Abstract
Conquering the mutational drug resistance is a great challenge in anti-HIV drug development and therapy. Quantitatively predicting the mutational drug resistance in molecular level and elucidating the three dimensional structure-resistance relationships for anti-HIV drug targets will help to improve the understanding of the drug resistance mechanism and aid the design of resistance evading inhibitors. Here the MB-QSAR (Mutation-dependent Biomacromolecular Quantitative Structure Activity Relationship) method was employed to predict the molecular drug resistance of HIV-1 protease mutants towards six drugs, and to depict the structure resistance relationships in HIV-1 protease mutants. MB-QSAR models were constructed based on a published data set of Ki values for HIV-1 protease mutants against drugs. Reliable MB-QSAR models were achieved and these models display both well internal and external prediction abilities. Interpreting the MB-QSAR models supplied structural information related to the drug resistance as well as the guidance for the design of resistance evading drugs. This work showed that MB-QSAR method can be employed to predict the resistance of HIV-1 protease caused by polymorphic mutations, which offer a fast and accurate method for the prediction of other drug target within the context of 3D structures.
Highlights
Conquering the mutational drug resistance is a great challenge in anti-HIV drug development and therapy
We have developed a method called as MB-QSAR (Mutation dependent Biomacromolecular Quantitative Structure Activity Relationship), which allows to rapidly predict the drug resistance accurately and supplies sufficient structural information directly related to the drug resistance
MB-QSAR method assumes that a suitable sampling of the molecular field values in the inhibitor binding pocket of the mutants can yield models which can quantitatively predict the drug resistance of new mutants and provide information to help the understand of the drug resistance mechanisms and the design of resistance evading inhibitors (Fig. 2)
Summary
Conquering the mutational drug resistance is a great challenge in anti-HIV drug development and therapy. Structure-based methods are inherently more suitable to predict and interpret the impact of mutations on target-drug interactions These methods include using molecular docking to predict resistance of HIV1-PR to different inhibitors[21,22], using molecular field potential to predict the genotypes of HIV drug r esistance[23], and using molecular dynamics (MD) simulations to study the impact of mutations on structural dynamics, stability and binding affinity[24,25,26,27,28]. These methods can provide detailed structural information related to mutational
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