Given the remarkable advance in computafional power over the past decade, why has molecular simulation not had a more significant impact on the drug discovery process? While there are certainly noteworthy successes, the impact of virtual screening is limited by approximate treatment of ligand-protein interacfions along h?o orthogonal dimensions: (1) Incorporation of backbone flexibility ofthe receptor, and (2) The accuracy with which molecular interacfions are computed at the atomic level.
The first Aim seeks a solufion to issue (1) by proposing a novel approach to virtual screening by targefing ensembles of receptor conformafions, as sampled in native like environments during microsecond fimescale simulafion. In contrast to previous efforts, the present proposal suggests a computationally expedient solution to the problem of esfimafing the entropy of binding.
The second Aim seeks a solufion to problem (2) by developing a new class of intermolecular potenfial based on recent advances in the quantum mechanical treatment of weak nonbonded interacfions. Previously published results indicate at least a factor of five improvement in accuracy over standard empirical approaches. By bringing these advances to the field of protein-ligand interacfions, dramafic improvement in the accuracy ofthese calculafions is expected.
Both Aims will be pursued in the context ofthe A2A adenosine receptor, a member ofthe G-protein coupled receptor family and a target for several disorders ofthe central nervous system, including Parkinson's disease. Hits identified from small molecule libraries will be experimentally validated via a collaboration with a lab with extensive expertise in A2A biochemistry. We will also apply our methods to the opfimizafion of a series of androgen receptor antagonists developed at UD, with the long term goal of treating prostate cancer. Overall, success in either Aim will have a profound and widespread, positive impact on the predictive validity of calculations of small molecule-protein interacfions. This will in turn improve the value of hits identified in virtual screens, and help to realize the predictive promise of virtual screening.
This project seeks to significantly advance the field of virtual screening for drug discovery, a potenfially powerful tool in the search for new therapies for known molecular targets. The proposed methods will be developed in the context of two protein targets: One that is under invesfigafion for treatment of Parkinson's and Hunfington's diseases, and one for the treatment of prostate cancer.
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