Discovery of natural MCL1 inhibitors using pharmacophore modelling, QSAR, docking, ADMET, molecular dynamics, and DFT analysis

Abstract

Mcl-1, a member of the Bcl-2 family, is a crucial regulator of apoptosis, frequently overexpressed in various cancers, including lung, breast, pancreatic, cervical, ovarian cancers, leukemia, and lymphoma. Its anti-apoptotic function allows tumor cells to evade cell death and contributes to drug resistance, making it an essential target for anticancer drug development. This study aimed to discover potent antileukemic compounds targeting Mcl-1. We selected diverse molecules from the BindingDB database to construct a structure-based pharmacophore model, which facilitated the virtual screening of 407,270 compounds from the COCONUT database. An e-pharmacophore model was developed using the co-crystallized inhibitor, followed by QSAR modeling to estimate IC₅₀ values and filter compounds with predicted values below the median. The top hits underwent molecular docking and MMGBSA binding energy calculations against Mcl-1, resulting in the selection of two promising candidates for further ADMET analysis. DFT calculations assessed their electronic properties, confirming favorable reactivity profiles of the screened compounds. Predictions for physicochemical and ADMET properties aligned with expected bioactivity and safety. Molecular dynamics simulations further validated their strong binding affinity and stability, positioning them as potential Mcl-1 inhibitors. Our comprehensive computational approach highlights these compounds as promising antileukemic agents, with future in vivo and in vitro validation recommended for further confirmation.