Literature DB >> 16426053

A multivariate analysis of HIV-1 protease inhibitors and resistance induced by mutation.

Anna Maria Almerico1, Marco Tutone, Antonino Lauria, Patrizia Diana, Paola Barraja, Alessandra Montalbano, Girolamo Cirrincione, Gaetano Dattolo.   

Abstract

This paper describes the use of the multivariate statistical procedure principal component analysis as a tool to explore the inhibitory activity of classes of protease inhibitors (PIs) against HIV-1 viruses (wild type and more-frequent single mutants, V82A, V82F, and I84V) and against protease enzymes. The analysis of correlations between biological activity and molecular descriptors or similarity indexes allowed a reliable classification of the 51 derivatives considered in this study. The best results were obtained in the case of the I84V mutant for which a high number of predictions was achieved. On this basis, this statistical approach is proposed as a reliable method for the prediction of the activity of PIs, for which the data against mutant strains have not been reported.

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Year:  2006        PMID: 16426053     DOI: 10.1021/ci050139z

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  2 in total

1.  Docking and multivariate methods to explore HIV-1 drug-resistance: a comparative analysis.

Authors:  Anna Maria Almerico; Marco Tutone; Antonino Lauria
Journal:  J Comput Aided Mol Des       Date:  2008-02-14       Impact factor: 3.686

2.  In silico Design of Novel HIV-1 NNRTIs Based on Combined Modeling Studies of Dihydrofuro[3,4-d]pyrimidines.

Authors:  Yanming Chen; Yafeng Tian; Ya Gao; Fengshou Wu; Xiaogang Luo; Xiulian Ju; Genyan Liu
Journal:  Front Chem       Date:  2020-03-24       Impact factor: 5.221

  2 in total

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