pCPPs-sADNN: Predicting cell-penetrating Peptides using Self-attention based Deep Neural Network

pCPPs-sADNN: Predicting cell-penetrating Peptides using Self-attention based Deep Neural Network | 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 Article pCPPs-sADNN: Predicting cell-penetrating Peptides using Self-attention based Deep Neural Network Shahid Shahid, Maqsood Hayat, Naif Almusallam, Fawaz Khaled Alarfaj This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7709038/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Cell-penetrating peptides (CPPs) are short peptides consisting of 5 to 50 amino acids which is useful for drug delivery and intracellular localization. Laboratory-based techniques are often lengthy and resource-intensive, whereas computational approaches offer a rapid and cost-effective solution. However, the precision and dependability of these computational approaches require further enhancement to meet rigorous scientific standards. To address these limitations, this research introduces a predictive framework called pCPPs-DNN leveraging feature fusion, integrating embeddings from the protein pre-trained language models ProtT5 and ESM-2, along with CTF-based features. By combining the distinct derived feature sets, generates an enhanced and robust features vector. Furthermore, we employed Random Forest-based Recursive Feature Elimination (RF-RFE) for feature selection and used the Adaptive Synthetic Sampling Approach (ADASYN), an advanced variant of SMOTE, to address class imbalance by generating synthetic minority samples. The hybrid feature set was subsequently utilized to train a deep neural network enhanced with an attention mechanism. The proposed pCPPs-DNN model achieved a high training accuracy of 98.58% and an AUC of 0.99. In evaluation on test dataset, pCPPs-DNN demonstrated strong performance with an accuracy of 96.84% and an AUC of 0.99. Biological sciences/Computational biology and bioinformatics Physical sciences/Mathematics and computing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 02 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 24 Oct, 2025 Reviews received at journal 20 Oct, 2025 Reviews received at journal 20 Oct, 2025 Reviews received at journal 07 Oct, 2025 Reviewers agreed at journal 07 Oct, 2025 Reviewers agreed at journal 06 Oct, 2025 Reviewers agreed at journal 06 Oct, 2025 Reviewers invited by journal 06 Oct, 2025 Editor invited by journal 29 Sep, 2025 Editor assigned by journal 28 Sep, 2025 Submission checks completed at journal 26 Sep, 2025 First submitted to journal 25 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. 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-7709038","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":530841508,"identity":"07af5c6b-3960-4ea3-b8db-42538a6f7064","order_by":0,"name":"Shahid Shahid","email":"","orcid":"","institution":"Abdul Wali Khan University Mardan","correspondingAuthor":false,"prefix":"","firstName":"Shahid","middleName":"","lastName":"Shahid","suffix":""},{"id":530841509,"identity":"3bf8faf2-c590-4556-8fb1-e1f260f98dd5","order_by":1,"name":"Maqsood Hayat","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYFACHjApx8DABmYwNjAwMBOjxcCYdC2JDURr0W3gPfiZp+ZPev+MtDSpGww2shsO8B42wKfF7ABfsjTPMYPcGTfSjknnMKQZbwCKJODXwmMgzcNmkNtwO70NqOVw4oYDPMYHCGgx/s3zzyBdHqLlP1FazKR52wwSDG6DHXYArAW/ww7zmFnO7TM23Hj/WbJ1jkGy8czDfMn4vX+8x/jGm29y8nJnjhnezqmwk+073ntYAp8WUBww8cB5IOOZeXCrhgHGH6h8IrSMglEwCkbBiAIAk1dHIEmh2UMAAAAASUVORK5CYII=","orcid":"","institution":"Abdul Wali Khan University Mardan","correspondingAuthor":true,"prefix":"","firstName":"Maqsood","middleName":"","lastName":"Hayat","suffix":""},{"id":530841510,"identity":"6452d2ef-9edf-49a2-979c-9581e8070d32","order_by":2,"name":"Naif Almusallam","email":"","orcid":"","institution":"Abdul Wali Khan University Mardan","correspondingAuthor":false,"prefix":"","firstName":"Naif","middleName":"","lastName":"Almusallam","suffix":""},{"id":530841511,"identity":"57e46424-237c-44e5-a840-d7e713c51ff9","order_by":3,"name":"Fawaz Khaled Alarfaj","email":"","orcid":"","institution":"Abdul Wali Khan University Mardan","correspondingAuthor":false,"prefix":"","firstName":"Fawaz","middleName":"Khaled","lastName":"Alarfaj","suffix":""}],"badges":[],"createdAt":"2025-09-25 05:38:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7709038/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7709038/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-30754-3","type":"published","date":"2025-12-02T15:57:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":93735765,"identity":"393b230f-48df-4030-b4f1-59b232c5316e","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5317031,"visible":true,"origin":"","legend":"","description":"","filename":"CPPPaper22Sep2025.docx","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/1de1594f4ecd1e3df98055bf.docx"},{"id":93735745,"identity":"33a2d26e-bbe3-4559-ad9a-089fb7f368ce","added_by":"auto","created_at":"2025-10-17 03:25:22","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6155,"visible":true,"origin":"","legend":"","description":"","filename":"1423a53353bd490aaa01d6820e24dd5c.json","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/b6f20c3968a0ea447d23365f.json"},{"id":93735763,"identity":"99ad2056-a0bf-41d9-ac49-4f76e2432601","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":148408,"visible":true,"origin":"","legend":"","description":"","filename":"1423a53353bd490aaa01d6820e24dd5c1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/ef052863c09cadbe12cdf1aa.xml"},{"id":93735751,"identity":"696e6aec-9de0-40b2-a5e0-fdcc74bc5aef","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"jpeg","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2095587,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/c0a21de94472fcfa92be3105.jpeg"},{"id":93735752,"identity":"8475eb78-d8a1-4e3b-b18c-bf5745754e97","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":90429,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/09dd8ee329f068dcb7a8a589.png"},{"id":93735777,"identity":"583cdf17-22a5-4304-8e76-bd6756f5c6d7","added_by":"auto","created_at":"2025-10-17 03:25:24","extension":"jpeg","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1936544,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/c44a9a9dc09ead948c2def51.jpeg"},{"id":93735775,"identity":"4ab17713-9daf-46e3-994d-76643d62b4b8","added_by":"auto","created_at":"2025-10-17 03:25:24","extension":"jpeg","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":269170,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/e07e7679fd54fda29943d007.jpeg"},{"id":93736083,"identity":"6f223d59-8e2a-4521-810f-567ba2303395","added_by":"auto","created_at":"2025-10-17 03:33:22","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":35697,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/7e3b16996f729dd323c67541.png"},{"id":93735749,"identity":"462da342-232b-41ad-b824-432bc6701f3d","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":40702,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/47889746a7ff9fd7e87e6554.png"},{"id":93735740,"identity":"f8af1348-7e83-44f6-b79b-58d6af82b80c","added_by":"auto","created_at":"2025-10-17 03:25:22","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":52557,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/be1626d3dc2f887806e51976.png"},{"id":93735781,"identity":"dd4a2905-f3e6-4bfa-8642-0458966b0a2b","added_by":"auto","created_at":"2025-10-17 03:25:24","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":42855,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/f48b7ff7e338f22c3965a454.png"},{"id":93736087,"identity":"be8f7180-8bb6-42ad-a079-1a205e71ff04","added_by":"auto","created_at":"2025-10-17 03:33:23","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":38903,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/9fa8f2a0eceb7a1e5d5878b5.png"},{"id":93735753,"identity":"252d8fbb-c097-4b5e-8aa5-b0cb5af29b50","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":90018,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/04b039de97673cbabfbea09f.png"},{"id":93735762,"identity":"6fa11cc5-2b1f-4797-93c9-bbcad2d6d6b9","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"wmf","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":598,"visible":true,"origin":"","legend":"","description":"","filename":"image24.wmf","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/6ade2613bce751b4d68a4e79.wmf"},{"id":93735759,"identity":"7db8905b-0b50-4035-97e4-b3020ee1d2a3","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"wmf","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":598,"visible":true,"origin":"","legend":"","description":"","filename":"image3.wmf","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/909da7e8ec1a5f854b71b726.wmf"},{"id":93735764,"identity":"306633f5-6b18-446f-8e5d-604802e82a9b","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"wmf","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":598,"visible":true,"origin":"","legend":"","description":"","filename":"image4.wmf","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/bca5e771e16f1e95d76406ce.wmf"},{"id":93735738,"identity":"29e6fcec-8da6-47c4-95eb-9078dbbfb4c1","added_by":"auto","created_at":"2025-10-17 03:25:22","extension":"wmf","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":598,"visible":true,"origin":"","legend":"","description":"","filename":"image40.wmf","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/0732148ed4ca2ccd167cb5d9.wmf"},{"id":93735754,"identity":"35797699-4644-4879-bb7b-2f467e5867b6","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"wmf","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":598,"visible":true,"origin":"","legend":"","description":"","filename":"image42.wmf","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/34cfceb8f46c98f8371aed0c.wmf"},{"id":93736084,"identity":"d20e2e39-7d37-4823-81fb-2bfa85a94002","added_by":"auto","created_at":"2025-10-17 03:33:22","extension":"wmf","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":598,"visible":true,"origin":"","legend":"","description":"","filename":"image5.wmf","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/e87a92c53ce6bb601ff1aaeb.wmf"},{"id":93735756,"identity":"03c3d520-778d-4cd7-aa95-4a2466ada42e","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"wmf","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":598,"visible":true,"origin":"","legend":"","description":"","filename":"image9.wmf","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/d0ce4e498da44488826433c2.wmf"},{"id":93735774,"identity":"f5b90bcd-6a43-47bf-aacf-7f9d267ca16f","added_by":"auto","created_at":"2025-10-17 03:25:24","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":238287,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/8916f9f012b72bf79b91a330.png"},{"id":93735743,"identity":"eb384b4f-1a95-4388-baf8-4b9317b10881","added_by":"auto","created_at":"2025-10-17 03:25:22","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":14811,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/4deeec3bd8bbc5cc9f467e94.png"},{"id":93735768,"identity":"937b13c1-f3f3-494c-a9b3-8212fedbdbab","added_by":"auto","created_at":"2025-10-17 03:25:24","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":315034,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/8d919d00f573c67310dd472a.png"},{"id":93735748,"identity":"7c62b0a0-bbea-4fa0-a965-73001aaff3b6","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"png","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":54922,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/84c0f7efb996cba84419f924.png"},{"id":93736090,"identity":"33975bc9-d2d1-4954-9873-54808ddd9cc7","added_by":"auto","created_at":"2025-10-17 03:33:24","extension":"png","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":12142,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/55c66f2a7c99d97d1bb462a3.png"},{"id":93735770,"identity":"e92a1f2e-3194-4346-a927-f5a5c7eee843","added_by":"auto","created_at":"2025-10-17 03:25:24","extension":"png","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":14469,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/7b6f249f1e9af905bfb69377.png"},{"id":93735767,"identity":"ff4fb463-de42-41ea-8cf0-ba052b820906","added_by":"auto","created_at":"2025-10-17 03:25:24","extension":"png","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":19392,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/54aa0caf0891cbb69093a1b6.png"},{"id":93735771,"identity":"b49e55fc-160a-4143-8029-88eabd3fdac1","added_by":"auto","created_at":"2025-10-17 03:25:24","extension":"png","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":15170,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/bf3fae489dc63209402b3d92.png"},{"id":93735773,"identity":"7bfc965d-bc12-4d9a-9448-512b8a951955","added_by":"auto","created_at":"2025-10-17 03:25:24","extension":"png","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":13461,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/165e448109f057e2426f40a2.png"},{"id":93736089,"identity":"106f7076-54e7-4fa3-9beb-f3b062601ba9","added_by":"auto","created_at":"2025-10-17 03:33:24","extension":"png","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":16498,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/b74890b2286224c97c5af3f5.png"},{"id":93735757,"identity":"59c07fe2-f025-4866-b407-8e077c7f37ec","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"png","order_by":30,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":232,"visible":true,"origin":"","legend":"","description":"","filename":"Onlineimage24.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/763c4d16b61e91afd198bf12.png"},{"id":93736088,"identity":"c479522d-05c2-46f3-a0ef-56ec9777eff4","added_by":"auto","created_at":"2025-10-17 03:33:23","extension":"png","order_by":31,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":266,"visible":true,"origin":"","legend":"","description":"","filename":"Onlineimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/8812ccd7c6649cecc56b8d88.png"},{"id":93735779,"identity":"a7c0dddf-674c-45b2-9bf3-5bda688177b4","added_by":"auto","created_at":"2025-10-17 03:25:24","extension":"png","order_by":32,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":275,"visible":true,"origin":"","legend":"","description":"","filename":"Onlineimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/a714f07c4188501fc893f813.png"},{"id":93735782,"identity":"d52360c9-bd0f-4e20-8b46-31a89a4e873a","added_by":"auto","created_at":"2025-10-17 03:25:25","extension":"png","order_by":33,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":252,"visible":true,"origin":"","legend":"","description":"","filename":"Onlineimage40.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/dc29d221046eab37225ced00.png"},{"id":93736091,"identity":"32713db0-d7cb-4769-9b85-c5fef267f37a","added_by":"auto","created_at":"2025-10-17 03:33:24","extension":"png","order_by":34,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":252,"visible":true,"origin":"","legend":"","description":"","filename":"Onlineimage42.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/8252dccf12df71d8d6f0bdab.png"},{"id":93735747,"identity":"bb97d2c4-96d7-46bc-aeea-5b8020f37f67","added_by":"auto","created_at":"2025-10-17 03:25:22","extension":"png","order_by":35,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":263,"visible":true,"origin":"","legend":"","description":"","filename":"Onlineimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/600fec5cd02ec5a4a38d75ce.png"},{"id":93736086,"identity":"a90f1de4-3610-4f20-a9aa-22a461f3b4d3","added_by":"auto","created_at":"2025-10-17 03:33:23","extension":"png","order_by":36,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":294,"visible":true,"origin":"","legend":"","description":"","filename":"Onlineimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/e14c6d89e74be32216a329be.png"},{"id":93735780,"identity":"cbdc475a-cbe3-41f1-9801-bb6fb113a397","added_by":"auto","created_at":"2025-10-17 03:25:24","extension":"xml","order_by":37,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":147972,"visible":true,"origin":"","legend":"","description":"","filename":"1423a53353bd490aaa01d6820e24dd5c1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/68dd38e3bd8ab749d46515c8.xml"},{"id":93735760,"identity":"4538b67f-dc7d-441d-8da0-a49831a7d85b","added_by":"auto","created_at":"2025-10-17 03:25:23","extension":"html","order_by":38,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":161615,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1/51d5f9df5098733cef9da685.html"},{"id":97723870,"identity":"9a89b254-61e9-45d9-b772-fe3d5113b721","added_by":"auto","created_at":"2025-12-08 16:08:55","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":968713,"visible":true,"origin":"","legend":"","description":"","filename":"CPPPaper22Sep2025.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7709038/v1_covered_305bb080-b50f-42b4-8c7c-c45d68237774.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"pCPPs-sADNN: Predicting cell-penetrating Peptides using Self-attention based Deep Neural Network","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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7709038/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7709038/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCell-penetrating peptides (CPPs) are short peptides consisting of 5 to 50 amino acids which is useful for drug delivery and intracellular localization. Laboratory-based techniques are often lengthy and resource-intensive, whereas computational approaches offer a rapid and cost-effective solution. However, the precision and dependability of these computational approaches require further enhancement to meet rigorous scientific standards. To address these limitations, this research introduces a predictive framework called pCPPs-DNN leveraging feature fusion, integrating embeddings from the protein pre-trained language models ProtT5 and ESM-2, along with CTF-based features. By combining the distinct derived feature sets, generates an enhanced and robust features vector. Furthermore, we employed Random Forest-based Recursive Feature Elimination (RF-RFE) for feature selection and used the Adaptive Synthetic Sampling Approach (ADASYN), an advanced variant of SMOTE, to address class imbalance by generating synthetic minority samples. The hybrid feature set was subsequently utilized to train a deep neural network enhanced with an attention mechanism. The proposed pCPPs-DNN model achieved a high training accuracy of 98.58% and an AUC of 0.99. In evaluation on test dataset, pCPPs-DNN demonstrated strong performance with an accuracy of 96.84% and an AUC of 0.99.\u003c/p\u003e","manuscriptTitle":"pCPPs-sADNN: Predicting cell-penetrating Peptides using Self-attention based Deep Neural Network","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-17 03:25:15","doi":"10.21203/rs.3.rs-7709038/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-24T14:50:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-20T13:02:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-20T06:29:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-07T07:40:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"252476784548119125238121854081197970317","date":"2025-10-07T04:38:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"260678501909288888026318105633991546655","date":"2025-10-07T00:25:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"255109211314664724265779143390980172082","date":"2025-10-06T23:20:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-06T20:08:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-29T15:45:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-28T16:42:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-26T10:47:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-09-25T05:32:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e38457c4-cabc-4832-b3e7-1349e5693427","owner":[],"postedDate":"October 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":56434583,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":56434584,"name":"Physical sciences/Mathematics and computing"}],"tags":[],"updatedAt":"2025-12-08T16:01:47+00:00","versionOfRecord":{"articleIdentity":"rs-7709038","link":"https://doi.org/10.1038/s41598-025-30754-3","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-12-02 15:57:44","publishedOnDateReadable":"December 2nd, 2025"},"versionCreatedAt":"2025-10-17 03:25:15","video":"","vorDoi":"10.1038/s41598-025-30754-3","vorDoiUrl":"https://doi.org/10.1038/s41598-025-30754-3","workflowStages":[]},"version":"v1","identity":"rs-7709038","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7709038","identity":"rs-7709038","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}