title: Strategies for lead discovery: application of footprint similarity targeting HIVgp41.
abstract: A highly-conserved binding pocket on HIVgp41 is an important target for development of anti-viral inhibitors. Holden et al. (Bioorg. Med. Chem. Lett.2012, 22, 3011) recently reported 7 experimentally-verified leads identified through a computational screen to the gp41 pocket in conjunction with a new DOCK scoring method (termed FPS scoring) developed in our laboratory. The method employs molecular footprints based on per-residue van der Waals interactions, electrostatic interactions, or the sum. In this work, we critically examine the gp41 screening results, prioritized using different scoring methods, in terms of two main criteria: (1) ligand pose properties which include footprint and energy score decompositions, MW, number of rotatable bonds, ligand efficiency, formal charge, and volume overlap, and (2) ligand pose stability which includes footprint stability (changes in footprint overlap) and rmsd stability (changes in geometry). Relative to standard DOCK scoring, pose property analyses demonstrate how FPS scoring can be used to identify ligands that mimic a known reference (derived here from the native gp41 substrate), while pose stability analyses demonstrate how FPS scoring can be used to enrich for compounds with greater overall stability during molecular dynamics (MD) simulations. Compellingly, of the 115 compounds tested experimentally, the 7 active compounds, as a group, more closely mimic the footprints made by the reference and show greater MD stability compared to the inactive group. Extensive studies using 116 protein-ligand complexes as controls reveal that ligands in their crystallographic binding pose also maintain higher FPS scores and smaller rmsds than do accompanying decoys, confirming that native poses are indeed 'stable' under the same conditions and that monitoring FPS variability during compound prioritization is likely to be beneficial. Overall, the results suggest the new scoring method will complement current virtual screening approaches for both the identification (FPS-ranking) and prioritization (FPS-stability) of target-compatible molecules in a quantitative and logical way.
authors: Department of Applied Mathematics & Statistics, Stony Brook University, Stony Brook, NY 11794, United States.
authors: Patrick M
authors: PM
authors: Holden
authors: Department of Applied Mathematics & Statistics, Stony Brook University, Stony Brook, NY 11794, United States.
authors: William J
authors: WJ
authors: Allen
authors: Department of Basic Sciences, Touro University-California, Mare Island, Vallejo, CA 94592, United States; Department of Pharmaceutical Chemistry, University of California San Francisco, CA 94143, United States.
authors: Miriam
authors: M
authors: Gochin
authors: Department of Applied Mathematics & Statistics, Stony Brook University, Stony Brook, NY 11794, United States; Institute of Chemical Biology & Drug Discovery, Stony Brook University, Stony Brook, NY 11794, United States; Laufer Center for Physical & Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, United States. Electronic address: rizzorc@gmail.com.
authors: Robert C
authors: RC
authors: Rizzo
mesh_terms: D019380:Anti-HIV Agents / Q000737:chemistry / Q000494:pharmacology*; D015195:Drug Design; D006678:HIV / Q000737:chemistry* / Q000378:metabolism; D015700:HIV Envelope Protein gp41 / Q000737:chemistry* / Q000378:metabolism; D006801:Humans; D008958:Models, Molecular; D062105:Molecular Docking Simulation; D011485:Protein Binding
chemical_list: D019380:Anti-HIV Agents; D015700:HIV Envelope Protein gp41
keywords: DCE; DOCK; DOCK Cartesian energy; Docking; ES; FPS; Footprint similarity; HIV; MD; Molecular dynamics; Protein–protein interactions; SASA; Scoring functions; VDW; Virtual screening; electrostatic; footprint similarity; glycoprotein-41; gp41; molecular dynamics; solvent accessible surface area; van der Waals