Predicting HIV-1 resistance to protease inhibitors: A new structure-based algorithm exploring binding-site Molecular Interaction Fields dissimilarities (original) (raw)

2017, Proceedings of MOL2NET 2017, International Conference on Multidisciplinary Sciences, 3rd edition

AI-generated Abstract

This study presents a novel computational algorithm designed to predict HIV-1 resistance to protease inhibitors by analyzing dissimilarities in binding-site Molecular Interaction Fields (MIF). The algorithm automatically generates high-quality 3D models of HIV-1 protease, assesses the chemical changes induced by mutations, and quantifies these variations to produce a resistance score. Preliminary tests indicate that the algorithm achieves promising sensitivity and specificity, offering a valuable tool for personalizing anti-HIV therapies and potentially extending to other viral targets.