GPUGrid New paper 1/2: PlayMolecule CrypticScout: Predicting Protein Cryptic Sites Using Mixed-Solvent Molecular Simulation

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Two recent papers which came out with results from GPUGRID. First, PlayMolecule CrypticScout: Predicting Protein Cryptic Sites Using Mixed-Solvent Molecular Simulations Gerard Martinez-Rosell, Silvia Lovera, Zara A. Sands, and Gianni De Fabritiis Journal of Chemical Information and Modeling 2020 60 (4), 2314-2324 DOI: 10.1021/acs.jcim.9b01209 In this paper (and the corresponding live system) GPUGRID's computations are used to power a search for elusive (transient) pockets which may become drug targets. Thanks for the contributions!
Cryptic pockets are protein cavities that remain hidden in resolved apo structures and generally require the presence of a co-crystallized ligand to become visible. Finding new cryptic pockets is crucial for structure-based drug discovery to identify new ways of modulating protein activity and thus expand the druggable space. We present here a new method and associated web application leveraging mixed-solvent molecular dynamics (MD) simulations using benzene as a hydrophobic probe to detect cryptic pockets. Our all-atom MD-based workflow was systematically tested on 18 different systems and 5 additional kinases and represents the largest validation study of this kind. CrypticScout identifies benzene probe binding hotspots on a protein surface by mapping probe occupancy, residence time, and the benzene occupancy reweighed by the residence time. The method is presented to the scientific community in a web application available via www.playmolecule.org using a distributed computing infrastructure to perform the simulations.
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