QSAR study for anti-HIV-1 activities of HEPT derivatives using MLR and PLS
| Autor: | Daniela Ivan, Simona Funar-Timofei, Mircea Mracec, Luminita Crisan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
Anti hiv 1
Quantitative structure–activity relationship Stereochemistry business.industry the Y-randomization Human immunodeficiency virus (HIV) Pattern recognition General Chemistry dragon descriptors medicine.disease_cause lcsh:Chemistry Goodness of fit lcsh:QD1-999 Golbraikh-Tropsha criteria Linear regression Partial least squares regression medicine Artificial intelligence business Mathematics |
| Zdroj: | Journal of the Serbian Chemical Society, Vol 78, Iss 4, Pp 495-506 (2013) |
| ISSN: | 0352-5139 |
| Popis: | 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] |
| Databáze: | OpenAIRE |
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