Computational insights into the stereo-selectivity of catechins for the inhibition of the cancer therapeutic target EGFR kinase.

Abstract

The epidermal growth factor receptor (EGFR) plays a crucial role in regulating cellular growth and survival, and its dysregulation is implicated in various cancers, making it a prime target for cancer therapy. Natural compounds known as catechins have garnered attention as promising anticancer agents. These compounds exert their anticancer effects through diverse mechanisms, primarily by inhibiting receptor tyrosine kinases (RTKs), a protein family that includes the notable member EGFR. Catechins, characterized by two chiral centers and stereoisomerism, demonstrate variations in chemical and physical properties due to differences in the spatial orientation of atoms. Although previous studies have explored the membrane fluidity effects and transport across cellular membranes, the stereo-selectivity of catechins concerning EGFR kinase inhibition remains unexplored. In this study, we investigated the stereo-selectivity of catechins in inhibiting EGFR kinase, both in its wild-type and in the prevalent L858R mutant. Computational analyses indicated that all stereoisomers, including the extensively studied catechin (-)-EGCG, effectively bound within the ATP-binding site, potentially inhibiting EGFR kinase activity. Notably, gallated catechins emerged as superior EGFR inhibitors to their non-gallated counterparts, revealing intriguing binding trends. The top four stereoisomers exhibiting high dock scores and binding energies with wild-type EGFR comprise (-)-CG (-)-GCG (+)-CG, and (-)-EGCG. To assess dynamic behavior and stability, molecular dynamics simulations over 100 ns were conducted for the top-ranked catechin (-)-CG and the widely investigated catechin (-)-EGCG with EGFR kinase. This study enhances our understanding of how the stereoisomeric nature of a drug influences inhibitory potential, providing insights that could guide the selection of specific stereoisomers for improved efficacy inexisting drugs.