Literature DB >> 35067782

Screening and identification of phytochemical drug molecules against mutant BRCA1 receptor of breast cancer using computational approaches.

Jitender Singh1, Namrata Sangwan1, Arushi Chauhan1, Phulen Sarma2, Ajay Prakash2, Bikash Medhi2, Pramod K Avti3.   

Abstract

The American Cancer Society claims that breast cancer is the second most significant cause of cancer-related death, with over one million women diagnosed each year. Breast cancer linked to the BRCA1 gene has a significant risk of mortality and recurrence and is susceptible to alteration or over-expression, which can lead to hereditary breast cancer. Given the shortage of effective and possibly curative treatments for breast cancer, the present study combined molecular and computational analysis to find prospective phytochemical substances that can suppress the mutant gene (BRCA1) that causes the disease. Virtual screening and Molecular docking approaches are utilized to find probable phytochemicals from the ZINC database. The 3D structure of mutant BRCA1 protein with the id 3PXB was extracted from the NCBI-PDB. Top 10 phytochemical compounds shortlisted based on molecular docking score between - 11.6 and - 13.0. Following the ADMET properties, only three (ZINC000085490903 = - 12.50, ZINC000085490832 = - 12.44, and ZINC000070454071 = - 11.681) of the 10 selected compounds have drug-like properties. The molecular dynamic simulation study of the top three potential phytochemicals showed stabilized RMSD and RMSF values as compared to the APO form of the BRCA1 receptor. Further, trajectory analysis revealed that approximately similar radius of gyration score tends to the compactness of complex structure, and principal component and cross-correlation analysis suggest that the residues move in a strong correlation. Thermostability of the target complex (B-factor) provides information on the stable energy minimized structure. The findings suggest that the top three ligands show potential as breast cancer inhibitors.
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  B-factor; Dynamic simulation; Metapocket; Mutant BRCA1; Phytochemicals; Tumor suppressor; Virtual screening

Mesh:

Substances:

Year:  2022        PMID: 35067782     DOI: 10.1007/s11010-021-04338-4

Source DB:  PubMed          Journal:  Mol Cell Biochem        ISSN: 0300-8177            Impact factor:   3.396


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