Design of Colchicine-Based Tubulin Inhibitors as Anticancer Agents by In Silico Analysis of Colchicine-Based Tubulin Inhibitors: 3D-QSAR, Molecular Docking, and Molecular Dynamics Simulations for Anticancer Drug Development.

This study explores colchicine analogues as potential anticancer agents by analyzing their interactions with the tubulin-colchicine complex. A robust three-dimensional quantitative structure-activity relationship (3D-QSAR) model (r = 0.9438, q = 0.8915) identified key substituent regions influencing biological activity. Among 720 evaluated colchicine derivatives, 25 compounds exhibited superior binding affinities compared to colchicine. Compounds S3, S22, and a reference (Colchicine) were selected for molecular dynamics (MD) simulations, which confirmed stable binding interactions over 100 ns. Root mean square deviation and RMSF analyses highlighted key residues contributing to ligand stability within the protein-ligand complexes. Atom-based QSAR and molecular docking were used to design new chemical entities (NCEs) with drug-like properties. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) screening ensured favorable pharmacokinetic and pharmacodynamic profiles, including optimal molecular weight, hydrogen bonding, and blood-brain barrier permeability. Compounds S3 and S22 demonstrated the most promising results, with strong stability, binding characteristics, and drug-likeness. This computational approach indicates colchicine derivatives as viable candidates for anticancer drug development by disrupting tubulin dynamics and inducing cell cycle arrest. The findings support the potential of these derivatives to serve as the foundation for future anticancer therapies, highlighting their stability, binding efficiency, and favorable pharmacological profiles. Colchicine derivatives show potential as anticancer drugs by disrupting tubulin dynamics.