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Integrative AI-assisted modeling suggests CPPF binding at a composite [Formula: see text]/[Formula: see text]-tubulin
Jixin Yang1, Lisha Liang2, Dengchao Zhu2
1Data Science and Analytics Thrust, Information Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China.
Abstract:
Microtubules are dynamic cytoskeletal polymers assembled from α/β-tubulin heterodimers. Microtubules are validated targets for novel therapeutic drugs, yet therapeutic efficacy targeting them is often compromised by multidrug resistance (MDR). 5-(3-chlorophenyl)-N-(3-pyridinyl)-2-furamide (CPPF) is a novel microtubule-targeting anticancer agent which was found to disrupt microtubule growth in cells and inhibit tubulin polymerization in vitro. CPPF could suppress the growth of multidrug-resistant cell lines and demonstrate anti-tumor efficacy in animal models. However, the fundamental mechanism of how CPPF disrupts microtubule assembly remains unclear. To investigate this, we performed structure prediction using Protenix, RoseTTAFold All-Atom (RFAA) and Umol, as well as molecular dynamics (MD) simulations, using the human α/β-tubulin heterodimer (PDB ID: 5IJ0) for analyzing the interaction between CPPF and tubulin. Our results showed that CPPF binds at the α/β interface with dominant contributions from β-tubulin residues, particularly VAL236 and LEU253. In isolated-monomer comparisons, β-tubulin exhibited more favorable binding energetics and deeper, broader free-energy minima than α-tubulin. Supplementary simulations on the alternative β-tubulin conformational state (PDB: 6E7B; straight microtubule-lattice) indicated that CPPF binding is preserved across the two major β-tubulin conformations, with comparable MM-PBSA binding free energies. Taken together, these findings establish a plausible binding mode for CPPF at the α/β-tubulin interface, providing a structural hypothesis for understanding its anticancer potential against multidrug-resistant cancers. Experimental validation through binding assays or crystallography is warranted to further substantiate these computational insights.
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