Binding of antifusion peptides with HIVgp41 from molecular dynamics simulations: quantitative correlation with experiment.

Robert C Rizzo, Bentley Strockbine

Journal: Proteins 2007;67(3):630-42

PMID: 17335007

Abstract

Peptides based on C-terminal regions of the human immunodeficiency virus (HIV) viral protein gp41 represent an important new class of antiviral therapeutics called peptide fusion inhibitors. In this study, computational methods were used to model the binding of six peptides that contain residues that pack into a conserved hydrophobic pocket on HIVgp41, an attractive target site for the development of small molecule inhibitors. Free energies of binding were computed using molecular mechanics Generalized Born surface area (MM-GBSA) methods from molecular dynamics (MD) simulations, which employed either explicit (TIP3P) or continuum Generalized Born (GB) water models and strong correlations between experimental and computational affinities were obtained in both cases. Energy decomposition of the TIP3P-MD results (r2 = 0.75) reveals that variation in experimental affinity is highly correlated with changes in intermolecular van der Waals energies (deltaE(vdw)) on both a local (residue-based, r2 = 0.94) and global (peptide-based, r2 = 0.84) scale. The results show that differential association of C-peptides with HIVgp41 is driven solely by changes within the conserved pocket supporting the hypothesis that this region is an important drug target site. Such strong agreement with experiment is notable given the large size of the ligands (34 amino-acids) relative to the small range of experimental affinities (2 kcal/mol) and demonstrates good sensitivity of this computational method for simulating peptide fusion inhibitors. Finally, inspection of simulation trajectories identified a highly populated pi-type hydrogen bond, which formed between Gln575 on the receptor and the aromatic ring of peptide ligand Phe631, which could have important implications for drug design.

2007 Wiley-Liss, Inc.

Address: Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794-3600, USA.

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