Modeling Protein-Ligand Binding by Mining Minima

We present the first application of the mining minima algorithm to protein small molecule binding. This end-point approach uses an empirical force field and implicit solvent models, treats the protein binding site as fully flexible, and estimates free energies as sums over local energy wells. The calculations are found to yield encouraging agreement with experimental results for three sets of HIV-1 protease inhibitors and a set of phosphodiesterase 10a inhibitors. The contributions of various aspects of the model to its accuracy are examined, and the Poisson-Boltzmann correction is found to be the most critical. Interestingly, the computed changes in configurational entropy upon binding fall roughly along the same entropy-energy correlation previously observed for smaller host-guest systems. Strengths and weaknesses of the method are discussed, as are the prospects for enhancing accuracy and speed.