Proper incorporation of protein flexibility for prediction of binding poses and affinities of small compounds has attracted increasing attention recently in computational drug design. Various approaches have been proposed to accommodate protein flexibility in the prediction of binding modes and the binding free energy of ligands in an efficient manner. In this review, the significance of incorporating protein flexibility is discussed from the structural biophysical point of view, and then various approaches of generating protein conformation ensembles, as well as their successes and limitations, are introduced and compared. Special emphasis is on how to generate a proper ensemble of conformation for a specific purpose, as well as the computational efficiency of various approaches. Different searching algorithms for the prediction of optimal binding poses of ligands, which are the core engines of docking programs, are accounted for. Scoring functions for evaluation of protein-ligand complexes are compared. Two end-point methods of free energy calculation, Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) and the Linear Interaction Energy (LIE) method, are briefly reviewed. Finally, we also provide an example for the extension of the conventional protein-ligand docking algorithm for prediction of multiple binding sites and ligand translocation pathways.
Keywords: docking, relaxed complex scheme, molecular dynamics, protein flexibility, drug design, protein, flexibility, MM/PBSA, LIE, NMR, TR-WAXS, DNP, bacteriorhodopsin, microscopy, catalysis, protein-ligand interactions, ASIC, SLITHER, X-ray crystallography, crystallization, CVN, AutoDock, GEMDock, OPTIMIZATION, ALGORITHMS, EA, GOLD, BPMC, DE, EGA, MEDock, Particle Swarm Algorithm, QSAR, IFREDA, enzymes, FKBP, AChE, HDAC
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