Computational Discovery of High-Affinity MCL-1 Binders as Promising Therapeutic Candidates for Breast Cancer.

Abstract

:  Breast cancer remains one of the leading causes of cancer-related mortality among women worldwide. The dysregulation of apoptosis-related signaling pathways has been recognized as a hallmark of breast tumorigenesis, where overexpression of the anti-apoptotic protein Myeloid Cell Leukemia-1 (MCL-1) contributes significantly to cancer cell survival and resistance to therapy. As such, MCL-1 represents an essential therapeutic target for rational drug design and discovery. The present study focuses on the identification and characterization of potential inhibitors of MCL-1 using in silico computational study. The PDB ID of the MCL-1 protein (5FDR) was retrieved from the Protein Data Bank (https://www.rcsb.org/structure/5FDR) with a small molecule inhibitor. The resolution of the structure is at 2.60 Å. Indian Medicinal Plants, Phytochemistry and Therapeutics (IMPPAT 2.0) database was utilized to identify relevant phytochemicals of the Pinnaceae family. 170 phytochemicals with the potential of inhibiting MCL-1 protein were retrieved. Molecular docking was performed using Molegro Virtual Docker 2013 V6.0. ProteinPlus server was used to show the 2D interactions between ligands and protein. From the docking study of the 170 phytochemicals, 10 phytochemicals show high MolDock Score between -120.39 to -144.272. Pharmacokinetics study using the SwissAdme server reveals 3 compounds (IMPHY000001, IMPHY003007, and IMPHY012983) with no violation of the Lipinski’s rule of 5, thereby rending them to have high drug-likeness property. The findings of this study suggest that phytochemicals from the Pinnaceae family especially IMPHY000001, IMPHY003007, and IMPHY012983 have the potential to be 

A therapeutic agent against breast cancer. Further research is needed to validate these findings in experimental and clinical settings