Investigating molecular dynamics-guided lead optimization of EGFR inhibitors

The epidermal growth factor receptor (EGFR) is part of an extended family of proteins that together control aspects of cell growth and development, and thus a validated target for drug discovery. We explore in this work the suitability of a molecular dynamics-based end-point binding free energy protocol to estimate the relative affinities of a virtual combinatorial library designed around the EGFR model inhibitor 6{1} as a tool to guide chemical synthesis toward the most promising compounds. To investigate the validity of this approach, selected analogs including some with better and worse predicted affinities relative to 6{1} were synthesized, and their biological activity determined. To understand the binding determinants of the different analogs, hydrogen bonding and van der Waals contributions, and water molecule bridging in the EGFR–analog complexes were analyzed. The experimental validation was in good qualitative agreement with our theoretical calculations, while also a 6-dibromophenyl-substituted compound with enhanced inhibitory effect on EGFR compared to the reference ligand was obtained.

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