Multiscale Computational Design of PIM-۳ Kinase Inhibitors: ۳D-QSAR, Docking, MD, and QM Analysis

A comprehensive computational approach was employed to design and evaluate novel indole-based inhibitors targeting PIM-۳ kinase, an attractive target for anticancer drug development. Using the experimental IC₅₀ values of ۳۵ compounds, two ۳D-QSAR models—CoMFA and CoMSIA—were developed and statistically validated (CoMFA: Q۲ = ۰.۵۰, R۲ = ۰.۷۱, and r۲test = ۰.۶۸; CoMSIA: Q۲ = ۰.۶۳, R۲ = ۰.۹۵ and r۲test = ۰.۶۶). A library of ۱,۳۳۱ novel compounds, designed by modifying substituents at three key positions on the indole scaffold and predicted by the models, was subjected to virtual screening. Molecular docking identified key binding interactions within the PIM-۳ kinase active site and was also used to screen the compound library. After integrating three sets of computational predictions, indole derivatives were identified that were common among the top ۱۰۰ active compounds ranked by each approach. Subsequent ۴۰۰ ns all-atom molecular dynamics (MD) simulations revealed that the selected compound–protein complexes remained structurally stable, as confirmed by multiple stability metrics. Quantum mechanical (QM) calculations were employed to determine binding energies and analyze electron density (ρ) at intermolecular bond critical points (BCPs). A strong correlation was observed between the total electron density (ρ) at bond critical points (BCPs) and the interaction energies, reinforcing the reliability of the findings. ADME analysis confirmed that the selected compounds exhibit favorable drug-like characteristics and pharmacokinetic profiles. This study provides valuable knowledge for the rational design of potent PIM-۳ kinase inhibitors.

کلیدواژه ها:

Indole derivatives ، ۳D-QSAR models ، Virtual screening ، Molecular docking ، Molecular Dynamics Simulation ، Quantum mechanical calculation