Computational Evaluation of Bioactive Compounds from Colocasia affinis Schott as a Novel EGFR Inhibitor for Cancer Treatment

Abstract

Introduction: Epidermal growth factor receptor (EGFR) is a transmembrane protein that belongs to the ErbB/HER-family of tyrosine kinase receptors. Somatic mutations and overexpression of EGFR have been reported to play a vital role in cancer cell development and progression, including cell proliferation, differentiation, angiogenesis, apoptosis, and metastatic spread. Hence, EGFR is an important therapeutic target for the treatment of various types of epithelial cancers. Somatic mutations have led to resistance to clinically approved synthetic EGFR inhibitors. Furthermore, synthetic EGFR inhibitors have been associated with several side effects. Thus, there is a need to develop novel EGFR inhibitors with an acceptable biosafety profile and high efficacy. Methods: Herein, we employed structural bioinformatics and theoretical chemistry techniques via molecular docking, molecular mechanics generalized Born surface area (MM-GBSA) calculation, density functional theory analysis (DFT), and pharmacokinetic study to identify novel EGFR inhibitors. Results: The stringent molecular docking and MM-GBSA calculations identified MET 793, LYS 745, PHE 723, ASP 855, ARG 411, and THR 854 as principal amino acid residues for EGFR-ligands interactions. Furthermore, Colocasia affinis Schott compounds exhibited higher binding energy and more stable interactions than the reference compound (gefitinib). DFT analysis also ascertains better bioactivity and chemical reactivity of C. affinis Schott with favorable intramolecular charge transfer between electron-donor and electron acceptor groups. The pharmacokinetic profile of C. affinis Schott bioactive compounds satisfies Lipinski’s rule of five assessment. Conclusion: Collectively, C. affinis Schott compounds demonstrated higher inhibitory potentials against EGFR and better pharmacological properties when compared with gefitinib. C. affinis Schott compounds are therefore suggested as promising therapeutic EGFR inhibitors for cancer treatment.

Nypa fruticans Wurmb inhibits melanogenesis in isobutylmethylxanthine‑treated melanoma via the PI3K/AKT/mTOR/CREB and MAPK signaling pathways

“…These studies suggest that the levels of melanin, which is synthesized by TYR, are decreased by the activity of the phytochemicals in ENF, such as catechin, epicatechin, and isoquercitrin. In studies of other plants (Pinellia pedatisecta, P. ternata, and Colocasia affinis) belonging to the Araceae family, the bioactivity derived from the phytochemicals in these plants were found to regulate melanogenesis, inhibit cancer, and alleviate inflammation (39)(40)(41). The inhibitory effect of ENF on melanogenesis is related to cellular signaling pathways associated with MITF, which is controlled via PI3K/AKT/mTOR, ERK, and CREB (42).…”

Discovery of putative inhibitors against main drivers of SARS-CoV-2 infection: Insight from quantum mechanical evaluation and molecular modeling

“…Subsequently, the 3D structure of 1,000 compounds consisting of the substructure of the co-crystallized ligand of the targets was downloaded from the PubChem database ( https://pubchem.ncbi.nlm.nih.gov ). The structures of the ligands were cleaned, and their geometries were subjected to structural optimization using the default specifications of the LigPrep module incorporated in the Schrodinger suite and utilized for hypothesis generation ( Balogun et al, 2021a ). The prepared proteins and fully optimized geometry of ligands were used as input for molecular docking.…”

“…nlm.nih.gov). The structures of the ligands were cleaned, and their geometries were subjected to structural optimization using the default specifications of the LigPrep module incorporated in the Schrodinger suite and utilized for hypothesis generation (Balogun et al, 2021a). The prepared proteins and fully optimized geometry of ligands were used as input for molecular docking.…”

Discovery of Promising Inhibitors for SARS-CoV-2 Therapeutic Targets: A Quantum Mechanics and Molecular Modeling study

“…Subsequently, the 3D structure of 1000 compounds consisting of substructure of the co-crystallised ligand of the targets were downloaded from PubChem database (https://pubchem.ncbi.nlm.nih.gov). The structures of the ligands were cleaned and their geometries were subjected to structural optimization using the default speci cations of the LigPrep module and utilized for hypothesis generation (33). The prepared proteins and fully optimized geometry of ligands were used as input for molecular docking.…”