Title:RepurposeVS: A Drug Repurposing-Focused Computational Method for Accurate Drug-Target Signature Predictions
Volume: 18
Issue: 8
Author(s): Naiem T. Issa, Oakland J. Peters, Stephen W. Byers and Sivanesan Dakshanamurthy
Affiliation:
Keywords:
Cancer, drug, interaction, mebendazole, repositioning, repurposing, virtual screening.
Abstract: We describe here RepurposeVS for the reliable prediction of drug-target signatures using
X-ray protein crystal structures. RepurposeVS is a virtual screening method that incorporates docking,
drug-centric and protein-centric 2D/3D fingerprints with a rigorous mathematical normalization
procedure to account for the variability in units and provide high-resolution contextual information for
drug-target binding. Validity was confirmed by the following: (1) providing the greatest enrichment of
known drug binders for multiple protein targets in virtual screening experiments, (2) determining that similarly shaped
protein target pockets are predicted to bind drugs of similar 3D shapes when RepurposeVS is applied to 2,335 human
protein targets, and (3) determining true biological associations in vitro for mebendazole (MBZ) across many predicted
kinase targets for potential cancer repurposing. Since RepurposeVS is a drug repurposing-focused method, benchmarking
was conducted on a set of 3,671 FDA approved and experimental drugs rather than the Database of Useful Decoys (DUDE)
so as to streamline downstream repurposing experiments. We further apply RepurposeVS to explore the overall
potential drug repurposing space for currently approved drugs. RepurposeVS is not computationally intensive and
increases performance accuracy, thus serving as an efficient and powerful in silico tool to predict drug-target associations
in drug repurposing.
