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Protocol for hit-to-lead optimization of compounds by auto in silico ligand directing evolution (AILDE) approach

Hit-to-lead (H2L) optimization is crucial for drug design, which has become an increasing concern in medicinal chemistry. A virtual screening strategy of auto in silico ligand directing evolution (AILDE) has been developed to yield promising lead compounds rapidly and efficiently. The protocol inclu...

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Detalles Bibliográficos
Autores principales: Mei, Longcan, Wu, Fengxu, Hao, Gefei, Yang, Guangfu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7856476/
https://www.ncbi.nlm.nih.gov/pubmed/33554146
http://dx.doi.org/10.1016/j.xpro.2021.100312
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author Mei, Longcan
Wu, Fengxu
Hao, Gefei
Yang, Guangfu
author_facet Mei, Longcan
Wu, Fengxu
Hao, Gefei
Yang, Guangfu
author_sort Mei, Longcan
collection PubMed
description Hit-to-lead (H2L) optimization is crucial for drug design, which has become an increasing concern in medicinal chemistry. A virtual screening strategy of auto in silico ligand directing evolution (AILDE) has been developed to yield promising lead compounds rapidly and efficiently. The protocol includes instructions for fragment compound library construction, conformational sampling by molecular dynamics simulation, ligand modification by fragment growing, as well as the binding free energy prediction. For complete details on the use and execution of this protocol, please refer to Wu et al. (2020).
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spelling pubmed-78564762021-02-05 Protocol for hit-to-lead optimization of compounds by auto in silico ligand directing evolution (AILDE) approach Mei, Longcan Wu, Fengxu Hao, Gefei Yang, Guangfu STAR Protoc Protocol Hit-to-lead (H2L) optimization is crucial for drug design, which has become an increasing concern in medicinal chemistry. A virtual screening strategy of auto in silico ligand directing evolution (AILDE) has been developed to yield promising lead compounds rapidly and efficiently. The protocol includes instructions for fragment compound library construction, conformational sampling by molecular dynamics simulation, ligand modification by fragment growing, as well as the binding free energy prediction. For complete details on the use and execution of this protocol, please refer to Wu et al. (2020). Elsevier 2021-02-01 /pmc/articles/PMC7856476/ /pubmed/33554146 http://dx.doi.org/10.1016/j.xpro.2021.100312 Text en © 2021 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Mei, Longcan
Wu, Fengxu
Hao, Gefei
Yang, Guangfu
Protocol for hit-to-lead optimization of compounds by auto in silico ligand directing evolution (AILDE) approach
title Protocol for hit-to-lead optimization of compounds by auto in silico ligand directing evolution (AILDE) approach
title_full Protocol for hit-to-lead optimization of compounds by auto in silico ligand directing evolution (AILDE) approach
title_fullStr Protocol for hit-to-lead optimization of compounds by auto in silico ligand directing evolution (AILDE) approach
title_full_unstemmed Protocol for hit-to-lead optimization of compounds by auto in silico ligand directing evolution (AILDE) approach
title_short Protocol for hit-to-lead optimization of compounds by auto in silico ligand directing evolution (AILDE) approach
title_sort protocol for hit-to-lead optimization of compounds by auto in silico ligand directing evolution (ailde) approach
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7856476/
https://www.ncbi.nlm.nih.gov/pubmed/33554146
http://dx.doi.org/10.1016/j.xpro.2021.100312
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