Classification of Anti-HIV Compounds using QSAR Studies
نویسنده
چکیده
The Acquired Immunodeficiency Syndrome (AIDS) is one the most fatal disorders for which there have been no complete or successful chemotherapy yet. The pandemic spread of this disease has prompted an unprecedented scientific clinical effort to understand and propagate ways to combat it. Quantitative Structure–Activity Relationship (QSAR) study has been reportedly used to study topological indices, physiochemical and indicator parameters on a series of HEPT analogues for understanding HIV reverse transcriptase inhibitor activity (Shovanlal Gayen et al, 2004). The aim of their study was to correlate the identified molecular surface properties with the inhibitory activity of HIV-1 RT using QSAR. The docking energies were used to categorize anti-HIV compounds as classified and non classified multiple linear regression models. Results indicate that classified MLR had a better predictability than the non classified models. Thus this method of classification proves to be a good predictability model.
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Application of Genetic Algorithms for Pixel Selection in MIA-QSAR Studies on Anti-HIV HEPT Analogues for New Design Derivatives
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