In Silico Insight to Identify Potential Inhibitors of BUB1B from Mushroom Bioactive Compounds to Prevent Breast Cancer Metastasis

Abstract

Background: Breast cancer is one of the most common types of cancer among women worldwide, and its metastasis is a significant cause of mortality. Therefore, identifying potential inhibitors of proteins involved in breast cancer metastasis is crucial for developing effective therapies. BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) is a key regulator of mitotic checkpoint control, which ensures the proper segregation of chromosomes during cell division. Dysregulation of BUB1B has been linked to a variety of human diseases, including breast cancer. Overexpression of BUB1B has been observed in various cancer types, and its inhibition has been shown to induce cancer cell death. Additionally, BUB1B inhibition has been suggested as a potential strategy for overcoming resistance to chemotherapy and radiation therapy. Given the importance of BUB1B in regulating cell division and its potential as a therapeutic target, the development of BUB1B inhibitors has been the focus of intense research efforts. Despite these efforts, few small molecule inhibitors of BUB1B have been identified, highlighting the need for further research in this area. In this study, the authors aimed to identify potential inhibitors of BUB1B from mushroom bioactive compounds using computational methods, which could ultimately lead to the development of new treatments for breast cancer metastasis. Methods: This study has incorporated 70 bioactive compounds (handpicked through literature mining) of distinct mushrooms that were considered and explored to identify a suitable drug candidate. Their absorption, distribution, metabolism and excretion (ADME) properties were obtained to predict the drug-likeness of these 70 mushroom compounds based on Lipinski’s rule of 5 (RO5). Screening these bioactive compounds and subsequent molecular docking against BUB1B provided compounds with the best conformation-based binding affinity. The best two complexes, i.e., BUB1B-lepitaprocerin D and BUB1B-peptidoglycan, were subjected to molecular dynamic simulations. Both complexes were assessed for their affinity, stability, and flexibility in protein-ligand complex systems. Results: The molecular dynamic (MD) simulation studies revealed that lepitaprocerin D has an energetically favorable binding affinity with BUB1B. Results showed that the formation of a hydrogen bond between residues ASN123 and SER157, and lepitaprocerin D had strengthened the affinity of lepitaprocerin D with BUB1B. Conclusions: This study identified lepitaprocerin D as a potential and novel inhibitor for BUB1B that could be a plausible drug candidate for identifying and controlling the spread of breast cancer metastasis.

Keywords

• lepitaprocerin d
• molecular docking
• molecular dynamics simulation
• bub1b
• admet
• aneuploidy
• tumorigenesis