Analysis of HIV wild-type and mutant structures via in silico docking against diverse ligand libraries.

TitleAnalysis of HIV wild-type and mutant structures via in silico docking against diverse ligand libraries.
Publication TypeJournal Article
Year of Publication2007
AuthorsChang MW, Lindstrom W, Olson AJ, Belew RK
JournalJ Chem Inf Model
Date Published2007 May-Jun
KeywordsComputer Simulation, HIV Protease, HIV Protease Inhibitors, HIV-1, Ligands, Mutation, Principal Component Analysis, Protein Binding, Structure-Activity Relationship

The FightAIDS@Home distributed computing project uses AutoDock for an initial virtual screen of HIV protease structures against a broad range of 1771 ligands including both known protease inhibitors and a diverse library of other ligands. The volume of results allows novel large-scale analyses of binding energy "profiles" for HIV structures. Beyond identifying potential lead compounds, these characterizations provide methods for choosing representative wild-type and mutant protein structures from the larger set. From the binding energy profiles of the PDB structures, a principal component analysis based analysis identifies seven "spanning" proteases. A complementary analysis finds that the wild-type protease structure 2BPZ best captures the central tendency of the protease set. Using a comparison of known protease inhibitors against the diverse ligand set yields an AutoDock binding energy "significance" threshold of -7.0 kcal/mol between significant, strongly binding ligands and other weak/nonspecific binding energies. This threshold captures nearly 98% of known inhibitor interactions while rejecting more than 95% of suspected noninhibitor interactions. These methods should be of general use in virtual screening projects and will be used to improve further FightAIDS@Home experiments.

PubMed URL
Alternate TitleJ Chem Inf Model
PubMed ID17447753