Work

Prediction of HIV‐1 Protease/Inhibitor Affinity using RosettaLigand

Year: 2012

Type: article

Abstract: Predicting HIV-1 protease/inhibitor binding affinity as the difference between the free energy of the inhibitor bound and unbound state remains difficult as the unbound state exists as an ensemble of conformations with various degrees of flap opening. We improve computational prediction of protease/inhibitor affinity by invoking the hypothesis that the free energy of the unbound state while difficult to predict is less sensitive to mutation. Thereby the HIV-1 protease/inhibitor binding affinity can be approximated with the free energy of the bound state alone. Bound state free energy can be predicted from comparative models of HIV-1 protease mutant/inhibitor complexes. Absolute binding energies are predicted with R = 0.71 and SE = 5.91 kJ/mol. Changes in binding free energy upon mutation can be predicted with R = 0.85 and SE = 4.49 kJ/mol. Resistance mutations that lower inhibitor binding affinity can thereby be recognized early in HIV-1 protease inhibitor development.

Source: Chemical Biology & Drug Design

DOI: 10.1111/j.1747-0285.2012.01356.x

Authors: Gordon Lemmon, Kristian Kaufmann, Jens Meiler

Institution: Vanderbilt University

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: Vanderbilt University, National Institute of Mental Health, National Institute of General Medical Sciences

Awards: G1149287275, Molecular Biophysics Training Grant at Vanderbilt, G2861424750