A QSAR Study of HIV Protease Inhibitors Using Computational Descriptors to Prediction of pki of Cycle Derivatives of Urea

Preventing and reducing the spread of HIV (HIV) has always been a concern in medical science. One of the most common ways to control the virus is using enzyme-blocking drugs. In this study, we attempted to predict the biological activity (PKi) of organic urea derivatives in protease inhibitor compou...

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Main Authors:	Zakiyeh Bayat, Samaneh Mohamad Ebrahimzadeh Sepasgozar
Format:	Article
Language:	fas
Published:	Alborz University of Medical Sciencs 2020-02-01
Series:	Bihdād
Subjects:	protease inhibitor qsar pki hiv computational
Online Access:	http://aums.abzums.ac.ir/article-1-1059-en.html

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spelling	doaj-0cd2ddb5540c4a7f85b361da72c700ef2020-11-25T03:00:27ZfasAlborz University of Medical SciencsBihdād1735-66792020-02-01914959A QSAR Study of HIV Protease Inhibitors Using Computational Descriptors to Prediction of pki of Cycle Derivatives of UreaZakiyeh Bayat0Samaneh Mohamad Ebrahimzadeh Sepasgozar1 Department of Chemistry , Quchan Branch, Islamic Azad University, Quchan, Iran Department of Chemistry , Quchan Branch, Islamic Azad University, Quchan, Iran Preventing and reducing the spread of HIV (HIV) has always been a concern in medical science. One of the most common ways to control the virus is using enzyme-blocking drugs. In this study, we attempted to predict the biological activity (PKi) of organic urea derivatives in protease inhibitor compounds using molecular modeling using QSAR (Quantitative Structure Activity Relation), which is the basis of quantitative study of the structure between And there is activity. Models were presented. In this study, the chemical structure of 41 compounds was optimized by Gaussian 09 software and other properties (descriptors) were obtained using software. The level used in B3LYP calculations and ground state series was 6-31G *. Validation tests were then performed on the obtained models. The results of the statistical data were acceptable. Given the effective variables in the models, it predicts biological activity and invokes appropriate drug design.http://aums.abzums.ac.ir/article-1-1059-en.htmlprotease inhibitorqsarpkihivcomputational
collection	DOAJ
language	fas
format	Article
sources	DOAJ
author	Zakiyeh Bayat Samaneh Mohamad Ebrahimzadeh Sepasgozar
spellingShingle	Zakiyeh Bayat Samaneh Mohamad Ebrahimzadeh Sepasgozar A QSAR Study of HIV Protease Inhibitors Using Computational Descriptors to Prediction of pki of Cycle Derivatives of Urea Bihdād protease inhibitor qsar pki hiv computational
author_facet	Zakiyeh Bayat Samaneh Mohamad Ebrahimzadeh Sepasgozar
author_sort	Zakiyeh Bayat
title	A QSAR Study of HIV Protease Inhibitors Using Computational Descriptors to Prediction of pki of Cycle Derivatives of Urea
title_short	A QSAR Study of HIV Protease Inhibitors Using Computational Descriptors to Prediction of pki of Cycle Derivatives of Urea
title_full	A QSAR Study of HIV Protease Inhibitors Using Computational Descriptors to Prediction of pki of Cycle Derivatives of Urea
title_fullStr	A QSAR Study of HIV Protease Inhibitors Using Computational Descriptors to Prediction of pki of Cycle Derivatives of Urea
title_full_unstemmed	A QSAR Study of HIV Protease Inhibitors Using Computational Descriptors to Prediction of pki of Cycle Derivatives of Urea
title_sort	qsar study of hiv protease inhibitors using computational descriptors to prediction of pki of cycle derivatives of urea
publisher	Alborz University of Medical Sciencs
series	Bihdād
issn	1735-6679
publishDate	2020-02-01
description	Preventing and reducing the spread of HIV (HIV) has always been a concern in medical science. One of the most common ways to control the virus is using enzyme-blocking drugs. In this study, we attempted to predict the biological activity (PKi) of organic urea derivatives in protease inhibitor compounds using molecular modeling using QSAR (Quantitative Structure Activity Relation), which is the basis of quantitative study of the structure between And there is activity. Models were presented. In this study, the chemical structure of 41 compounds was optimized by Gaussian 09 software and other properties (descriptors) were obtained using software. The level used in B3LYP calculations and ground state series was 6-31G *. Validation tests were then performed on the obtained models. The results of the statistical data were acceptable. Given the effective variables in the models, it predicts biological activity and invokes appropriate drug design.
topic	protease inhibitor qsar pki hiv computational
url	http://aums.abzums.ac.ir/article-1-1059-en.html
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A QSAR Study of HIV Protease Inhibitors Using Computational Descriptors to Prediction of pki of Cycle Derivatives of Urea

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