In this work we have developed a multi-tiered computational platform to study protein-drug interactions. At the beginning of the workflow more efficient and less accurate methods are used to enable large libraries of proteins in many conformations and massive chemical libraries to be screened. At each subsequent step in the workflow a subset of input data is investigated with increased accuracy and more computationally expensive methods. We demonstrate the developed workflow with the investigation of the lymphocyte-specific kinase LCK, which is implicated as a drug target in many cancers and also known to have toxic effects when unintentionally targeted. Several LCK states and conformations are investigated using molecular docking and generalized Born and surface area continuum solvation (MM/GBSA). Different variations in the drug screening process provide unique results that may elucidate the biological mechanisms underlying the drug interactions.

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Published in Procedia Computer Science, v. 108C, p. 1222-1231.

© 2017 The Authors. Published by Elsevier B.V.

Under a Creative Commons license.

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This research used computational resources at the University of Kentucky’s Center for Computational and the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This work was supported by the National Institutes of Health (NIH) National Center for Advancing Translational Science grant KL2TR000116 and 1KL2TR001996-01. This work was supported in part by the U.S. Department of Energy, Office of Science, Office of Workforce Development for Teachers and Scientists (WDTS) under the BLUFF.