2017 SIAM Conference on Computational Science and Engineering
Abstract. We present a model that has been created to improve in silico predictions of protein-drug interactions by using a variety of computational screening methods in an automated pipeline. Our test case for this model is LCK, a protein that normally mediates immune system development and is known to have both toxicological and oncologic implications. We have applied homology modeling, docking, molecular dynamics, and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) methods to achieve progressively better enrichment for an increasingly smaller set of tested compounds.
- Amir Kucharski, University of Kentucky, USA, firstname.lastname@example.org