The effect of protein mutations on drug binding suggests ensuing personalised drug selection

Abstract The advent of personalised medicine promises a deeper understanding of mechanisms and therefore therapies. However, the connection between genomic sequences and clinical treatments is often unclear. We studied 50 breast cancer patients belonging to a population-cohort in the state of Qatar....

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Autores principales:	Shunzhou Wan, Deepak Kumar, Valentin Ilyin, Ussama Al Homsi, Gulab Sher, Alexander Knuth, Peter V. Coveney
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2a363102d41c4c2d90161fca91a7f1ec
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spelling	oai:doaj.org-article:2a363102d41c4c2d90161fca91a7f1ec2021-12-02T16:32:02ZThe effect of protein mutations on drug binding suggests ensuing personalised drug selection10.1038/s41598-021-92785-w2045-2322https://doaj.org/article/2a363102d41c4c2d90161fca91a7f1ec2021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-92785-whttps://doaj.org/toc/2045-2322Abstract The advent of personalised medicine promises a deeper understanding of mechanisms and therefore therapies. However, the connection between genomic sequences and clinical treatments is often unclear. We studied 50 breast cancer patients belonging to a population-cohort in the state of Qatar. From Sanger sequencing, we identified several new deleterious mutations in the estrogen receptor 1 gene (ESR1). The effect of these mutations on drug treatment in the protein target encoded by ESR1, namely the estrogen receptor, was achieved via rapid and accurate protein–ligand binding affinity interaction studies which were performed for the selected drugs and the natural ligand estrogen. Four nonsynonymous mutations in the ligand-binding domain were subjected to molecular dynamics simulation using absolute and relative binding free energy methods, leading to the ranking of the efficacy of six selected drugs for patients with the mutations. Our study shows that a personalised clinical decision system can be created by integrating an individual patient’s genomic data at the molecular level within a computational pipeline which ranks the efficacy of binding of particular drugs to variant proteins.Shunzhou WanDeepak KumarValentin IlyinUssama Al HomsiGulab SherAlexander KnuthPeter V. CoveneyNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Shunzhou Wan Deepak Kumar Valentin Ilyin Ussama Al Homsi Gulab Sher Alexander Knuth Peter V. Coveney The effect of protein mutations on drug binding suggests ensuing personalised drug selection
description	Abstract The advent of personalised medicine promises a deeper understanding of mechanisms and therefore therapies. However, the connection between genomic sequences and clinical treatments is often unclear. We studied 50 breast cancer patients belonging to a population-cohort in the state of Qatar. From Sanger sequencing, we identified several new deleterious mutations in the estrogen receptor 1 gene (ESR1). The effect of these mutations on drug treatment in the protein target encoded by ESR1, namely the estrogen receptor, was achieved via rapid and accurate protein–ligand binding affinity interaction studies which were performed for the selected drugs and the natural ligand estrogen. Four nonsynonymous mutations in the ligand-binding domain were subjected to molecular dynamics simulation using absolute and relative binding free energy methods, leading to the ranking of the efficacy of six selected drugs for patients with the mutations. Our study shows that a personalised clinical decision system can be created by integrating an individual patient’s genomic data at the molecular level within a computational pipeline which ranks the efficacy of binding of particular drugs to variant proteins.
format	article
author	Shunzhou Wan Deepak Kumar Valentin Ilyin Ussama Al Homsi Gulab Sher Alexander Knuth Peter V. Coveney
author_facet	Shunzhou Wan Deepak Kumar Valentin Ilyin Ussama Al Homsi Gulab Sher Alexander Knuth Peter V. Coveney
author_sort	Shunzhou Wan
title	The effect of protein mutations on drug binding suggests ensuing personalised drug selection
title_short	The effect of protein mutations on drug binding suggests ensuing personalised drug selection
title_full	The effect of protein mutations on drug binding suggests ensuing personalised drug selection
title_fullStr	The effect of protein mutations on drug binding suggests ensuing personalised drug selection
title_full_unstemmed	The effect of protein mutations on drug binding suggests ensuing personalised drug selection
title_sort	effect of protein mutations on drug binding suggests ensuing personalised drug selection
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/2a363102d41c4c2d90161fca91a7f1ec
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The effect of protein mutations on drug binding suggests ensuing personalised drug selection

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