Screening of Natural Inhibitors from <i>Pleurotus ostreatus</i> against PHGDH for Enhancing Antiviral Innate Immunity through Mendelian Randomization, Machine Learning, Molecular Docking, Molecular Dynamics Simulation, and Binding Free Energy Calcula

The human innate immune response plays a critical role in limiting and controlling viral infections. Consequently, therapeutic strategies that promote or modulate innate antiviral immunity are regarded as promising approaches to combating viral pathogens. Recent animal studies suggest that inhibition of serine biosynthesis may enhance host antiviral innate immunity, thereby providing novel targets for drug development. This study aims to identify natural compounds derived from <i>Pleurotus ostreatus</i> that inhibit serine biosynthesis and consequently strengthen antiviral innate immunity using a machine learning model integrated with molecular-docking-based virtual screening. First, we identified PHGDHone of the key enzymes in the serine biosynthesis pathwayas a potential therapeutic target through Mendelian randomization (MR) analysis. The MR results provided suggestive evidence that PHGDH inhibition is associated with elevated IFN-β levels (OR = 0.862, 95% CI: 0.786-0.955, <i>p</i> = 0.004), supporting its immunomodulatory role and highlighting its therapeutic potential. Next, we developed a deep neural network model based on RDKit descriptors to predict the inhibitory activity of natural compounds from <i>Pleurotus ostreatus</i> against PHGDH, achieving a sensitivity of 96.3%, specificity of 98.2%, F1 score of 0.976, accuracy of 97.2%, and AUROC of 0.997. By combination of this predictive model with molecular-docking-based virtual screening, five compounds (FDB024162, FDB024165, FDB095731, FDB095733, and FDB095735) were prioritized as potent PHGDH inhibitors. Furthermore, molecular dynamics simulations and binding free energy calculations revealed that these compounds form stable complexes with PHGDH and bind specifically to key residues within the cofactor-binding pocket. In conclusion, the identified natural compounds exhibit a strong potential to inhibit PHGDH and thereby enhance antiviral innate immunity. Further experimental validation is warranted to fully characterize their functional contributions to innate immune activation.

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Journal
ACS Omega
Published
2026-01-27
DOI
https://doi.org/10.1021/acsomega.5c13179
Primary Topic
interferon and immune responses
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article
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article

Screening of Natural Inhibitors from Pleurotus ostreatus against PHGDH for Enhancing Antiviral Innate Immunity through Mendelian Randomization, Machine Learning, Molecular Docking, Molecular Dynamics Simulation, and Binding Free Energy Calcula

Kai Yang, Shaohua Xu
ACS Omega
interferon and immune responses
article

Screening of Natural Inhibitors from Pleurotus ostreatus against PHGDH for Enhancing Antiviral Innate Immunity through Mendelian Randomization, Machine Learning, Molecular Docking, Molecular Dynamics Simulation, and Binding Free Energy Calcula

Kai Yang, Shaohua Xu
article en

Abstract

The human innate immune response plays a critical role in limiting and controlling viral infections. Consequently, therapeutic strategies that promote or modulate innate antiviral immunity are regarded as promising approaches to combating viral pathogens. Recent animal studies suggest that inhibition of serine biosynthesis may enhance host antiviral innate immunity, thereby providing novel targets for drug development. This study aims to identify natural compounds derived from <i>Pleurotus ostreatus</i> that inhibit serine biosynthesis and consequently strengthen antiviral innate immunity using a machine learning model integrated with molecular-docking-based virtual screening. First, we identified PHGDHone of the key enzymes in the serine biosynthesis pathwayas a potential therapeutic target through Mendelian randomization (MR) analysis. The MR results provided suggestive evidence that PHGDH inhibition is associated with elevated IFN-β levels (OR = 0.862, 95% CI: 0.786-0.955, <i>p</i> = 0.004), supporting its immunomodulatory role and highlighting its therapeutic potential. Next, we developed a deep neural network model based on RDKit descriptors to predict the inhibitory activity of natural compounds from <i>Pleurotus ostreatus</i> against PHGDH, achieving a sensitivity of 96.3%, specificity of 98.2%, F1 score of 0.976, accuracy of 97.2%, and AUROC of 0.997. By combination of this predictive model with molecular-docking-based virtual screening, five compounds (FDB024162, FDB024165, FDB095731, FDB095733, and FDB095735) were prioritized as potent PHGDH inhibitors. Furthermore, molecular dynamics simulations and binding free energy calculations revealed that these compounds form stable complexes with PHGDH and bind specifically to key residues within the cofactor-binding pocket. In conclusion, the identified natural compounds exhibit a strong potential to inhibit PHGDH and thereby enhance antiviral innate immunity. Further experimental validation is warranted to fully characterize their functional contributions to innate immune activation.

ACS OmegaVol. 11(5)
Drug Trials America (US)
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interferon and immune responses
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Screening of Natural Inhibitors from <i>Pleurotus ostreatus</i> against PHGDH for Enhancing Antiviral Innate Immunity through Mendelian Randomization, Machine Learning, Molecular Docking, Molecular Dynamics Simulation, and Binding Free Energy Calcula — Kai Yang, Shaohua Xu · ACS Omega (2026) | TGRS Research Map | TGRS