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Updated: Jul 5, 2026

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Prediction of HIV-1 protease inhibitor resistance by Molecular Modeling Protocols (MMPs) using GenMol software
G Pèpe1, J Courcambeck, R Perbost
1GCOM2, UMR-CNRS 6114, Faculté des Sciences de Luminy, Case 901, 13288 Marseille Cedex 9, France. pepe@luminy.univ-mrs.fr
Abstract:
This paper investigates the contribution of Molecular Modeling to (i) predict and (ii) understand more fundamentally HIV drug resistance. Based on a new automated GenMol module, these goals are approached by Molecular Modeling Protocols (MMPs), respectively, (i) the Molecular Modeling Phenotype Protocol (MMPP) and (ii) the Molecular Modeling Phenotype-Genotype Protocol (MMGPP). Section 2 recalls clinical practice with a reference case study and Section 3 presents atomistic simulation tools. Section 4 is the heart of the paper. In Section 4.1, MMPP drug resistance prediction is based on correlations between fold resistances versus binding energies on 2959 HIV-1 complexes with 6 protease inhibitors. Based on a drug sensitivity twofold criterion, modeling prediction is able to replace long and costly phenotype tests. In Section 4.2, MMGPP enlightens drug resistance by investigating steric and energetic residues/inhibitor interaction. Section 5 gives a synthesis on modeling contribution to drug resistance prediction. In conclusion, the most promising trend consists of MMP automats that are able to suggest a real time diagnosis taking into account the history of each patient, to enrich databases and to develop therapy strategy and new drugs.

