Chemoinformatics analysis of Mangifera indica leaves extracted phytochemicals as potential EGFR kinase modulators
Breast cancer, being among the most frequent and fatal cancers in women, is an enormous issue globally. The critical requirement for novel treatment methods is underscored by its high mortality rate and relentless advancement. Even though breast cancer is one of the world's most common causes of death, the therapeutic avenue is still limited. The aim of this work is to investigate the potential inhibitory effects of specific compounds present in leaf extract from <i>Mangifera indica</i> on the growth of drug-resistant breast cancer protease PDB ID 3w32. The chemical compounds present in <i>Mangifera indica</i> leaves were used to analyze using molecular modeling techniques, such as molecular docking, molecular dynamics (MD) simulations, quantum mechanics (QM) calculations, and the Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) method, in order to examine three key chemical constituents: quercetin (08), catechin (09), and elagic acid (10). The ligands undergo extensive testing to figure out how effective they are against the 3w32-overexpressing breast cancer protein. Quantum calculations retaining HOMO-LUMO analysis might identify important characteristics of molecules, such as chemical potential, electronegativity, hardness, softness, and orbital energy gaps. According to the molecular docking inquiry, ligands 08, 09, and 10 are strong candidates with strong binding affinity for the breast cancer protein that overexpresses 3w32. The protein binding site stability of the chosen natural ligands was verified by MD simulation. These three ligands not only surpass the efficacy of the FDA-approved treatment, but also fulfill the requirements for a possible new inhibitor of breast cancer.
Authors
- Ismat Jahan (ORCID: https://orcid.org/0000-0002-0384-1628)
- A. F. M. Shahab Uddin (ORCID: https://orcid.org/0000-0003-1074-0515)
- Ajoy Kumer (ORCID: https://orcid.org/0000-0001-5136-6166)
- Md. Mashiar Rahman (ORCID: https://orcid.org/0000-0002-3776-9855)
- Md. Abdullah Al Mashud (ORCID: https://orcid.org/0000-0002-2106-2134)
- Mohammad Harun‐Ur‐Rashid (ORCID: https://orcid.org/0000-0003-1883-4620)
- Md. Enamul Kabir Talukder (ORCID: https://orcid.org/0000-0001-8943-1912)
- Youssouf Ali Younous (ORCID: https://orcid.org/0009-0000-6869-6508)
- Mizanur Rahman (ORCID: https://orcid.org/0000-0003-4225-9451)
- Md. Harun-Or-Rashid (ORCID: https://orcid.org/0000-0002-9898-7119)
- Gamal A. Shazly
- Md. Mehedi Hasan Somrat
Institutions
- Daffodil International University (BD)
- King Saud University (SA)
- Islamic University (BD)
- International University of Business Agriculture and Technology (BD)
- Saveetha University (IN)
- Macquarie University (AU)
Publication Details
- Journal
- Frontiers in Chemistry
- Published
- 2025-03-24
- DOI
- https://doi.org/10.3389/fchem.2025.1524384
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00