Type 2 diabetes mellitus (T2DM) is characterized by chronic metabolic dysfunction and low-grade inflammation. This study aimed to identify inflammation-associated molecular targets in T2DM and to computationally evaluate the therapeutic potential of Bacillus subtilis –derived metabolites targeting the key inflammatory cytokine IL6. Publicly available human RNA-sequencing datasets were retrieved from the NCBI Gene Expression Omnibus and analyzed using GEO2R to compare lean, obese, and T2DM groups. Common differentially expressed genes (DEGs) were identified and functionally enriched, with IL6 prioritized as a central inflammatory target. The IL6 protein structure was prepared for structure-based screening. Fifty-five B. subtilis metabolites were screened using PyRx, followed by ADME and toxicity prediction. Top-ranked compounds were further evaluated using molecular docking and 500 ns molecular dynamics simulations, with metformin as a reference. Free energy landscape (FEL) and dynamic cross-correlation matrix (DCCM) analyses assessed ligand-induced conformational stability and internal protein dynamics. A total of 179 common DEGs were identified, enriched in cytokine-mediated inflammatory pathways out of which IL6 emerged as a consistently upregulated hub gene. Three metabolites showed favorable pharmacokinetics, low predicted toxicity, and stronger binding affinities to IL6 than metformin. Docking revealed stable interactions with key IL6 residues, while molecular dynamics confirmed sustained complex stability. FEL and dynamic cross-correlation matrix analyses showed ligand-dependent differences in conformational stability while preserving internal dynamics. This integrative transcriptomics and structure-based analysis highlights B. subtilis metabolites as computationally predicted IL6-binding compounds involved in T2DM-associated inflammation, identifying them as promising candidates for further investigation towards potential healthcare and therapeutic applications.
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Muthukumar et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69fd7d4abfa21ec5bbf05cbf — DOI: https://doi.org/10.3389/fbinf.2026.1792877
Tarsha Muthukumar
S. Kumar
V. N. Vasudevan
Frontiers in Bioinformatics
Sri Ramachandra Institute of Higher Education and Research
Institute for Transfusion Medicine
Government Medical College
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