Protein−Ligand Docking Using Mutually Orthogonal Latin Squares (MOLSDOCK)
Shankaran Nehru Viji, P. Arun Prasad, N. Gautham
Abstract
Shankaran Nehru Viji, P. Arun Prasad, N. Gautham
Abstract
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 have proposed a 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 search through both the conformational space of a peptide as well its docking space. Here we extend this method to simultaneously identify both the low energy conformation as well as a high scoring docking mode for the small organic ligand molecules. Application of the method to 45 protein-ligand complexes, in which the number of rotatable torsions varies from 2 to 19, and comparisons with AutoDock 4.0, showed that the method works well.
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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 have proposed a 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 search through both the conformational space of a peptide as well its docking space. Here we extend this method to simultaneously identify both the low energy conformation as well as a high scoring docking mode for the small organic ligand molecules. Application of the method to 45 protein-ligand complexes, in which the number of rotatable torsions varies from 2 to 19, and comparisons with AutoDock 4.0, showed that the method works well.
Key concepts: Docking (animal), Computational biology, Protein–ligand docking, Ligand (biochemistry), Chemistry, Computer science, Stereochemistry, Biochemistry