, Volume 20, Issue 6, pp 343-360
Date: 29 Sep 2006

Comparative residue interaction analysis (CoRIA): a 3D-QSAR approach to explore the binding contributions of active site residues with ligands

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Abstract

A novel approach termed comparative residue-interaction analysis (CoRIA), emphasizing the trends and principles of QSAR in a ligand–receptor environment has been developed to analyze and predict the binding affinity of enzyme inhibitors. To test this new approach, a training set of 36 COX-2 inhibitors belonging to nine families was selected. The putative binding (bioactive) conformations of inhibitors in the COX-2 active site were searched using the program DOCK. The docked configurations were further refined by a combination of Monte Carlo and simulated annealing methods with the Affinity program. The non-bonded interaction energies of the inhibitors with the individual amino acid residues in the active site were then computed. These interaction energies, plus specific terms describing the thermodynamics of ligand–enzyme binding, were correlated to the biological activity with G/PLS. The various QSAR models obtained were validated internally by cross validation and boot strapping, and externally using a test set of 13 molecules. The QSAR models developed on the CoRIA formalism were robust with good r 2, q 2 and r pred 2 values. The major highlights of the method are: adaptation of the QSAR formalism in a receptor setting to answer both the type (qualitative) and the extent (quantitative) of ligand–receptor binding, and use of descriptors that account for the complete thermodynamics of the ligand–receptor binding. The CoRIA approach can be used to identify crucial interactions of inhibitors with the enzyme at the residue level, which can be gainfully exploited in optimizing the inhibitory activity of ligands. Furthermore, it can be used with advantage to guide point mutation studies. As regards the COX-2 dataset, the CoRIA approach shows that improving Coulombic interaction with Pro528 and reducing van der Waals interaction with Tyr385 will improve the binding affinity of inhibitors.