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dc.contributor.author
Cavasotto, Claudio Norberto
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dc.contributor.author
Aucar, María Gabriela
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dc.date.available
2022-08-02T13:20:30Z
dc.date.issued
2020-04
dc.identifier.citation
Cavasotto, Claudio Norberto; Aucar, María Gabriela; High-Throughput Docking Using Quantum Mechanical Scoring; Frontiers Media; Frontiers in Chemistry; 8; 4-2020; 1-10
dc.identifier.issn
2296-2646
dc.identifier.uri
http://hdl.handle.net/11336/163869
dc.description.abstract
Today high-throughput docking is one of the most commonly used computational tools in drug lead discovery. While there has been an impressive methodological improvement in docking accuracy, docking scoring still remains an open challenge. Most docking programs are rooted in classical molecular mechanics. However, to better characterize protein-ligand interactions, the use of a more accurate quantum mechanical (QM) description would be necessary. In this work, we introduce a QM-based docking scoring function for high-throughput docking and evaluate it on 10 protein systems belonging to diverse protein families, and with different binding site characteristics. Outstanding results were obtained, with our QM scoring function displaying much higher enrichment (screening power) than a traditional docking method. It is acknowledged that developments in quantum mechanics theory, algorithms and computer hardware throughout the upcoming years will allow semi-empirical (or low-cost) quantum mechanical methods to slowly replace force-field calculations. It is thus urgently needed to develop and validate novel quantum mechanical-based scoring functions for high-throughput docking toward more accurate methods for the identification and optimization of modulators of pharmaceutically relevant targets.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Frontiers Media
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dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/
dc.subject
HIGH-THROUGHPUT DOCKING
dc.subject
MOLECULAR DOCKING
dc.subject
QUANTUM MECHANICS
dc.subject
SEMI-EMPIRICAL METHODS
dc.subject
STRUCTURE-BASED DRUG DESIGN
dc.subject.classification
Otras Ciencias Químicas
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dc.subject.classification
Ciencias Químicas
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dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
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dc.title
High-Throughput Docking Using Quantum Mechanical Scoring
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2021-09-07T15:23:08Z
dc.journal.volume
8
dc.journal.pagination
1-10
dc.journal.pais
Suiza
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dc.description.fil
Fil: Cavasotto, Claudio Norberto. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentina
dc.description.fil
Fil: Aucar, María Gabriela. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentina
dc.journal.title
Frontiers in Chemistry
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.3389/fchem.2020.00246
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