Exploration of virtual candidates for human HMG-CoA reductase inhibitors using pharmacophore modeling and molecular dynamics simulations.

3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) is a rate-controlling enzyme in the mevalonate pathway which involved in biosynthesis of cholesterol and other isoprenoids. This enzyme catalyzes the conversion of HMG-CoA to mevalonate and is regarded as a drug target to treat hypercholesterole...

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Autores principales:	Minky Son, Ayoung Baek, Sugunadevi Sakkiah, Chanin Park, Shalini John, Keun Woo Lee
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/51fe6cef964249ec9dafd72edd9f96b7
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spelling	oai:doaj.org-article:51fe6cef964249ec9dafd72edd9f96b72021-11-18T08:39:55ZExploration of virtual candidates for human HMG-CoA reductase inhibitors using pharmacophore modeling and molecular dynamics simulations.1932-620310.1371/journal.pone.0083496https://doaj.org/article/51fe6cef964249ec9dafd72edd9f96b72013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24386216/?tool=EBIhttps://doaj.org/toc/1932-62033-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) is a rate-controlling enzyme in the mevalonate pathway which involved in biosynthesis of cholesterol and other isoprenoids. This enzyme catalyzes the conversion of HMG-CoA to mevalonate and is regarded as a drug target to treat hypercholesterolemia. In this study, ten qualitative pharmacophore models were generated based on chemical features in active inhibitors of HMGR. The generated models were validated using a test set. In a validation process, the best hypothesis was selected based on the statistical parameters and used for virtual screening of chemical databases to find novel lead candidates. The screened compounds were sorted by applying drug-like properties. The compounds that satisfied all drug-like properties were used for molecular docking study to identify their binding conformations at active site of HMGR. The final hit compounds were selected based on docking score and binding orientation. The HMGR structures in complex with the hit compounds were subjected to 10 ns molecular dynamics simulations to refine the binding orientation as well as to check the stability of the hits. After simulation, binding modes including hydrogen bonding patterns and molecular interactions with the active site residues were analyzed. In conclusion, four hit compounds with new structural scaffold were suggested as novel and potent HMGR inhibitors.Minky SonAyoung BaekSugunadevi SakkiahChanin ParkShalini JohnKeun Woo LeePublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 12, p e83496 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Minky Son Ayoung Baek Sugunadevi Sakkiah Chanin Park Shalini John Keun Woo Lee Exploration of virtual candidates for human HMG-CoA reductase inhibitors using pharmacophore modeling and molecular dynamics simulations.
description	3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) is a rate-controlling enzyme in the mevalonate pathway which involved in biosynthesis of cholesterol and other isoprenoids. This enzyme catalyzes the conversion of HMG-CoA to mevalonate and is regarded as a drug target to treat hypercholesterolemia. In this study, ten qualitative pharmacophore models were generated based on chemical features in active inhibitors of HMGR. The generated models were validated using a test set. In a validation process, the best hypothesis was selected based on the statistical parameters and used for virtual screening of chemical databases to find novel lead candidates. The screened compounds were sorted by applying drug-like properties. The compounds that satisfied all drug-like properties were used for molecular docking study to identify their binding conformations at active site of HMGR. The final hit compounds were selected based on docking score and binding orientation. The HMGR structures in complex with the hit compounds were subjected to 10 ns molecular dynamics simulations to refine the binding orientation as well as to check the stability of the hits. After simulation, binding modes including hydrogen bonding patterns and molecular interactions with the active site residues were analyzed. In conclusion, four hit compounds with new structural scaffold were suggested as novel and potent HMGR inhibitors.
format	article
author	Minky Son Ayoung Baek Sugunadevi Sakkiah Chanin Park Shalini John Keun Woo Lee
author_facet	Minky Son Ayoung Baek Sugunadevi Sakkiah Chanin Park Shalini John Keun Woo Lee
author_sort	Minky Son
title	Exploration of virtual candidates for human HMG-CoA reductase inhibitors using pharmacophore modeling and molecular dynamics simulations.
title_short	Exploration of virtual candidates for human HMG-CoA reductase inhibitors using pharmacophore modeling and molecular dynamics simulations.
title_full	Exploration of virtual candidates for human HMG-CoA reductase inhibitors using pharmacophore modeling and molecular dynamics simulations.
title_fullStr	Exploration of virtual candidates for human HMG-CoA reductase inhibitors using pharmacophore modeling and molecular dynamics simulations.
title_full_unstemmed	Exploration of virtual candidates for human HMG-CoA reductase inhibitors using pharmacophore modeling and molecular dynamics simulations.
title_sort	exploration of virtual candidates for human hmg-coa reductase inhibitors using pharmacophore modeling and molecular dynamics simulations.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/51fe6cef964249ec9dafd72edd9f96b7
work_keys_str_mv	AT minkyson explorationofvirtualcandidatesforhumanhmgcoareductaseinhibitorsusingpharmacophoremodelingandmoleculardynamicssimulations AT ayoungbaek explorationofvirtualcandidatesforhumanhmgcoareductaseinhibitorsusingpharmacophoremodelingandmoleculardynamicssimulations AT sugunadevisakkiah explorationofvirtualcandidatesforhumanhmgcoareductaseinhibitorsusingpharmacophoremodelingandmoleculardynamicssimulations AT chaninpark explorationofvirtualcandidatesforhumanhmgcoareductaseinhibitorsusingpharmacophoremodelingandmoleculardynamicssimulations AT shalinijohn explorationofvirtualcandidatesforhumanhmgcoareductaseinhibitorsusingpharmacophoremodelingandmoleculardynamicssimulations AT keunwoolee explorationofvirtualcandidatesforhumanhmgcoareductaseinhibitorsusingpharmacophoremodelingandmoleculardynamicssimulations
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Exploration of virtual candidates for human HMG-CoA reductase inhibitors using pharmacophore modeling and molecular dynamics simulations.

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