What question did this study set out to answer?

To discover and validate novel natural BACE1 inhibitors by combining machine learning predictive models with enzymatic assays and cellular experiments for Alzheimer's disease intervention.

September 17, 2026ACS OmegaOpen Access

Machine Learning-Guided Discovery of Natural BACE1 Inhibitors with Enzymatic and Cellular Validation

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Authors

YBYiming BaiAcademy of Medical Sciences JZJun ZhaoChangzhi Medical College SZShurong ZhangChinese Academy of Medical Sciences & Peking Union Medical College

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Implication

In vitro and computational screening reveals natural BACE1 inhibitors in cellular models, highlighting theaflavin-3,3′-digallate as a promising candidate for Alzheimer's disease.

Key Points

To discover and validate novel natural BACE1 inhibitors by combining machine learning predictive models with enzymatic assays and cellular experiments for Alzheimer's disease intervention.
Constructed nine machine learning predictive models using Naïve Bayes and Recursive Partitioning algorithms to screen an in-house library of 452 natural compounds.
Assayed 171 computationally prioritized compounds via fluorescence resonance energy transfer (FRET)-based enzymatic screening.
Evaluated lead compounds in APPswe-HEK293T cells for extracellular Aβ1–42 secretion and conducted molecular docking to analyze binding modes.
Enzymatic testing showed 33 compounds achieved >50% BACE1 inhibition at 50 μg/mL, with five compounds demonstrating IC50 values below 50 μM: Theaflavin-3,3′-digallate, γ-mangostin, Licoagrochalcone B, Chicoric acid, and Resveratrol.
Theaflavin-3,3′-digallate significantly reduced extracellular Aβ1–42 secretion in APPswe-HEK293T cells.
Molecular docking demonstrated that Theaflavin-3,3′-digallate forms stable hydrogen-bond and hydrophobic interactions within the BACE1 active site.

Cite This Study

Bai et al. (2026) studied this question.

synapsesocial.com/papers/6aabb68c5f706d05830e5149 https://doi.org/10.1021/acsomega.6c07963

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Implication

In vitro and computational screening reveals natural BACE1 inhibitors in cellular models, highlighting theaflavin-3,3′-digallate as a promising candidate for Alzheimer's disease.

Machine Learning-Guided Discovery of Natural BACE1 Inhibitors with Enzymatic and Cellular Validation

Discussion

Member takes

Implication

Key Points

Cite This Study

Machine Learning-Guided Discovery of Natural BACE1 Inhibitors with Enzymatic and Cellular Validation

Discussion

Member takes

Implication

Key Points

Cite This Study

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