Screening and identification of phytochemical drug molecules against mutant BRCA1 receptor of breast cancer using computational approaches.
Jitender SinghNamrata SangwanArushi ChauhanPhulen SarmaAjay PrakashBikash MedhiPramod K AvtiPublished in: Molecular and cellular biochemistry (2022)
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.
Keyphrases
- molecular docking
- breast cancer risk
- molecular dynamics simulations
- binding protein
- genome wide
- healthcare
- emergency department
- squamous cell carcinoma
- childhood cancer
- pregnant women
- skeletal muscle
- climate change
- transcription factor
- long non coding rna
- risk factors
- rectal cancer
- copy number
- insulin resistance
- social media
- dna methylation
- wild type
- papillary thyroid
- protein protein
- genome wide identification