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In silico evaluation of novel metabolites from Tricholoma pardinum: Insights into drug-likeness, toxicity and target interactions via molecular docking and dynamics.

Aug 2026 · Technology and Health Care · pp. 9287329261472774 · 0 citations · 31 references
Medicine

TL;DR

Six previously uncharacterized metabolites isolated from the poisonous mushroom Tricholoma pardinum are investigated using an integrated in silico approach to evaluate their therapeutic potential, highlighting the potential of metabolites from T. pardinum as novel scaffolds for developing anticancer agents targeting PARP1 and PIP4K2γ.

Abstract

Natural products from fungi are a significant source for drug discovery. This study investigates six previously uncharacterized metabolites isolated from the poisonous mushroom Tricholoma pardinum using an integrated in silico approach to evaluate their therapeutic potential. Pharmacokinetic (ADMET) profiling predicted varied drug-likeness and toxicity profiles, with several compounds showing potential to cross the blood-brain barrier. Molecular docking and MM-GBSA calculations identified compound 1 as a potent inhibitor of Poly [ADP-ribose] polymerase 1 (PARP1), with a strong binding affinity (XP GScore: -6.756; ΔGbind: -48.75 kcal/mol). This interaction is anchored by a robust network of hydrogen bonds with key residues, including ASP914, CYS908, and THR866. Similarly, compound 6 emerged as a strong binder to Phosphatidylinositol 5-phosphate 4-kinase type-2 gamma (PIP4K2γ) (XP GScore: -7.705; ΔGbind: -45.94 kcal/mol), with its binding stabilized by extensive hydrophobic interactions complemented by a critical hydrogen bond with the residue Methionine 206 (MET206). Subsequent 100 ns molecular dynamics simulations confirmed the high stability of both protein-ligand complexes, validating the persistence of these key interactions. These computational findings highlight the potential of metabolites from T. pardinum as novel scaffolds for developing anticancer agents targeting PARP1 and PIP4K2γ, warranting further experimental validation.

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