In Silico Optimization of Epidermal Growth Factor Receptor Inhibitors Followed by Experimental Evaluation

CLAUDIO N CAVASOTTO; MARTÍN J. LAVECCHIA; JOSÉ IGNACIO BORRELL

Bariloche

Conferencia; 5th Argentinian Conference on Bioinformatics and Computational Biology; 2014

A2B2C

The Epidermal Growth Factor Receptor (EGFR) is part of an extended family of proteins that together control aspects of cell growth and development. It is a validated target for drug discovery, since it is involved in several types of cancer. Starting from a dichlorobenzyl pyridopyrimidine scaffold lead, and following an in silico flexible-ligand/flexible receptor docking-based characterization of its binding mode, a combinatorial virtual library of analogs was built, and their binding free energy assessed using the molecular mechanics-generalized born surface area (MM/GB-SA) approach, after performing long molecular dynamics simulations in explicit water. Molecules with better and worse predicted affinity were synthetized and their activity experimentally evaluated, thus obtaining a dibromobenzyl-substituted molecule with improved performance; experimental results were in excellent agreement with theoretical predictions. It is also remarkable that the ranking of the experimental inhibition activity is consistent with our calculations, which shows that binding free energy evaluation using the MM/GB-SA is a valid method for ligand optimization using an in silico-generated combinatorial library of analogs, followed by energy calculation and bioevaluation.