Virtual Screening and Molecular Dynamics Prioritisation of Natural-Product NUDT1 Inhibitors for Colorectal Cancer
Keywords:
NUDT1, MTH1, colorectal cancer, virtual screening, molecular dynamics, natural productsAbstract
Background: Oxidative nucleotide sanitisation through NUDT1/MTH1 can support tumour-cell survival under persistent redox stress, creating an attractive target for small-molecule discovery.
Objective: This study screened a chemically diverse natural-product library to identify candidates with favourable predicted binding, developability and dynamic stability against human NUDT1.
Methods: A curated library of 2,480 natural and nature-inspired compounds was filtered by physicochemical alerts, docked against the catalytic pocket of NUDT1, and rescored using consensus docking. The highest-ranked 25 ligands underwent ADMET prediction; six were advanced to 100-ns molecular-dynamics simulations with MM/GBSA calculations. Ligand–protein contacts, RMSD, RMSF, radius of gyration and hydrogen-bond persistence were evaluated against a reference inhibitor.
Results: Twelve compounds achieved docking energies below -9.0 kcal/mol. NP-147 and NP-922 produced the most stable trajectories, with protein–ligand RMSD values of 1.76±0.24 Å and 1.91±0.29 Å, respectively. NP-147 maintained catalytic-pocket contacts with Asp120 and Phe72 for more than 70% of simulation frames and showed a mean MM/GBSA binding energy of -42.8±5.6 kcal/mol. Both candidates met the predefined oral-drug-likeness filters, while NP-147 generated fewer predicted hepatotoxicity and hERG alerts than the reference compound. A sensitivity analysis using an alternative protonation state preserved the ranking of the two leading candidates.
Conclusion: The screening workflow identified two natural-product scaffolds with reproducible computational evidence of NUDT1 engagement. NP-147 showed the strongest overall profile and warrants biochemical enzyme testing followed by colorectal-cancer cell validation. The findings also demonstrate how sequential docking, pharmacokinetic filtering and dynamic simulation can reduce false-positive prioritisation before experimental work.
Publication format: research abstract. No full-text manuscript accompanies this record.
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