QSAR study for anti-HIV-1 activities of HEPT derivatives using MLR and PLS

A QSAR study using Multiple Linear Regression (MLR) and a Partial Least Squares (PLS) methodology was performed for a series of 127 derivatives of 1-(2-hydroxy-ethoxy)methyl]-6-(phenylthio)-timine (HEPT), a potent inhibitor of the of the human immunodeficiency virus type 1, HIV-1 reverse transcr...

Full description

Bibliographic Details
Main Authors: Ivan Daniela, Crisan Luminita, Funar-Timofei Simona, Mracec Mircea
Format: Article
Language:English
Published: Serbian Chemical Society 2013-01-01
Series:Journal of the Serbian Chemical Society
Subjects:
Online Access:http://www.doiserbia.nb.rs/img/doi/0352-5139/2013/0352-51391200085I.pdf
_version_ 1818147137654882304
author Ivan Daniela
Crisan Luminita
Funar-Timofei Simona
Mracec Mircea
author_facet Ivan Daniela
Crisan Luminita
Funar-Timofei Simona
Mracec Mircea
author_sort Ivan Daniela
collection DOAJ
description A QSAR study using Multiple Linear Regression (MLR) and a Partial Least Squares (PLS) methodology was performed for a series of 127 derivatives of 1-(2-hydroxy-ethoxy)methyl]-6-(phenylthio)-timine (HEPT), a potent inhibitor of the of the human immunodeficiency virus type 1, HIV-1 reverse transcriptase (RT). To explore the relationship between a pool of HEPT derivative descriptors (as independent variables) and anti-HIV-1 activity expressed as log (1/EC50), as dependent variable) MLR and PLS methods have been employed. Using Dragon descriptors, the present study aims to develop a predictive and robust QSAR model for predicting anti-HIV activity of the HEPT derivatives for better understanding the molecular features of these compounds important for their biological activity. According to the squared correlation coefficients, which had values between 0.826 and 0.809 for the MLR and PLS methods, the results demonstrate almost identical qualities and good predictive ability for both MLR and PLS models. After dividing the dataset into training and test sets, the model predictability was tested by several parameters, including the Golbraikh-Tropsha external criteria and the goodness of fit tested with the Y-randomization test. [Acknowledgements. This project was financially supported by Project 1.1 and 1.2 of the Institute of Chemistry of the Romanian Academy. STATISTICA, MobyDigs and SIMCA-P+ acquisition was funded by Ministerul Educatiei, Cercetarii si Tineretului - Autoritatea Nationala pentru Cercetare Stiintifica (MedC-ANCS), contract grant number: 71GR/2006]
first_indexed 2024-12-11T12:30:28Z
format Article
id doaj.art-6081dbb17a9041c1a64071f191a85a52
institution Directory Open Access Journal
issn 0352-5139
language English
last_indexed 2024-12-11T12:30:28Z
publishDate 2013-01-01
publisher Serbian Chemical Society
record_format Article
series Journal of the Serbian Chemical Society
spelling doaj.art-6081dbb17a9041c1a64071f191a85a522022-12-22T01:07:16ZengSerbian Chemical SocietyJournal of the Serbian Chemical Society0352-51392013-01-0178449550610.2298/JSC120713085IQSAR study for anti-HIV-1 activities of HEPT derivatives using MLR and PLSIvan DanielaCrisan LuminitaFunar-Timofei SimonaMracec MirceaA QSAR study using Multiple Linear Regression (MLR) and a Partial Least Squares (PLS) methodology was performed for a series of 127 derivatives of 1-(2-hydroxy-ethoxy)methyl]-6-(phenylthio)-timine (HEPT), a potent inhibitor of the of the human immunodeficiency virus type 1, HIV-1 reverse transcriptase (RT). To explore the relationship between a pool of HEPT derivative descriptors (as independent variables) and anti-HIV-1 activity expressed as log (1/EC50), as dependent variable) MLR and PLS methods have been employed. Using Dragon descriptors, the present study aims to develop a predictive and robust QSAR model for predicting anti-HIV activity of the HEPT derivatives for better understanding the molecular features of these compounds important for their biological activity. According to the squared correlation coefficients, which had values between 0.826 and 0.809 for the MLR and PLS methods, the results demonstrate almost identical qualities and good predictive ability for both MLR and PLS models. After dividing the dataset into training and test sets, the model predictability was tested by several parameters, including the Golbraikh-Tropsha external criteria and the goodness of fit tested with the Y-randomization test. [Acknowledgements. This project was financially supported by Project 1.1 and 1.2 of the Institute of Chemistry of the Romanian Academy. STATISTICA, MobyDigs and SIMCA-P+ acquisition was funded by Ministerul Educatiei, Cercetarii si Tineretului - Autoritatea Nationala pentru Cercetare Stiintifica (MedC-ANCS), contract grant number: 71GR/2006]http://www.doiserbia.nb.rs/img/doi/0352-5139/2013/0352-51391200085I.pdfGolbraikh-Tropsha criteriadragon descriptorsthe Y-randomization
spellingShingle Ivan Daniela
Crisan Luminita
Funar-Timofei Simona
Mracec Mircea
QSAR study for anti-HIV-1 activities of HEPT derivatives using MLR and PLS
Journal of the Serbian Chemical Society
Golbraikh-Tropsha criteria
dragon descriptors
the Y-randomization
title QSAR study for anti-HIV-1 activities of HEPT derivatives using MLR and PLS
title_full QSAR study for anti-HIV-1 activities of HEPT derivatives using MLR and PLS
title_fullStr QSAR study for anti-HIV-1 activities of HEPT derivatives using MLR and PLS
title_full_unstemmed QSAR study for anti-HIV-1 activities of HEPT derivatives using MLR and PLS
title_short QSAR study for anti-HIV-1 activities of HEPT derivatives using MLR and PLS
title_sort qsar study for anti hiv 1 activities of hept derivatives using mlr and pls
topic Golbraikh-Tropsha criteria
dragon descriptors
the Y-randomization
url http://www.doiserbia.nb.rs/img/doi/0352-5139/2013/0352-51391200085I.pdf
work_keys_str_mv AT ivandaniela qsarstudyforantihiv1activitiesofheptderivativesusingmlrandpls
AT crisanluminita qsarstudyforantihiv1activitiesofheptderivativesusingmlrandpls
AT funartimofeisimona qsarstudyforantihiv1activitiesofheptderivativesusingmlrandpls
AT mracecmircea qsarstudyforantihiv1activitiesofheptderivativesusingmlrandpls