Computational Prioritization of Multi-Target Inhibitors: Explainable QSAR and Docking- Based Discovery of Dual AChE/BACE1 Chemotypes

Computational Prioritization of Multi-Target Inhibitors: Explainable QSAR and Docking- Based Discovery of Dual AChE/BACE1 Chemotypes | 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 Computational Prioritization of Multi-Target Inhibitors: Explainable QSAR and Docking- Based Discovery of Dual AChE/BACE1 Chemotypes İsa Bozkır, Merve Seda İbişoğlu, İlknur Kayıkçıoğlu Bozkır, Halil İbrahim Güler This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7718358/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Jan, 2026 Read the published version in Journal of Computer-Aided Molecular Design → Version 1 posted 9 You are reading this latest preprint version Abstract The discovery of dual acetylcholinesterase (AChE) and β-secretase (BACE1) inhibitors remains a promising strategy against multifactorial Alzheimer’s disease. Here, rigorously curated ChEMBL-derived data were used to develop explainable QSAR models for dual-inhibition prioritization. Molecules were standardized, near-duplicates were removed using a Tanimoto similarity threshold (≥ 0.80), and physicochemical outliers were filtered prior to modeling. Multiple classifiers (including LightGBM, XGBoost, Random Forest, SVM, kNN, MLP, and AdaBoost) and fingerprints (e.g., RDKit-FP, ECFP6) were benchmarked under scaffold-based nested cross-validation to prevent data leakage. Class imbalance was handled with SMOTETomek applied strictly within training folds. Model selection relied on a weighted composite score combining F1, PR-AUC, MCC, and Recall, and performance was accompanied by bootstrap confidence intervals, calibration curves, and Y-randomization controls. The top model (LightGBM + RDKit-FP) achieved strong generalization (Accuracy ≈ 0.92, Recall ≈ 1.00, PR-AUC ≈ 0.86, ROC-AUC ≈ 0.96). SHAP analysis highlighted aromatic and hydrogen-bonding substructures as key positive contributors. Prospective candidates (e.g., CHEMBL5082250, CHEMBL1651126, CHEMBL1651127) were evaluated by active-site-focused docking against AChE (PDB: 4EY7) and BACE1 (PDB: 2G94) with essential waters retained; docking scores (ΔG, kcal·mol⁻¹) were used for relative ranking only and were further consensus-rescored. SwissADME/pkCSM profiling suggested CNS-relevant properties (e.g., MPO, logBB, P-gp liability) and acceptable oral drug-likeness. Collectively, the workflow provides a reproducible and transparent pipeline for prioritizing dual AChE/BACE1 chemotypes and nominates testable scaffolds for experimental validation. Alzheimer’s disease AChE BACE1 Dual inhibitors Explainable QSAR Docking/ADMET Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Jan, 2026 Read the published version in Journal of Computer-Aided Molecular Design → Version 1 posted Editorial decision: Revision requested 18 Nov, 2025 Reviews received at journal 18 Nov, 2025 Reviews received at journal 31 Oct, 2025 Reviewers agreed at journal 28 Oct, 2025 Reviewers agreed at journal 11 Oct, 2025 Reviewers invited by journal 09 Oct, 2025 Editor assigned by journal 05 Oct, 2025 Submission checks completed at journal 26 Sep, 2025 First submitted to journal 26 Sep, 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. 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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-7718358","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":532676951,"identity":"c7f0e408-cb48-498f-bafa-1d329f1db207","order_by":0,"name":"İsa Bozkır","email":"","orcid":"","institution":"Gümüşhane University","correspondingAuthor":false,"prefix":"","firstName":"İsa","middleName":"","lastName":"Bozkır","suffix":""},{"id":532676952,"identity":"3c68af8c-03c8-4b71-82e8-1f58a22977a0","order_by":1,"name":"Merve Seda İbişoğlu","email":"","orcid":"","institution":"Karadeniz Technical 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Chemotypes","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-computer-aided-molecular-design","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcam","sideBox":"Learn more about [Journal of Computer-Aided Molecular Design](http://link.springer.com/journal/10822)","snPcode":"10822","submissionUrl":"https://submission.nature.com/new-submission/10822/3","title":"Journal of Computer-Aided Molecular Design","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Alzheimer’s disease, AChE, BACE1, Dual inhibitors, Explainable QSAR, Docking/ADMET","lastPublishedDoi":"10.21203/rs.3.rs-7718358/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7718358/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe discovery of dual acetylcholinesterase (AChE) and β-secretase (BACE1) inhibitors remains a promising strategy against multifactorial Alzheimer\u0026rsquo;s disease. Here, rigorously curated ChEMBL-derived data were used to develop explainable QSAR models for dual-inhibition prioritization. Molecules were standardized, near-duplicates were removed using a Tanimoto similarity threshold (\u0026ge;\u0026thinsp;0.80), and physicochemical outliers were filtered prior to modeling. Multiple classifiers (including LightGBM, XGBoost, Random Forest, SVM, kNN, MLP, and AdaBoost) and fingerprints (e.g., RDKit-FP, ECFP6) were benchmarked under scaffold-based nested cross-validation to prevent data leakage. Class imbalance was handled with SMOTETomek applied strictly within training folds. Model selection relied on a weighted composite score combining F1, PR-AUC, MCC, and Recall, and performance was accompanied by bootstrap confidence intervals, calibration curves, and Y-randomization controls. The top model (LightGBM\u0026thinsp;+\u0026thinsp;RDKit-FP) achieved strong generalization (Accuracy\u0026thinsp;\u0026asymp;\u0026thinsp;0.92, Recall\u0026thinsp;\u0026asymp;\u0026thinsp;1.00, PR-AUC\u0026thinsp;\u0026asymp;\u0026thinsp;0.86, ROC-AUC\u0026thinsp;\u0026asymp;\u0026thinsp;0.96). SHAP analysis highlighted aromatic and hydrogen-bonding substructures as key positive contributors. Prospective candidates (e.g., CHEMBL5082250, CHEMBL1651126, CHEMBL1651127) were evaluated by active-site-focused docking against AChE (PDB: 4EY7) and BACE1 (PDB: 2G94) with essential waters retained; docking scores (ΔG, kcal\u0026middot;mol⁻\u0026sup1;) were used for relative ranking only and were further consensus-rescored. SwissADME/pkCSM profiling suggested CNS-relevant properties (e.g., MPO, logBB, P-gp liability) and acceptable oral drug-likeness. Collectively, the workflow provides a reproducible and transparent pipeline for prioritizing dual AChE/BACE1 chemotypes and nominates testable scaffolds for experimental validation.\u003c/p\u003e","manuscriptTitle":"Computational Prioritization of Multi-Target Inhibitors: Explainable QSAR and Docking- Based Discovery of Dual AChE/BACE1 Chemotypes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-23 11:09:05","doi":"10.21203/rs.3.rs-7718358/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-18T11:34:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-18T09:20:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-31T18:10:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"286854828965551154037836460523462714679","date":"2025-10-28T06:58:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"37455456617609692146585210561232797317","date":"2025-10-11T20:28:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-09T17:29:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-06T01:29:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-27T03:32:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Computer-Aided Molecular Design","date":"2025-09-26T06:31:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-computer-aided-molecular-design","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcam","sideBox":"Learn more about [Journal of Computer-Aided Molecular Design](http://link.springer.com/journal/10822)","snPcode":"10822","submissionUrl":"https://submission.nature.com/new-submission/10822/3","title":"Journal of Computer-Aided Molecular Design","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"9fe864c2-f820-4abe-902d-a24a197aa2b2","owner":[],"postedDate":"October 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-02T16:01:26+00:00","versionOfRecord":{"articleIdentity":"rs-7718358","link":"https://doi.org/10.1007/s10822-025-00757-3","journal":{"identity":"journal-of-computer-aided-molecular-design","isVorOnly":false,"title":"Journal of Computer-Aided Molecular Design"},"publishedOn":"2026-01-28 15:58:19","publishedOnDateReadable":"January 28th, 2026"},"versionCreatedAt":"2025-10-23 11:09:05","video":"","vorDoi":"10.1007/s10822-025-00757-3","vorDoiUrl":"https://doi.org/10.1007/s10822-025-00757-3","workflowStages":[]},"version":"v1","identity":"rs-7718358","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7718358","identity":"rs-7718358","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}