drogas
Descoberta de chumbo
Em métodos silico
Aprendizado de máquina
Otimização
Fragment-based
Drug discovery
Lead discovery
in silico methods
Machine learning
De novo design
Optimization
Hot spot analysis
title_short In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery
title_full In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery
title_fullStr In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery
title_full_unstemmed In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery
title_sort In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery
author Souza Neto, Lauro Ribeiro de
author_facet Souza Neto, Lauro Ribeiro de
Moreira Filho, José Teófilo
Neves, Bruno Junior
Maidana, Rocío Lucía Beatriz Riveros
Guimarães, Ana Carolina Ramos
Furnham, Nicholas
Andrade, Carolina Horta
Silva, Floriano Paes
author_role author
author2 Moreira Filho, José Teófilo
Neves, Bruno Junior
Maidana, Rocío Lucía Beatriz Riveros
Guimarães, Ana Carolina Ramos
Furnham, Nicholas
Andrade, Carolina Horta
Silva, Floriano Paes
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Souza Neto, Lauro Ribeiro de
Moreira Filho, José Teófilo
Neves, Bruno Junior
Maidana, Rocío Lucía Beatriz Riveros
Guimarães, Ana Carolina Ramos
Furnham, Nicholas
Andrade, Carolina Horta
Silva, Floriano Paes
dc.subject.other.pt_BR.fl_str_mv Fragmentos
Descoberta de drogas
Descoberta de chumbo
Em métodos silico
Aprendizado de máquina
Otimização
topic Fragmentos
Descoberta de drogas
Descoberta de chumbo
Em métodos silico
Aprendizado de máquina
Otimização
Fragment-based
Drug discovery
Lead discovery
in silico methods
Machine learning
De novo design
Optimization
Hot spot analysis
dc.subject.en.pt_BR.fl_str_mv Fragment-based
Drug discovery
Lead discovery
in silico methods
Machine learning
De novo design
Optimization
Hot spot analysis
description Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Bioquímica Experimental e Computacional de Fármacos. Rio de Janeiro, RJ, Brasil..
publishDate 2020
dc.date.accessioned.fl_str_mv 2020-07-28T18:28:16Z
dc.date.available.fl_str_mv 2020-07-28T18:28:16Z
dc.date.issued.fl_str_mv 2020
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.citation.fl_str_mv SOUZA NETO, Lauro Ribeiro de et al. In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery. Frontiers in Chemistry, v.8, Article 93, 18p, Feb. 2020.
dc.identifier.uri.fl_str_mv https://www.arca.fiocruz.br/handle/icict/42426
dc.identifier.issn.pt_BR.fl_str_mv 2296-2646
dc.identifier.doi.none.fl_str_mv 10.3389/fchem.2020.00093
identifier_str_mv SOUZA NETO, Lauro Ribeiro de et al. In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery. Frontiers in Chemistry, v.8, Article 93, 18p, Feb. 2020.
2296-2646
10.3389/fchem.2020.00093
url https://www.arca.fiocruz.br/handle/icict/42426
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Frontiers Media
publisher.none.fl_str_mv Frontiers Media
dc.source.none.fl_str_mv reponame:Repositório Institucional da FIOCRUZ (ARCA)
instname:Fundação Oswaldo Cruz (FIOCRUZ)
instacron:FIOCRUZ
instname_str Fundação Oswaldo Cruz (FIOCRUZ)
instacron_str FIOCRUZ
institution FIOCRUZ
reponame_str Repositório Institucional da FIOCRUZ (ARCA)
collection Repositório Institucional da FIOCRUZ (ARCA)
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