Quantum chemical approaches in structure-based virtual screening and lead optimization

Autores
Cavasotto, Claudio Norberto; Adler, Natalia Sol; Aucar, María Gabriela
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Today computational chemistry is a consolidated tool in drug lead discovery endeavors. Due to methodological developments and to the enormous advance in computer hardware, methods based on quantum mechanics (QM) have gained great attention in the last 10 years, and calculations on biomacromolecules are becoming increasingly explored, aiming to provide better accuracy in the description of protein-ligand interactions and the prediction of binding affinities. In principle, the QM formulation includes all contributions to the energy, accounting for terms usually missing in molecular mechanics force-fields, such as electronic polarization effects, metal coordination, and covalent binding; moreover, QM methods are systematically improvable, and provide a greater degree of transferability. In this mini-review we present recent applications of explicit QM-based methods in small-molecule docking and scoring, and in the calculation of binding free-energy in protein-ligand systems. Although the routine use of QM-based approaches in an industrial drug lead discovery setting remains a formidable challenging task, it is likely they will increasingly become active players within the drug discovery pipeline.
Fil: Cavasotto, Claudio Norberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina
Fil: Adler, Natalia Sol. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina
Fil: Aucar, María Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina
Materia
BINDING FREE ENERGY
DRUG LEAD OPTIMIZATION
MOLECULAR DOCKING
MOLECULAR DYNAMICS
QUANTUM MECHANICS
SEMI-EMPIRICAL METHODS
STRUCTURE-BASED DRUG DESIGN
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/91266

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network_name_str CONICET Digital (CONICET)
spelling Quantum chemical approaches in structure-based virtual screening and lead optimizationCavasotto, Claudio NorbertoAdler, Natalia SolAucar, María GabrielaBINDING FREE ENERGYDRUG LEAD OPTIMIZATIONMOLECULAR DOCKINGMOLECULAR DYNAMICSQUANTUM MECHANICSSEMI-EMPIRICAL METHODSSTRUCTURE-BASED DRUG DESIGNhttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1Today computational chemistry is a consolidated tool in drug lead discovery endeavors. Due to methodological developments and to the enormous advance in computer hardware, methods based on quantum mechanics (QM) have gained great attention in the last 10 years, and calculations on biomacromolecules are becoming increasingly explored, aiming to provide better accuracy in the description of protein-ligand interactions and the prediction of binding affinities. In principle, the QM formulation includes all contributions to the energy, accounting for terms usually missing in molecular mechanics force-fields, such as electronic polarization effects, metal coordination, and covalent binding; moreover, QM methods are systematically improvable, and provide a greater degree of transferability. In this mini-review we present recent applications of explicit QM-based methods in small-molecule docking and scoring, and in the calculation of binding free-energy in protein-ligand systems. Although the routine use of QM-based approaches in an industrial drug lead discovery setting remains a formidable challenging task, it is likely they will increasingly become active players within the drug discovery pipeline.Fil: Cavasotto, Claudio Norberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; ArgentinaFil: Adler, Natalia Sol. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; ArgentinaFil: Aucar, María Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; ArgentinaFrontiers Research Foundation2018-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/91266Cavasotto, Claudio Norberto; Adler, Natalia Sol; Aucar, María Gabriela; Quantum chemical approaches in structure-based virtual screening and lead optimization; Frontiers Research Foundation; Frontiers in Chemistry; 6; MAY; 5-2018; 1-72296-2646CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fchem.2018.00188/fullinfo:eu-repo/semantics/altIdentifier/doi/10.3389/fchem.2018.00188info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:01:58Zoai:ri.conicet.gov.ar:11336/91266instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 15:01:59.274CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Quantum chemical approaches in structure-based virtual screening and lead optimization
title Quantum chemical approaches in structure-based virtual screening and lead optimization
spellingShingle Quantum chemical approaches in structure-based virtual screening and lead optimization
Cavasotto, Claudio Norberto
BINDING FREE ENERGY
DRUG LEAD OPTIMIZATION
MOLECULAR DOCKING
MOLECULAR DYNAMICS
QUANTUM MECHANICS
SEMI-EMPIRICAL METHODS
STRUCTURE-BASED DRUG DESIGN
title_short Quantum chemical approaches in structure-based virtual screening and lead optimization
title_full Quantum chemical approaches in structure-based virtual screening and lead optimization
title_fullStr Quantum chemical approaches in structure-based virtual screening and lead optimization
title_full_unstemmed Quantum chemical approaches in structure-based virtual screening and lead optimization
title_sort Quantum chemical approaches in structure-based virtual screening and lead optimization
dc.creator.none.fl_str_mv Cavasotto, Claudio Norberto
Adler, Natalia Sol
Aucar, María Gabriela
author Cavasotto, Claudio Norberto
author_facet Cavasotto, Claudio Norberto
Adler, Natalia Sol
Aucar, María Gabriela
author_role author
author2 Adler, Natalia Sol
Aucar, María Gabriela
author2_role author
author
dc.subject.none.fl_str_mv BINDING FREE ENERGY
DRUG LEAD OPTIMIZATION
MOLECULAR DOCKING
MOLECULAR DYNAMICS
QUANTUM MECHANICS
SEMI-EMPIRICAL METHODS
STRUCTURE-BASED DRUG DESIGN
topic BINDING FREE ENERGY
DRUG LEAD OPTIMIZATION
MOLECULAR DOCKING
MOLECULAR DYNAMICS
QUANTUM MECHANICS
SEMI-EMPIRICAL METHODS
STRUCTURE-BASED DRUG DESIGN
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Today computational chemistry is a consolidated tool in drug lead discovery endeavors. Due to methodological developments and to the enormous advance in computer hardware, methods based on quantum mechanics (QM) have gained great attention in the last 10 years, and calculations on biomacromolecules are becoming increasingly explored, aiming to provide better accuracy in the description of protein-ligand interactions and the prediction of binding affinities. In principle, the QM formulation includes all contributions to the energy, accounting for terms usually missing in molecular mechanics force-fields, such as electronic polarization effects, metal coordination, and covalent binding; moreover, QM methods are systematically improvable, and provide a greater degree of transferability. In this mini-review we present recent applications of explicit QM-based methods in small-molecule docking and scoring, and in the calculation of binding free-energy in protein-ligand systems. Although the routine use of QM-based approaches in an industrial drug lead discovery setting remains a formidable challenging task, it is likely they will increasingly become active players within the drug discovery pipeline.
Fil: Cavasotto, Claudio Norberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina
Fil: Adler, Natalia Sol. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina
Fil: Aucar, María Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina
description Today computational chemistry is a consolidated tool in drug lead discovery endeavors. Due to methodological developments and to the enormous advance in computer hardware, methods based on quantum mechanics (QM) have gained great attention in the last 10 years, and calculations on biomacromolecules are becoming increasingly explored, aiming to provide better accuracy in the description of protein-ligand interactions and the prediction of binding affinities. In principle, the QM formulation includes all contributions to the energy, accounting for terms usually missing in molecular mechanics force-fields, such as electronic polarization effects, metal coordination, and covalent binding; moreover, QM methods are systematically improvable, and provide a greater degree of transferability. In this mini-review we present recent applications of explicit QM-based methods in small-molecule docking and scoring, and in the calculation of binding free-energy in protein-ligand systems. Although the routine use of QM-based approaches in an industrial drug lead discovery setting remains a formidable challenging task, it is likely they will increasingly become active players within the drug discovery pipeline.
publishDate 2018
dc.date.none.fl_str_mv 2018-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/91266
Cavasotto, Claudio Norberto; Adler, Natalia Sol; Aucar, María Gabriela; Quantum chemical approaches in structure-based virtual screening and lead optimization; Frontiers Research Foundation; Frontiers in Chemistry; 6; MAY; 5-2018; 1-7
2296-2646
CONICET Digital
CONICET
url http://hdl.handle.net/11336/91266
identifier_str_mv Cavasotto, Claudio Norberto; Adler, Natalia Sol; Aucar, María Gabriela; Quantum chemical approaches in structure-based virtual screening and lead optimization; Frontiers Research Foundation; Frontiers in Chemistry; 6; MAY; 5-2018; 1-7
2296-2646
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fchem.2018.00188/full
info:eu-repo/semantics/altIdentifier/doi/10.3389/fchem.2018.00188
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Frontiers Research Foundation
publisher.none.fl_str_mv Frontiers Research Foundation
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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