Deciphering quinazoline derivatives' interactions with EGFR: a computational quest for advanced cancer therapy through 3D-QSAR, virtual screening, and MD simulations.

ABSTRACT:

Introduction

The epidermal growth factor receptor (EGFR) presents a crucial target for combatting cancer mortality.

Methods

This study employs a suite of computational techniques, including 3D-QSAR, ligand-based virtual screening, molecular docking, fingerprinting analysis, ADME, and DFT-based analyses (MESP, HOMO, LUMO), supplemented by molecular dynamics simulations and MMGB/PBSA free energy calculations, to explore the binding dynamics of quinazoline derivatives with EGFR. With strong q2 and r2 values from CoMFA and CoMSIA models, our 3D- QSAR models reliably predict EGFR inhibitors' efficacy.

Results and discussion

Utilizing a potent model compound as a reference, an E-pharmacophore model was developed to sift through the eMolecules database, identifying 19 virtua

SUBMITTER: Anwar S 

PROVIDER: S-EPMC11540632 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature