Integrative Genomic and Computational Drug Discovery Approach to Unveil Key Pathways and Therapeutic Targets in Coronary Artery Disease

Integrative Genomic and Computational Drug Discovery Approach to Unveil Key Pathways and Therapeutic Targets in Coronary Artery Disease | 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 Integrative Genomic and Computational Drug Discovery Approach to Unveil Key Pathways and Therapeutic Targets in Coronary Artery Disease Ajit Kulkarni, Basavaraj Vastrad, Shivaling Pattanashetti, Chanabasayya Vastrad, and 1 more This is a preprint; it has not been peer reviewed by a journal.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-8072940/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 Coronary artery disease (CAD) is the most common cardiovascular disorder and the leading cause of heart-related deaths in world. Increasing molecular targets have been discovered for CAD and CAD-related complications prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might help the diagnosis and treatment of CAD and CAD-related complications. We searched next generation sequencing (NGS) dataset (GSE202625) and identified differentially expressed genes (DEGs) by comparing CAD and normal control samples using DESeq2. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g:Profiler online database. The protein-protein interaction (PPI) network and modules were constructed and analyzed. MiRNA-hub gene regulatory network, TF-hub gene regulatory network and drug-hub gene interaction network constructed and analysis were performed to use to predict hub genes, miRNAs, TFs and drug molecules. Receiver operating characteristic (ROC) curve analysis was used to predict the diagnostic effectiveness of the hub genes. Finally, molecular docking and ADMET studies were performed for phytoconstituents. A total of 118 DEGs (479 up regulated genes and 479 down regulated genes) were detected. The GO enrichment analysis indicated that the DEGs most significantly enriched in cellular response to stimulus and biosynthetic process. The REACTOME pathway enrichment analysis revealed that the DEGs were most significantly enriched in immune system and eukaryotic translation elongation. PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network analysis demonstrated that EGR1, SIRT1, STAT1, LRRK2, HIF1A, CSNK2B, RPS3, RPS2, RPS4X and HDAC11 were the hub genes. Drug molecules were predicted including Resveratrol, Methyltrienolone, Sevoflurane and Omacetaxinemepesuccinate for treatment of CAD. Molecular docking analysis revealed that Isocryptomerin was the main active compounds with good binding activities to the SIRT1 and ERG1. On the whole, the findings of this study enhance our understanding of the potential molecular mechanisms of CAD and CAD-related complications, and provide potential targets for further research. Coronary artery disease Bioinformatics analysis Differentially expressed genes Biomarkers Protein-protein network analysis Molecular docking Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryTableS1.docx SupplementaryTableS2.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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8072940","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":542396207,"identity":"610295b4-6d7f-457c-a5ec-71ea7ed34077","order_by":0,"name":"Ajit Kulkarni","email":"","orcid":"","institution":"VGK Heart Institute, Raichur -584101, Karanataka, India.","correspondingAuthor":false,"prefix":"","firstName":"Ajit","middleName":"","lastName":"Kulkarni","suffix":""},{"id":542396208,"identity":"628ecdf0-8abb-4f5f-aafd-9c8a4edd3143","order_by":1,"name":"Basavaraj Vastrad","email":"","orcid":"","institution":"Department of Pharmaceutical Chemistry, K.L.E. 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Disease","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Coronary artery disease, Bioinformatics analysis, Differentially expressed genes, Biomarkers, Protein-protein network analysis, Molecular docking","lastPublishedDoi":"10.21203/rs.3.rs-8072940/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8072940/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCoronary artery disease (CAD) is the most common cardiovascular disorder and the leading cause of heart-related deaths in world. Increasing molecular targets have been discovered for CAD and CAD-related complications prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might help the diagnosis and treatment of CAD and CAD-related complications. We searched next generation sequencing (NGS) dataset (GSE202625) and identified differentially expressed genes (DEGs) by comparing CAD and normal control samples using DESeq2. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g:Profiler online database. The protein-protein interaction (PPI) network and modules \u0026nbsp;were constructed and analyzed. MiRNA-hub gene regulatory network, TF-hub gene regulatory network and drug-hub gene interaction network constructed and analysis were performed to use to predict hub genes, miRNAs, TFs and drug molecules. Receiver operating characteristic (ROC) curve analysis was used to predict the diagnostic effectiveness of the hub genes. Finally, molecular docking and ADMET studies were performed for phytoconstituents. A total of 118 DEGs (479 up regulated genes and 479 down regulated genes) were detected. The GO enrichment analysis indicated that the DEGs most significantly enriched in cellular response to stimulus and biosynthetic process. The REACTOME pathway enrichment analysis revealed that the DEGs were most significantly enriched in immune system and eukaryotic translation elongation. PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network analysis demonstrated that EGR1, SIRT1, STAT1, LRRK2, HIF1A, CSNK2B, RPS3, RPS2, RPS4X and HDAC11 were the hub genes. Drug molecules were predicted including Resveratrol, Methyltrienolone, Sevoflurane and Omacetaxinemepesuccinate for treatment of CAD. Molecular docking analysis revealed that Isocryptomerin was the main active compounds with good binding activities to the SIRT1 and ERG1. On the whole, the findings of this study enhance our understanding of the potential molecular mechanisms of CAD and CAD-related complications, and provide potential targets for further research.\u003c/p\u003e","manuscriptTitle":"Integrative Genomic and Computational Drug Discovery Approach to Unveil Key Pathways and Therapeutic Targets in Coronary Artery Disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-12 01:45:29","doi":"10.21203/rs.3.rs-8072940/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a01d12c8-5612-4567-869c-61a82031e855","owner":[],"postedDate":"November 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-28T08:42:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-12 01:45:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8072940","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8072940","identity":"rs-8072940","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}