Sterilized fermented drink targets obesity and type 2 diabetes in a computer study

Sterilized fermented drink targets obesity and type 2 diabetes in a computer study

By analyzing the drinks people would actually consume, researchers reveal how sterilized plant ferments could theoretically affect insulin, lipids and inflammatory pathways, laying the groundwork for future experimental testing.

A recent study in the journalScientific reportsidentified, characterized and evaluated bioactive molecules in a terminally sterilized, probiotic fermented, medicinal food homologue (MFH) beverage that may counteract obesity and type 2 diabetes (T2D).in silicoMulti-target modulation of metabolic inflammation.

Global burden of obesity and type 2 diabetes

More than one in eight adults suffer from obesity and over 500 million suffer from type 2 diabetes, a syndemic disease that leads to heart disease, kidney failure and loss of productivity. Families feel this at the grocery checkout and at the pharmacy counter. Effective drugs such as glucagon-like peptide-1 (GLP-1) receptor agonists work, but costs, side effects, and access limit practical use.

Foods and ferments guided by Traditional Chinese Medicine (TCM) are inexpensive, shelf-stable options that people can drink daily.

Yet most research characterizes raw herbs rather than the final sterilized beverage that people actually consume. Integrated chemical and systems analyzes are required to clarify which molecules survive processing and how they affect insulin, lipids, and inflammation.

Further research should test these mechanisms in cells and humans, as current findings are based solely on computational analyses.

Profiling of bioactives in a sterilized MFH beverage

Researchers analyzed a ready-to-drink, terminally sterilized fermented beverage (FH03FS) made from five MFH plants such as Radix ofMillettia speciosaLotus leaf, monk fruit, mandarin peel andCinnamomi cortex. For safety reasons, they are first heat treated and then fermentedLacticaseibacillus paracaseiAndLactiplantibacillus plantarumand finally pasteurized for stability.

Phytochemicals were profiled using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Compounds with a relative abundance of >0.1% were evaluated for oral bioavailability and drug-likeness.

In silicoAbsorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions included gastrointestinal (GI) absorption, blood-brain barrier permeability, P-glycoprotein (P-gp) substrate status, and cytochrome P450 (CYP) inhibition.

Systems analyzes used network pharmacology to intersect predicted compound targets with obesity and T2D gene sets, protein-protein interaction networks (PPI), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyzes to define core nodes and pathways.

Molecular docking quantified binding (kcal/mol) between prioritized compounds and hub proteins, molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA), guided molecular dynamics (MD) simulations (100 ns) assessed stability using root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), and solvent accessible surface area (SASA).

Together, this pipeline connects “what’s in the bottle” to “what it might do” in metabolic-inflammatory networks, as predicted by computational models rather than experimental tests.

Chemical profiling identifies ten important bioactives

UPLC-MS/MS detected 3,387 molecules from phenylpropanoids/polyketides, organoheterocycles, lipids, benzoids and alkaloids. This resulted in ten pharmacokinetically favorable active ingredients, dominated by aporphine alkaloids (nuciferin, asimilobin) and flavonoids (isosinensetin, morin, 5,7,3′,4′-tetramethoxyflavone, 7,4′-di-O-methylapigenin, 3,3′,4′,5,6,7,8-heptamethoxyflavone, 5-desmethylsinensetin), plus (S)-coclaurin and the lignan eudesmin.

ADMET suggested high gastrointestinal absorption and generally low safety concerns; Most compounds did not trigger human ether-à-go-go related gene (hERG) or Ames test (AMES) mutagenicity indicators, while some showed CYP interactions that should be monitored in polypharmacy.

Systems modeling links bioactives to metabolic inflammation

Target prediction intersected 338 putative composite targets with thousands of obesity and T2D genes, yielding 144 overlapping nodes. The network topology distilled 20 core proteins central to metabolic inflammation and insulin signaling, including peroxisome proliferator-activated receptor gamma (PPARG), estrogen receptor 1 (ESR1), RAC alpha-serine/threonine protein kinase (AKT1), tumor necrosis factor (TNF), interleukin-1 beta (IL1B), signal transducer and activator of transcription 3 (STAT3), apoptosis regulator B-cell lymphoma 2 (BCL2), cellular tumor antigen p53 (TP53), proto-oncogene tyrosine protein kinase Src (SRC), mechanistic target of rapamycin (MTOR), and matrix metalloproteinases (MMP2/MMP9).

GO and KEGG enrichment highlighted signaling pathways relevant to the biology of metabolic diseases, including insulin resistance, lipid and atherosclerosis signaling, advanced glycation end products receptor for AGE (AGE-RAGE) signaling pathways, and core cascades such as phosphoinositide 3-kinase-Akt (PI3K-Akt), mitogen-activated protein kinase (MAPK), cyclic adenosine monophosphate (cAMP), TNF and estrogen signaling.

These networks reflect statistically enriched pathway associations and plausibly link a daily drink to enhanced glucose transport via glucose transporter type 4 (GLUT4), reduced hepatic gluconeogenesis via forkhead box protein O1 (FOXO1), attenuated inflammatory signaling, and altered lipid handling in computational network models.

Docking and simulations demonstrate binding stability

Molecular docking supported multi-target engagement. Morin bound ESR1, BCL2, and SRC with high affinity; Several flavonoids and (S)-coclaurin promoted PPARG, and 5-desmethylsinensetin targeted AKT1. Notably, nuciferin showed broad predicted binding across multiple metabolic centers.

Two representative complexes were subjected to MD simulations. Morin-ESR1 stabilized rapidly (RMSD ≈ 0.26 nm), retained hydrogen bonds, and exhibited van der Waals-driven binding through MM-PBSA with consistent SASA and Rg, characteristics of a low-energy binding pose.

Asimilobin-PPARG showed similar stability (RMSD ≈ 0.28 nm) with larger electrostatic contributions and persistent hydrophobic contacts after minor optimization in the middle of the trajectory.

Taken together, the trajectories revealed a single deep minimum in the free energy landscape, indicating persistent binding modes within the simulated systems.

Potential for accessible, fermented metabolic support

In communities balancing food budgets against pharmacy bills, a shelf-stable fermented beverage that survives sterilization with intact aporphins and flavonoids is needed and thatin silicoinvolves PPARG, AKT1, ESR1, and inflammatory nodes, providing a plausible, accessible addition to diet and exercise as a hypothesis generated by computational analysis. It does not replace GLP-1 or sodium-glucose cotransporter-2 (SGLT2) therapies, but could help households manage glucose, lipids and inflammation in the right direction if future experimental and clinical studies confirm the biological relevance.

Conclusions and future experimental directions

A terminally sterilized MFH fermented beverage (FH03FS) contains aporphine alkaloids and flavonoids with favorable ADMET profiles, high predicted GI absorption, and multi-target effects across insulin, lipid, and inflammatory pathways identified using integrated methodsin silicoApproaches.

Network pharmacology, molecular docking and 100 ns MD simulations (with MM-PBSA) indicate stable binding to core nodes such as PPARG, ESR1, AKT1, TNF and others, aligned with KEGG insulin resistance pathways, PI3K-Akt, MAPK and AGE-RAGE signaling.

These computational results generate testable hypotheses that a daily, affordable beverage could complement lifestyle modification and conventional care, pending validation through experimental and human studies. Next steps should include biophysical testing, cell modeling and human trials to confirm efficacy, safety, dose and interactions in real-world settings.

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