On the Characterization and Selection of Diverse Conformational Ensembles with Applications to Flexible Docking
Issue No. 02 - March/April (2011 vol. 8)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TCBB.2009.59
Sébastien Loriot , INRIA Sophia-Antipolis, France
Sushant Sachdeva , Princeton University, USA
Karine Bastard , Université de Nantes, CNRS, France
Chantal Prévost , CNRS, France
Frédéric Cazals , INRIA Sophia-Antipolis, France
To address challenging flexible docking problems, a number of docking algorithms pregenerate large collections of candidate conformers. To remove the redundancy from such ensembles, a central problem in this context is to report a selection of conformers maximizing some geometric diversity criterion. We make three contributions to this problem. First, we resort to geometric optimization so as to report selections maximizing the molecular volume or molecular surface area (MSA) of the selection. Greedy strategies are developed, together with approximation bounds. Second, to assess the efficacy of our algorithms, we investigate two conformer ensembles corresponding to a flexible loop of four protein complexes. By focusing on the MSA of the selection, we show that our strategy matches the MSA of standard selection methods, but resorting to a number of conformers between one and two orders of magnitude smaller. This observation is qualitatively explained using the Betti numbers of the union of balls of the selection. Finally, we replace the conformer selection problem in the context of multiple-copy flexible docking. On the aforementioned systems, we show that using the loops selected by our strategy can improve the result of the docking process.
Flexibility, conformer selection, flexible docking, geometric optimization, Van der Waals models, molecular surface area (MSA).
K. Bastard, S. Loriot, C. Prévost, F. Cazals and S. Sachdeva, "On the Characterization and Selection of Diverse Conformational Ensembles with Applications to Flexible Docking," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. , pp. 487-498, 2009.