A new peptide docking strategy using a mean field technique with mutually orthogonal Latin square sampling.
The theoretical prediction of the association of a flexible ligand with a protein receptor requires efficient sampling of the conformational space of the ligand. Several docking methodologies are currently available. We propose a new docking technique that performs well at low computational cost. The method uses mutually orthogonal Latin squares to efficiently sample the docking space. A variant of the mean field technique is used to analyze this sample to arrive at the optimum. The method has been previously applied to explore the conformational space of peptides and identify structures with low values for the potential energy. Here we extend this method to simultaneously identify both the low energy conformation as well as a 'high-scoring' docking mode. Application of the method to 56 protein-peptide complexes, in which the length of the peptide ligand ranges from three to seven residues, and comparisons with Autodock 3.05, showed that the method works well.
Arun Prasad
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Centre of Advanced Study in Crystallography and Biophysics, University of Madras, Chennai, India.
Gautham
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D000465:Algorithms; D019295:Computational Biology; D003198:Computer Simulation; D015195:Drug Design; D008024:Ligands; D008958:Models, Molecular; D010455:Peptides / Q000737:chemistry* / Q000378:metabolism*; D011485:Protein Binding / Q000502:physiology; D011487:Protein Conformation
D008024:Ligands; D010455:Peptides