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In silico prediction of ARB resistance: A first step in creating personalized ARB therapy

Angiotensin II type 1 receptor (AT(1)R) blockers (ARBs) are among the most prescribed drugs. However, ARB effectiveness varies widely, which may be due to non-synonymous single nucleotide polymorphisms (nsSNPs) within the AT(1)R gene. The AT(1)R coding sequence contains over 100 nsSNPs; therefore, t...

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Autores principales: Anderson, Shane D., Tabassum, Asna, Yeon, Jae Kyung, Sharma, Garima, Santos, Priscilla, Soong, Tik Hang, Thu, Yin Win, Nies, Isaac, Kurita, Tomomi, Chandler, Andrew, Alsamarah, Abdelaziz, Kanassatega, Rhye-Samuel, Luo, Yun L., Botello-Smith, Wesley M., Andresen, Bradley T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725353/
https://www.ncbi.nlm.nih.gov/pubmed/33237899
http://dx.doi.org/10.1371/journal.pcbi.1007719
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author Anderson, Shane D.
Tabassum, Asna
Yeon, Jae Kyung
Sharma, Garima
Santos, Priscilla
Soong, Tik Hang
Thu, Yin Win
Nies, Isaac
Kurita, Tomomi
Chandler, Andrew
Alsamarah, Abdelaziz
Kanassatega, Rhye-Samuel
Luo, Yun L.
Botello-Smith, Wesley M.
Andresen, Bradley T.
author_facet Anderson, Shane D.
Tabassum, Asna
Yeon, Jae Kyung
Sharma, Garima
Santos, Priscilla
Soong, Tik Hang
Thu, Yin Win
Nies, Isaac
Kurita, Tomomi
Chandler, Andrew
Alsamarah, Abdelaziz
Kanassatega, Rhye-Samuel
Luo, Yun L.
Botello-Smith, Wesley M.
Andresen, Bradley T.
author_sort Anderson, Shane D.
collection PubMed
description Angiotensin II type 1 receptor (AT(1)R) blockers (ARBs) are among the most prescribed drugs. However, ARB effectiveness varies widely, which may be due to non-synonymous single nucleotide polymorphisms (nsSNPs) within the AT(1)R gene. The AT(1)R coding sequence contains over 100 nsSNPs; therefore, this study embarked on determining which nsSNPs may abrogate the binding of selective ARBs. The crystal structure of olmesartan-bound human AT(1)R (PDB:4ZUD) served as a template to create an inactive apo-AT(1)R via molecular dynamics simulation (n = 3). All simulations resulted in a water accessible ligand-binding pocket that lacked sodium ions. The model remained inactive displaying little movement in the receptor core; however, helix 8 showed considerable flexibility. A single frame representing the average stable AT(1)R was used as a template to dock Olmesartan via AutoDock 4.2, MOE, and AutoDock Vina to obtain predicted binding poses and mean Boltzmann weighted average affinity. The docking results did not match the known pose and affinity of Olmesartan. Thus, an optimization protocol was initiated using AutoDock 4.2 that provided more accurate poses and affinity for Olmesartan (n = 6). Atomic models of 103 of the known human AT(1)R polymorphisms were constructed using the molecular dynamics equilibrated apo-AT(1)R. Each of the eight ARBs was then docked, using ARB-optimized parameters, to each polymorphic AT(1)R (n = 6). Although each nsSNP has a negligible effect on the global AT(1)R structure, most nsSNPs drastically alter a sub-set of ARBs affinity to the AT(1)R. Alterations within N298 –L314 strongly effected predicted ARB affinity, which aligns with early mutagenesis studies. The current study demonstrates the potential of utilizing in silico approaches towards personalized ARB therapy. The results presented here will guide further biochemical studies and refinement of the model to increase the accuracy of the prediction of ARB resistance in order to increase overall ARB effectiveness.
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spelling pubmed-77253532020-12-16 In silico prediction of ARB resistance: A first step in creating personalized ARB therapy Anderson, Shane D. Tabassum, Asna Yeon, Jae Kyung Sharma, Garima Santos, Priscilla Soong, Tik Hang Thu, Yin Win Nies, Isaac Kurita, Tomomi Chandler, Andrew Alsamarah, Abdelaziz Kanassatega, Rhye-Samuel Luo, Yun L. Botello-Smith, Wesley M. Andresen, Bradley T. PLoS Comput Biol Research Article Angiotensin II type 1 receptor (AT(1)R) blockers (ARBs) are among the most prescribed drugs. However, ARB effectiveness varies widely, which may be due to non-synonymous single nucleotide polymorphisms (nsSNPs) within the AT(1)R gene. The AT(1)R coding sequence contains over 100 nsSNPs; therefore, this study embarked on determining which nsSNPs may abrogate the binding of selective ARBs. The crystal structure of olmesartan-bound human AT(1)R (PDB:4ZUD) served as a template to create an inactive apo-AT(1)R via molecular dynamics simulation (n = 3). All simulations resulted in a water accessible ligand-binding pocket that lacked sodium ions. The model remained inactive displaying little movement in the receptor core; however, helix 8 showed considerable flexibility. A single frame representing the average stable AT(1)R was used as a template to dock Olmesartan via AutoDock 4.2, MOE, and AutoDock Vina to obtain predicted binding poses and mean Boltzmann weighted average affinity. The docking results did not match the known pose and affinity of Olmesartan. Thus, an optimization protocol was initiated using AutoDock 4.2 that provided more accurate poses and affinity for Olmesartan (n = 6). Atomic models of 103 of the known human AT(1)R polymorphisms were constructed using the molecular dynamics equilibrated apo-AT(1)R. Each of the eight ARBs was then docked, using ARB-optimized parameters, to each polymorphic AT(1)R (n = 6). Although each nsSNP has a negligible effect on the global AT(1)R structure, most nsSNPs drastically alter a sub-set of ARBs affinity to the AT(1)R. Alterations within N298 –L314 strongly effected predicted ARB affinity, which aligns with early mutagenesis studies. The current study demonstrates the potential of utilizing in silico approaches towards personalized ARB therapy. The results presented here will guide further biochemical studies and refinement of the model to increase the accuracy of the prediction of ARB resistance in order to increase overall ARB effectiveness. Public Library of Science 2020-11-25 /pmc/articles/PMC7725353/ /pubmed/33237899 http://dx.doi.org/10.1371/journal.pcbi.1007719 Text en © 2020 Anderson et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Anderson, Shane D.
Tabassum, Asna
Yeon, Jae Kyung
Sharma, Garima
Santos, Priscilla
Soong, Tik Hang
Thu, Yin Win
Nies, Isaac
Kurita, Tomomi
Chandler, Andrew
Alsamarah, Abdelaziz
Kanassatega, Rhye-Samuel
Luo, Yun L.
Botello-Smith, Wesley M.
Andresen, Bradley T.
In silico prediction of ARB resistance: A first step in creating personalized ARB therapy
title In silico prediction of ARB resistance: A first step in creating personalized ARB therapy
title_full In silico prediction of ARB resistance: A first step in creating personalized ARB therapy
title_fullStr In silico prediction of ARB resistance: A first step in creating personalized ARB therapy
title_full_unstemmed In silico prediction of ARB resistance: A first step in creating personalized ARB therapy
title_short In silico prediction of ARB resistance: A first step in creating personalized ARB therapy
title_sort in silico prediction of arb resistance: a first step in creating personalized arb therapy
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725353/
https://www.ncbi.nlm.nih.gov/pubmed/33237899
http://dx.doi.org/10.1371/journal.pcbi.1007719
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