Single-Cell RNA Sequencing Analysis of Key Candidate Genes; Molecular Modeling and Docking-Based Therapeutic Molecules Exploration of Nature Derived Phytoconstituents for Type 2 Diabetes Mellitus.

Single-Cell RNA Sequencing Analysis of Key Candidate Genes; Molecular Modeling and Docking-Based Therapeutic Molecules Exploration of Nature Derived Phytoconstituents for Type 2 Diabetes Mellitus. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Single-Cell RNA Sequencing Analysis of Key Candidate Genes; Molecular Modeling and Docking-Based Therapeutic Molecules Exploration of Nature Derived Phytoconstituents for Type 2 Diabetes Mellitus. Basavaraj Vastrad, Shivaling Pattanashetti, Chanabasayya Vastrad, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8562423/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Type 2 diabetes mellitus (T2DM) is common metabolic disorder in the middle age population, conferring a heavy worldwide burden. Exact underlying common molecular mechanism of T2DM occurrence is unclear. The purpose of this study is to further explore the molecular mechanism of T2DM through integrated bioinformatic analysis. In this investigation, single cell RNA-sequencing data GSE214517 obtained from the Gene Expression Omnibus (GEO) database, was used for investigating the biomarkers and molecular mechanisms of T2DM. Differentially expressed genes (DEGs) were picked out by limma R bioconductor package. Gene Ontology (GO) and REACTOME pathway enrichment analysis, protein-protein interaction (PPI) network analysis, module analysis, miRNA-hub gene regulatory network analysis, TF-hub gene regulatory network analysis, drug-hub gene interaction network analysis, receiver operating characteristic (ROC) curves analysis, homology modeling, molecular docking and ADMET analysis were performed. In total, 957 DEGs, containing 478 up-regulated genes and 479 down-regulated genes, were identified. The DEGs were mainly enriched in protein metabolic process, anatomical structure development, endomembrane system, nucleoplasm, catalytic activity, ion binding, metabolism of carbohydrates and signal transduction. The hub-genes of RPS28, RUVBL1, RPS29, MRPS12, RPS21, KRAS, RPS3A, JUN, RPL9 and GNAQ might be associated with T2DM. The predicted miRNAs (e.g., hsa-mir-325 and hsa-mir-181c-3p), TFs (STAT4 and NUCKS1) and drug molecules (Becaplermin and Phosphorylisopropane) were found to be significantly correlated with T2DM. Molecular docking analysis revealed that Diosgenin binds to KEAP1 with a binding energy of -9.70 and Diosgenin binds to INSIG2 with a binding energy of -9.81, indicating highly stable binding. This study distinguished hub genes and related signaling pathways that can potentially serve as diagnostic indicators and therapeutic biomarkers for T2DM, thereby improving understanding of the molecular mechanisms involved in T2DM. Bioinformatics Endocrinology & Metabolism Computational Biology Drug Discovery, Design, & Development Bioinformatics analysis Biomarkers Differentially expressed genes Type 2 diabetes mellitus Single cell RNA-sequencing Molecular docking Full Text Additional Declarations The authors declare no competing interests. Tables 1 to 10 are available in the Supplementary Files section. Supplementary Files TableF.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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