Improving conformational searches by geometric screening

Bioinformatics, Mar 2005

Motivation: Conformational searches in molecular docking are a time-consuming process with wide range of applications. Favorable conformations of the ligands that successfully bind with receptors are sought to form stable ligand–receptor complexes. Usually a large number of conformations are generated and their binding energies are examined. We propose adding a geometric screening phase before an energy minimization procedure so that only conformations that geometrically fit in the binding site will be prompted for energy calculation. Results: Geometric screening can drastically reduce the number of conformations to be examined from millions (or higher) to thousands (or lower). The method can also handle cases when there are more variables than geometric constraints. An early-stage implementation is able to finish the geometric filtering of conformations for molecules with up to nine variables in 1 min. To the best of our knowledge, this is the first time such results are reported deterministically. Contact: mzhang{at}mdanderson.org

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Improving conformational searches by geometric screening

Ming Zhang 1 2 R. Allen White 1 2 Liqun Wang 2 Ronald Goldman 0 Lydia Kavraki 0 3 5 Brendan Hassett 4 0 Department of Computer Science 1 Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston , Houston, TX 77225, USA 2 Department of Biostatistics and Applied Mathematics, The University of Texas M.D. Anderson Cancer Center , Houston, TX 77030, USA 3 Graudate Program in Structural and Computational Biology, Baylor College of Medicine , Houston, TX 77030, USA 4 Department of Mathematics, Rice University , Houston, TX 77251, USA 5 Department of Bioengineering Motivation: Conformational searches in molecular docking are a time-consuming process with wide range of applications. Favorable conformations of the ligands that successfully bind with receptors are sought to form stable ligand-receptor complexes. Usually a large number of conformations are generated and their binding energies are examined. We propose adding a geometric screening phase before an energy minimization procedure so that only conformations that geometrically fit in the binding site will be prompted for energy calculation. Results: Geometric screening can drastically reduce the number of conformations to be examined from millions (or higher) to thousands (or lower). The method can also handle cases when there are more variables than geometric constraints. An early-stage implementation is able to finish the geometric filtering of conformations for molecules with up to nine variables in 1 min. To the best of our knowledge, this is the first time such results are reported deterministically. Contact: The Author 2004. Published by Oxford University Press. All rights reserved. For Permissions, please email: - INTRODUCTION The properties and possible interactions of molecules are intimately related to their accessible conformations. Conformational searches seek to solve the problem of identifying reachable conformations of molecules with low energy. Such conformations determine molecular flexibility and hence functionality, which are important in understanding a variety of biological phenomena at the molecular level. In depth understanding of molecular flexibility will greatly help the design of synthetic materials, the synthesis of drugs, the mechanism of surface catalysis and the development of biological sensors (Cavasotto and Abagyan, 2004; Perola and Charifson, 2004; Henry and Ozkabak, 1998; Lengauer, 2002). Conformational searches are common in many applications involving pharmacophore modeling, molecular docking, protein folding and three-dimensional quantitative structureactivity relationships (Baker and Sali, 2001; Diller and Merz, 2001; Klebe, 2000; Samudrala, 2000; Song and Amato, 2002). In this paper, we investigate a new geometric screening method to improve conformational searches in computer-assisted drug design. Most drug discovery programs start from the identification of a biomolecular target of potential therapeutic value. Drug-like compounds (leads) binding to the molecular target and interfering with its activity as a receptor or an enzyme are then sought. High-throughput screening is usually performed on molecular libraries of known or constructed compounds. The resulting leads subsequently undergo a cycle of chemical refinement and testing until a drug is developed for clinical trials. When the structure of the biomolecular target is known, the most common virtual screening approach is molecular docking. In a successful ligandreceptor docking, the molecules exhibit geometric and chemical complementarity, which are essential for successful drug activity. Very often the binding site is specified by a pharmacophore, a set of three-dimensional features. The features can be specific atoms, centers of (benzene) rings, positive or negative charges, hydrophobic or hydrophilic centers, hydrogen bond donors or acceptors. The pharmacophore reflects the prevailing idea in computer-assisted drug design that ligand binding is primarily due to the interaction between the features of the ligand and the complementary features of the receptor (Lavalle et al., 2000; Rarey et al., 1996). Identifying the conformations of the ligands whose features reach the target positions while still maintaining low energies gives rise to conformational search problems. Earlier work The methods currently available for conformational searches fall into two categories: forward searches and inverse searches. Forward search methods are mostly energy oriented. That is, a large number of conformations are generated and their energies are examined. These methods assign values to the variables (torsional angles) systematically, randomly or deterministically, and then the energies of these conformations are calculated (Bursulaya et al., 2003; Brooijmans and Kuntz, 2003). Systematic search algorithms are based on grid values for each variable. The number of conformations to be examined increases exponentially when the num (...truncated)


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Ming Zhang, R. Allen White, Liqun Wang, Ronald Goldman, Lydia Kavraki, Brendan Hassett. Improving conformational searches by geometric screening, Bioinformatics, 2005, pp. 624-630, 21/5, DOI: 10.1093/bioinformatics/bti055