A Directed Weighted Network-Based Method for Drug Combinations Identification Using Drug-Target and Inter-target Regulation

A Directed Weighted Network-Based Method for Drug Combinations Identification Using Drug-Target and Inter-target Regulation | 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 A Directed Weighted Network-Based Method for Drug Combinations Identification Using Drug-Target and Inter-target Regulation Shen Xiao, Yuhang Li, Jinwei Bai, Zhenhua Shen, Can Huang, Rongwu Xiang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6209063/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Dec, 2025 Read the published version in BMC Bioinformatics → Version 1 posted 4 You are reading this latest preprint version Abstract Background Drug combination is currently a promising solution in treating complex diseases due to its reducing toxicity and enhancing therapeutic efficacy. However, the accurate identification of drug combination effects remains challenging. Results In this work, we propose a novel directed weighted network-based approach to identify drug combinations. Specifically, the network is constructed on both drug-target and inter-target interactions, together with their directed regulation. The biological processes of drug effects propagation and attenuation are modeled, aiming to capture direct and indirect drug actions on targets. By assigning weights to nodes of regulatory effects, relative distances between node sets within network can thus be computed. These distances are then analyzed to discriminate the combinatorial efficacy of various drug combinations. Empirical evaluations validate a remarkable working performance of the proposed method. Compared to existing approaches, our method is a better alternative on the task of drug combination prediction. Conclusion The proposed method reports a creative and practical scheme for identifying drug combination effects. With the analysis of drug-target and inter-target regulatory relation, our method is more competitive in distinguishing the combinatorial efficacy, which mitigates the deficiencies of classical drug combination prediction models. Drug Combination Directed Weighted Network Drug-Target Interaction Inter-target Interaction Regulatory Effect Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 29 Dec, 2025 Read the published version in BMC Bioinformatics → Version 1 posted Reviewers invited by journal 15 Mar, 2025 Editor assigned by journal 12 Mar, 2025 Submission checks completed at journal 12 Mar, 2025 First submitted to journal 12 Mar, 2025 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-6209063","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":429253994,"identity":"b7fadf35-e29a-48ce-b5bf-c6339e359a0e","order_by":0,"name":"Shen Xiao","email":"","orcid":"","institution":"Shenyang Pharmaceutical University","correspondingAuthor":false,"prefix":"","firstName":"Shen","middleName":"","lastName":"Xiao","suffix":""},{"id":429253995,"identity":"f3d45907-463f-48e7-8a48-75f1515f2278","order_by":1,"name":"Yuhang Li","email":"","orcid":"","institution":"Shenyang Pharmaceutical 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Bioinformatics","twitterHandle":"@BMC_Bioinformatics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Drug Combination, Directed Weighted Network, Drug-Target Interaction, Inter-target Interaction, Regulatory Effect","lastPublishedDoi":"10.21203/rs.3.rs-6209063/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6209063/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDrug combination is currently a promising solution in treating complex diseases due to its reducing toxicity and enhancing therapeutic efficacy. However, the accurate identification of drug combination effects remains challenging.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn this work, we propose a novel directed weighted network-based approach to identify drug combinations. Specifically, the network is constructed on both drug-target and inter-target interactions, together with their directed regulation. The biological processes of drug effects propagation and attenuation are modeled, aiming to capture direct and indirect drug actions on targets. By assigning weights to nodes of regulatory effects, relative distances between node sets within network can thus be computed. These distances are then analyzed to discriminate the combinatorial efficacy of various drug combinations. Empirical evaluations validate a remarkable working performance of the proposed method. Compared to existing approaches, our method is a better alternative on the task of drug combination prediction.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe proposed method reports a creative and practical scheme for identifying drug combination effects. With the analysis of drug-target and inter-target regulatory relation, our method is more competitive in distinguishing the combinatorial efficacy, which mitigates the deficiencies of classical drug combination prediction models.\u003c/p\u003e","manuscriptTitle":"A Directed Weighted Network-Based Method for Drug Combinations Identification Using Drug-Target and Inter-target Regulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-17 06:05:39","doi":"10.21203/rs.3.rs-6209063/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-03-15T16:43:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-13T03:16:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-13T03:16:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Bioinformatics","date":"2025-03-12T06:18:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-bioinformatics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"binf","sideBox":"Learn more about [BMC Bioinformatics](http://bmcbioinformatics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/binf","title":"BMC Bioinformatics","twitterHandle":"@BMC_Bioinformatics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"07d9338a-e1a4-44da-a723-69f7d64fd9d3","owner":[],"postedDate":"March 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-05T16:04:53+00:00","versionOfRecord":{"articleIdentity":"rs-6209063","link":"https://doi.org/10.1186/s12859-025-06321-y","journal":{"identity":"bmc-bioinformatics","isVorOnly":false,"title":"BMC Bioinformatics"},"publishedOn":"2025-12-29 15:57:29","publishedOnDateReadable":"December 29th, 2025"},"versionCreatedAt":"2025-03-17 06:05:39","video":"","vorDoi":"10.1186/s12859-025-06321-y","vorDoiUrl":"https://doi.org/10.1186/s12859-025-06321-y","workflowStages":[]},"version":"v1","identity":"rs-6209063","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6209063","identity":"rs-6209063","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}