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<p>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 (<b>4</b>), Daphnoretin (<b>5</b>), and L-asarinin (<b>9</b>) 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&#xa0;µM, which is consistent with their inhibitory of 3-MST with IC<sub>50</sub> = 5.83 ± 0.69&#xa0;µM and IC<sub>50</sub> = 19.11 ± 3.37&#xa0;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.</p> Graphical abstract <p></p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月4日

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  • Changkang Wang,
  • Xiao Chen,
  • Yu Yin,
  • Huimin Ding,
  • Zhensuo Sha,
  • Yifan Zhu,
  • Xin Xue,
  • Dongliang Zhang

摘要

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.

Graphical abstract