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Updated: Jul 17, 2026

Rapid Screening of HIV Reverse Transcriptase and Integrase Inhibitors
Published on: April 10, 2014
Artificial neural networks: non-linear QSAR studies of HEPT derivatives as HIV-1 reverse transcriptase inhibitors
Latifa Douali1, Didier Villemin, Abdelmajid Zyad
1Département de Chimie, Faculté des Sciences Semlalia BP 2390 Université Cadi Ayyad, Marrakech, Morocco.
Abstract:
Structure-anti HIV activity relationships were established for a sample of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio)thymine (HEPT) using a three-layer neural network (NN). Eight structural descriptors and physicochemical variables were used to characterize the HEPT derivatives under study. The network's architecture and parameters were optimized in order to obtain good results. All the NN architectures were able to establish a satisfactory relationship between the molecular descriptors and the anti-HIV activity. NN proved to give better results than other models in the literature. NN have been shown to be particularly successful in their ability to identify non-linear relationships.
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