Inverse Degree-Based Topological Indices for QSPR Modeling of Anti-Babesiosis Drugs: A Computational Approach

Inverse Degree-Based Topological Indices for QSPR Modeling of Anti-Babesiosis Drugs: A Computational Approach | 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 Inverse Degree-Based Topological Indices for QSPR Modeling of Anti-Babesiosis Drugs: A Computational Approach Muhammad Ahsan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8735211/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 In this study, we investigate the utility of inverse degree-based topological indices in modeling the physicochemical properties of anti-babesiosis drugs via quantitative structure–property relationship (QSPR) analysis. Thirteen drug molecules were analyzed using indices such as M2-1, KCD2-1, GO2-1, and ISD-1. Linear regression was applied to correlate these indices with experimentally known properties, including molar refractivity, polarizability, boiling point, polar surface area, and molar volume. Statistical validation was conducted using the Shapiro–Wilk test and Q–Q plots to assess the normality of residuals, while cross-validation (CV R2) was used to evaluate generalization performance. The model predicting molar refractivity from M2-1 achieved the highest fit (R2 = 0.980), though some CV R2$ values suggested potential overfitting. This research contributes to computational drug discovery by demonstrating the predictive power of inverse topological indices, offering a promising framework for screening and evaluating new compounds for the treatment of babesiosis. Classification of Mathematics Subjects: 05C92, 05C09, 92E10 Inverse Degree based indices Babesia drugs Python Smiles Excel QSPR QSAR 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-8735211","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":593527521,"identity":"2eefeede-40d7-4ecd-97e4-5fc7edd29e45","order_by":0,"name":"Muhammad Ahsan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYDACCQY2KIv5AIgrQ4oWtgQQl4cULTwGYJKgDv7Zzc8e/qi5k8fff+bzqxs1FjwM7IePbsBryZ1j5sY8x54VSxw4u8065xjQYTxpaTfwaTGQSDCTZmA7nNhwsHebcQ4bUIsEjxkBLenfJH/8O5w4/zDPM+Ocf0RpyTGT4G07nLjhGA/z49w2IrRI3Mgpk+btO5y48QybGXNunwQPGyG/8M9I3yb549vhxHnnDz/+nPOtTo6f/fAxvFqQAZsEmCRWOQgwfyBF9SgYBaNgFIwcAAA8iEfIi0BSNwAAAABJRU5ErkJggg==","orcid":"","institution":"National Research University Higher School of Economics","correspondingAuthor":true,"prefix":"","firstName":"Muhammad","middleName":"","lastName":"Ahsan","suffix":""}],"badges":[],"createdAt":"2026-01-29 21:23:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8735211/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8735211/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103327894,"identity":"8d45ea31-75bf-4a4b-a2c5-565261fe4735","added_by":"auto","created_at":"2026-02-24 13:12:12","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1570539,"visible":true,"origin":"","legend":"","description":"","filename":"InverseDegreeBasedTopologicalIndicesforQSPRModelingofAntiBabesiosisDrugsAComputationalApproach6.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8735211/v1_covered_46bc97b9-6710-42c5-bf23-02181dd1ebce.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Inverse Degree-Based Topological Indices for QSPR Modeling of Anti-Babesiosis Drugs: A Computational Approach","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":"Inverse Degree based indices, Babesia drugs, Python, Smiles, Excel, QSPR, QSAR","lastPublishedDoi":"10.21203/rs.3.rs-8735211/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8735211/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this study, we investigate the utility of inverse degree-based topological indices in modeling the physicochemical properties of \u0026nbsp;anti-babesiosis drugs via quantitative structure–property relationship (QSPR) analysis. Thirteen drug molecules were analyzed using indices such as M2-1, KCD2-1, GO2-1, and ISD-1. Linear regression was applied to correlate these indices with experimentally known properties, including molar refractivity, polarizability, boiling point, polar surface area, and molar volume. Statistical validation was conducted using the Shapiro–Wilk test and Q–Q plots to assess the normality of residuals, while cross-validation (CV\u0026nbsp; R2) was used to evaluate generalization performance. The model predicting molar refractivity from M2-1 achieved the highest fit (R2 = 0.980), though some CV\u0026nbsp; R2$ values suggested potential overfitting. This research contributes to computational drug discovery by demonstrating the predictive power of inverse topological indices, offering a promising framework for screening and evaluating new compounds for the treatment of babesiosis.\u003c/p\u003e\n\u003cp\u003eClassification of Mathematics Subjects: 05C92, 05C09, 92E10\u003c/p\u003e","manuscriptTitle":"Inverse Degree-Based Topological Indices for QSPR Modeling of Anti-Babesiosis Drugs: A Computational Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-23 13:41:44","doi":"10.21203/rs.3.rs-8735211/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":"e9567b9f-632f-4630-95bf-f540bfbb4994","owner":[],"postedDate":"February 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-24T13:08:52+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-23 13:41:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8735211","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8735211","identity":"rs-8735211","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}