Identification of potential inhibitors of 3‑mercaptopyruvate sulfurtransferase with a deep-learning based screening of natural products

Clinical Snapshot

Key Findings

• P Value: Not reported for statistical comparisons

• Effect Size: Methylophiopogonanone A: 40.3% cell viability reduction at 25 µM; L-asarinin: 26.3% reduction at 25 µM

• Primary Outcome: Identification of natural product 3-MST inhibitors with IC50 values in low micromolar range

• Nnt Or Sensitivity: IC50 = 5.83 µM for most potent compound (Methylophiopogonanone A)

• Confidence Interval: IC50 values: Methylophiopogonanone A 5.83 ± 0.69 µM; L-asarinin 19.11 ± 3.37 µM

Clinical Application

Very early stage - requires medicinal chemistry optimization, safety studies, and clinical trials Would require TGA approval pathway for novel therapeutics; natural product origin may facilitate development under existing regulatory frameworks for complementary medicines initially Patients with cancers where 3-MST represents a therapeutic target, pending extensive further development

Abstract

3-Mercaptopyruvate sulfurtransferase (3-MST), a key enzyme in sulfur metabolism, has recently gained attention as a potential anticancer target. However, reported 3-MST inhibitors remain limited, motivating the exploration of new scaffolds such as natural products. In this study, a library of 3744 natural products was virtually screened against human 3-MST using DiffDock (diffusion-model-based docking) followed by AutoDock Vina docking. Top-ranking candidates were further analyzed via molecular dynamics simulations and Molecular Mechanics Poisson-Boltzmann Surface Area binding free energy calculations. Methylophiopogonanone A (4), Daphnoretin (5), and L-asarinin (9) exhibited stable binding with favorable energetics, displaying binding free energies comparable to the reference ligand 7NC301. Binding mode analyses revealed that Methylophiopogonanone A primarily engaged in hydrophobic interactions, whereas Daphnoretin and L-asarinin formed extensive polar contacts, accompanied by higher desolvation penalties. In vitro cytotoxicity assays showed that Methylophiopogonanone A and L-asarinin reduced HCT116 cell viability by 40.3% and 26.3% at 25 µM, which is consistent with their inhibitory of 3-MST with IC50 = 5.83 ± 0.69 µM and IC50 = 19.11 ± 3.37 µM, respectively. These results suggested that the natural products identified in this study represent promising scaffolds for further optimization as potential 3-MST inhibitors. This work provides an AI-guided natural-product screening workflow for 3-MST and delivers prioritized inhibitor scaffolds for subsequent optimization and experimental validation.

References

1. 1.Wang, C., Chen, X., Yin, Y., Ding, H., Sha, Z., Zhu, Y., Xue, X., & Zhang, D. (2026). Identification of potential inhibitors of 3‑mercaptopyruvate sulfurtransferase with a deep-learning based screening of natural products. Journal of Computer-Aided Molecular Design. https://doi.org/10.1074/jbc.M307187200