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Modeling Protein-Ligand Binding by Mining Minima.


ABSTRACT: We present the first application of the mining minima algorithm to protein-small molecule binding. This end-point approach use 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 experiment for three sets of HIV-1protease 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.

SUBMITTER: Chen W 

PROVIDER: S-EPMC3359898 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature

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Modeling Protein-Ligand Binding by Mining Minima.

Chen Wei W   Gilson Michael K MK   Webb Simon P SP   Potter Michael J MJ  

Journal of chemical theory and computation 20101008 11


We present the first application of the mining minima algorithm to protein-small molecule binding. This end-point approach use 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 experiment for three sets of HIV-1protease inhibitors and a set of phosphodiesterase 10a inhibitors. The contributions of various aspects of the  ...[more]

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