Data driven polypharmacological drug design for lung cancer: analyses for targeting ALK, MET, and EGFR.

ABSTRACT: Drug design of protein kinase inhibitors is now greatly enabled by thousands of publicly available X-ray structures, extensive ligand binding data, and optimized scaffolds coming off patent. The extensive data begin to enable design against a spectrum of targets (polypharmacology); however, the data also reveal heterogeneities of structure, subtleties of chemical interactions, and apparent inconsistencies between diverse data types. As a result, incorporation of all relevant data requires expert choices to combine computational and informatics methods, along with human insight. Here we consider polypharmacological targeting of protein kinases ALK, MET, and EGFR (and its drug resistant mutant T790M) in non small cell lung cancer as an example. Both EGFR and ALK represent sources of primary

SUBMITTER: Narayanan D 

PROVIDER: S-EPMC5496928 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature