Integrated 2D- and 3D-QSAR Modeling Reveals Structural Determinants Governing the Bioactivity of Triazine Derivatives Against COPD

Integrated 2D- and 3D-QSAR Modeling Reveals Structural Determinants Governing the Bioactivity of Triazine Derivatives Against COPD | 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 Integrated 2D- and 3D-QSAR Modeling Reveals Structural Determinants Governing the Bioactivity of Triazine Derivatives Against COPD Ajay Singh, Sushil K. Kashaw, Ajay Kumar Verma This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7960180/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 Background The class of heterocyclic compounds known as triazine derivatives is significant and has the potential to treat chronic obstructive pulmonary disease (COPD). The identification of structural determinants and the prediction of bioactivity are made possible by Quantitative Structure–Activity Relationship (QSAR) approaches. This study evaluated the steric and hydrophobic contributions governing the activity of triazine derivatives using integrated 2D- and 3D-QSAR methodologies. Methods V-Life MDS was used to model a dataset of 34 triazine derivatives following energy minimisation using the Merck Molecular Force Field (MMFF). Partial Least Squares (PLS) regression with stepwise selection was used to create 2D-QSAR models, and k-Nearest Neighbour Molecular Field Analysis (kNN-MFA) was used to develop 3D-QSAR models. Z-score randomisation, F-test, r², q², and pred_r² were all used in the statistical validation. Results Strong predictivity was shown by the ideal 2D-QSAR Model (Model I) (r² = 0.7876, q² = 0.7146, pred_r² = 0.622). Descriptor analysis showed that while aliphatic CH₂ groups harmed potency, hydrophobic surface area and aromatic connectivity (Saa CHE-index) increased activity. With q2 = 0.7388 and pred_r2 = 0.4073, the 3D-QSAR model (k = 2) demonstrated good internal stability but moderate external predictivity. Important information about substitution patterns was provided by steric contour maps, which showed that bioactivity was favoured by decreased steric hindrance at lattice points S_952 and S_668. Conclusion The combined 2D- and 3D-QSAR results show that steric modulation, aromatic connectivity, and hydrophobic interactions are important activity determinants. The logical development of optimised triazine derivatives with improved therapeutic potential against COPD is supported by these findings. Triazines Quantitative Structure–Activity Relationship Chronic Obstructive Pulmonary Disease Molecular Field Analysis Partial Least Squares Analysis Hydrophobic Interactions Full Text Additional Declarations No competing interests reported. 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-7960180","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":561167687,"identity":"42290c77-a1ea-45d1-8f52-80aed063e5a7","order_by":0,"name":"Ajay Singh","email":"","orcid":"","institution":"Sai College of Pharmacy","correspondingAuthor":false,"prefix":"","firstName":"Ajay","middleName":"","lastName":"Singh","suffix":""},{"id":561167688,"identity":"da51b8b1-d081-420f-aea4-6fe05e09ad9f","order_by":1,"name":"Sushil K. 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COPD","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Triazines, Quantitative Structure–Activity Relationship, Chronic Obstructive Pulmonary Disease, Molecular Field Analysis, Partial Least Squares Analysis, Hydrophobic Interactions","lastPublishedDoi":"10.21203/rs.3.rs-7960180/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7960180/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe class of heterocyclic compounds known as triazine derivatives is significant and has the potential to treat chronic obstructive pulmonary disease (COPD). The identification of structural determinants and the prediction of bioactivity are made possible by Quantitative Structure\u0026ndash;Activity Relationship (QSAR) approaches. This study evaluated the steric and hydrophobic contributions governing the activity of triazine derivatives using integrated 2D- and 3D-QSAR methodologies.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eV-Life MDS was used to model a dataset of 34 triazine derivatives following energy minimisation using the Merck Molecular Force Field (MMFF). Partial Least Squares (PLS) regression with stepwise selection was used to create 2D-QSAR models, and k-Nearest Neighbour Molecular Field Analysis (kNN-MFA) was used to develop 3D-QSAR models. Z-score randomisation, F-test, r\u0026sup2;, q\u0026sup2;, and pred_r\u0026sup2; were all used in the statistical validation.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eStrong predictivity was shown by the ideal 2D-QSAR Model (Model I) (r\u0026sup2; = 0.7876, q\u0026sup2; = 0.7146, pred_r\u0026sup2; = 0.622). Descriptor analysis showed that while aliphatic CH₂ groups harmed potency, hydrophobic surface area and aromatic connectivity (Saa CHE-index) increased activity. With q2\u0026thinsp;=\u0026thinsp;0.7388 and pred_r2\u0026thinsp;=\u0026thinsp;0.4073, the 3D-QSAR model (k\u0026thinsp;=\u0026thinsp;2) demonstrated good internal stability but moderate external predictivity. Important information about substitution patterns was provided by steric contour maps, which showed that bioactivity was favoured by decreased steric hindrance at lattice points S_952 and S_668.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe combined 2D- and 3D-QSAR results show that steric modulation, aromatic connectivity, and hydrophobic interactions are important activity determinants. The logical development of optimised triazine derivatives with improved therapeutic potential against COPD is supported by these findings.\u003c/p\u003e","manuscriptTitle":"Integrated 2D- and 3D-QSAR Modeling Reveals Structural Determinants Governing the Bioactivity of Triazine Derivatives Against COPD","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-17 03:39:01","doi":"10.21203/rs.3.rs-7960180/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":"fc005c25-14a5-4032-9ba9-35acd5099a2c","owner":[],"postedDate":"December 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-01T08:41:39+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-17 03:39:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7960180","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7960180","identity":"rs-7960180","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}