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How Good is Jarzynski’s Equality for Computer-Aided Drug Design?
[Image: see text] Accurate determination of the binding affinity of the ligand to the receptor remains a difficult problem in computer-aided drug design. Here, we study and compare the efficiency of Jarzynski’s equality (JE) combined with steered molecular dynamics and the linear interaction energy...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical
Society
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7590978/ https://www.ncbi.nlm.nih.gov/pubmed/32484689 http://dx.doi.org/10.1021/acs.jpcb.0c02009 |
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author | Ho, Kiet Truong, Duc Toan Li, Mai Suan |
author_facet | Ho, Kiet Truong, Duc Toan Li, Mai Suan |
author_sort | Ho, Kiet |
collection | PubMed |
description | [Image: see text] Accurate determination of the binding affinity of the ligand to the receptor remains a difficult problem in computer-aided drug design. Here, we study and compare the efficiency of Jarzynski’s equality (JE) combined with steered molecular dynamics and the linear interaction energy (LIE) method by assessing the binding affinity of 23 small compounds to six receptors, including β-lactamase, thrombin, factor Xa, HIV-1 protease (HIV), myeloid cell leukemia-1, and cyclin-dependent kinase 2 proteins. It was shown that Jarzynski’s nonequilibrium binding free energy ΔG(neq)(Jar) correlates with the available experimental data with the correlation levels R = 0.89, 0.86, 0.83, 0.80, 0.83, and 0.81 for six data sets, while for the binding free energy ΔG(LIE) obtained by the LIE method, we have R = 0.73, 0.80, 0.42, 0.23, 0.85, and 0.01. Therefore, JE is recommended to be used for ranking binding affinities as it provides accurate and robust results. In contrast, LIE is not as reliable as JE, and it should be used with caution, especially when it comes to new systems. |
format | Online Article Text |
id | pubmed-7590978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Chemical
Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-75909782020-10-28 How Good is Jarzynski’s Equality for Computer-Aided Drug Design? Ho, Kiet Truong, Duc Toan Li, Mai Suan J Phys Chem B [Image: see text] Accurate determination of the binding affinity of the ligand to the receptor remains a difficult problem in computer-aided drug design. Here, we study and compare the efficiency of Jarzynski’s equality (JE) combined with steered molecular dynamics and the linear interaction energy (LIE) method by assessing the binding affinity of 23 small compounds to six receptors, including β-lactamase, thrombin, factor Xa, HIV-1 protease (HIV), myeloid cell leukemia-1, and cyclin-dependent kinase 2 proteins. It was shown that Jarzynski’s nonequilibrium binding free energy ΔG(neq)(Jar) correlates with the available experimental data with the correlation levels R = 0.89, 0.86, 0.83, 0.80, 0.83, and 0.81 for six data sets, while for the binding free energy ΔG(LIE) obtained by the LIE method, we have R = 0.73, 0.80, 0.42, 0.23, 0.85, and 0.01. Therefore, JE is recommended to be used for ranking binding affinities as it provides accurate and robust results. In contrast, LIE is not as reliable as JE, and it should be used with caution, especially when it comes to new systems. American Chemical Society 2020-06-02 2020-07-02 /pmc/articles/PMC7590978/ /pubmed/32484689 http://dx.doi.org/10.1021/acs.jpcb.0c02009 Text en This is an open access article published under a Creative Commons Attribution (CC-BY) License (http://pubs.acs.org/page/policy/authorchoice_ccby_termsofuse.html) , which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited. |
spellingShingle | Ho, Kiet Truong, Duc Toan Li, Mai Suan How Good is Jarzynski’s Equality for Computer-Aided Drug Design? |
title | How Good is Jarzynski’s Equality for Computer-Aided
Drug Design? |
title_full | How Good is Jarzynski’s Equality for Computer-Aided
Drug Design? |
title_fullStr | How Good is Jarzynski’s Equality for Computer-Aided
Drug Design? |
title_full_unstemmed | How Good is Jarzynski’s Equality for Computer-Aided
Drug Design? |
title_short | How Good is Jarzynski’s Equality for Computer-Aided
Drug Design? |
title_sort | how good is jarzynski’s equality for computer-aided
drug design? |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7590978/ https://www.ncbi.nlm.nih.gov/pubmed/32484689 http://dx.doi.org/10.1021/acs.jpcb.0c02009 |
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