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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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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). |
format | Online Article Text |
id | pubmed-7856476 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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