{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T15:45:56Z","timestamp":1776872756389,"version":"3.51.2"},"reference-count":29,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T00:00:00Z","timestamp":1757548800000},"content-version":"vor","delay-in-days":11,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010877","name":"Shenzhen Science and Technology Innovation Commission","doi-asserted-by":"publisher","award":["JCYJ20230807114206014"],"award-info":[{"award-number":["JCYJ20230807114206014"]}],"id":[{"id":"10.13039\/501100010877","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangdong Province Basic and Applied Research Fund","award":["2025A1515011753"],"award-info":[{"award-number":["2025A1515011753"]}]},{"name":"Kobilka Institute of Innovative Drug Discovery, The Chinese University of Hong Kong, Shenzhen, China"},{"name":"Center for Intelligent Drug Systems and Smart Biodevices"},{"name":"Featured Areas Research Center Program"},{"name":"Higher Education Sprout Project and Yushan Young Fellow Program","award":["113C51N055"],"award-info":[{"award-number":["113C51N055"]}]},{"DOI":"10.13039\/100009122","name":"Ministry of Education","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100009122","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100020595","name":"National Science and Technology Council","doi-asserted-by":"publisher","award":["NSTC 113-2321-B-A49-025-"],"award-info":[{"award-number":["NSTC 113-2321-B-A49-025-"]}],"id":[{"id":"10.13039\/100020595","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100020595","name":"National Science and Technology Council","doi-asserted-by":"publisher","award":["113-2634-F-039-001"],"award-info":[{"award-number":["113-2634-F-039-001"]}],"id":[{"id":"10.13039\/100020595","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100020595","name":"National Science and Technology Council","doi-asserted-by":"publisher","award":["113-2221-E-A49-160-MY3"],"award-info":[{"award-number":["113-2221-E-A49-160-MY3"]}],"id":[{"id":"10.13039\/100020595","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100020595","name":"National Science and Technology Council","doi-asserted-by":"publisher","award":["112-2740-B-400-005"],"award-info":[{"award-number":["112-2740-B-400-005"]}],"id":[{"id":"10.13039\/100020595","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Taiwan and The National Health Research Institutes","award":["NHRI-EX114-11320BI"],"award-info":[{"award-number":["NHRI-EX114-11320BI"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,31]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Neuropeptides are essential signaling molecules produced in the nervous system that regulate diverse physiological processes and are closely implicated in the pathogenesis of neurodegenerative and neuropsychiatric disorders. Investigating neuropeptides contributes to a better understanding of their regulatory mechanisms and offers new insights into therapeutic strategies for related diseases. Therefore, accurate identification of neuropeptides is crucial for advancing biomedical research and drug development. Due to the high cost of experimental validation, various artificial intelligence methods have been developed for rapid neuropeptide identification. However, existing approaches often suffer from high computational resource consumption, slow processing speed, and poor deploy ability. Moreover, a user-friendly web server for practical application is still lacking. To this end, we propose MSKDNP, a neuropeptide prediction model based on a multi-stage knowledge distillation framework. With only 1.2% of the parameters, MSKDNP attains performance comparable to a fully fine-tuned protein language model while achieving state-of-the-art results in neuropeptide recognition. Moreover, MSKDNP provides favorable interpretability, facilitating biological understanding. A freely accessible web server is available at https:\/\/awi.cuhk.edu.cn\/\u223cbiosequence\/MSKDNP\/index.php.<\/jats:p>","DOI":"10.1093\/bib\/bbaf466","type":"journal-article","created":{"date-parts":[[2025,9,5]],"date-time":"2025-09-05T11:56:54Z","timestamp":1757073414000},"source":"Crossref","is-referenced-by-count":6,"title":["Toward high-efficiency, low-resource, and explainable neuropeptide prediction with MSKDNP"],"prefix":"10.1093","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-6448-2908","authenticated-orcid":false,"given":"Peilin","family":"Xie","sequence":"first","affiliation":[{"name":"Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen 518172 ,","place":["China"]},{"name":"School of Science and Engineering, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen, 518172 ,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2839-2199","authenticated-orcid":false,"given":"Jiahui","family":"Guan","sequence":"additional","affiliation":[{"name":"Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen 518172 ,","place":["China"]},{"name":"School of Medicine, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen, 518172 ,","place":["China"]}]},{"given":"Zhihao","family":"Zhao","sequence":"additional","affiliation":[{"name":"Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen 518172 ,","place":["China"]}]},{"given":"Yulan","family":"Liu","sequence":"additional","affiliation":[{"name":"Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen 518172 ,","place":["China"]}]},{"given":"Zhang","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Medicine, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen, 518172 ,","place":["China"]}]},{"given":"Xuxin","family":"He","sequence":"additional","affiliation":[{"name":"School of Medicine, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen, 518172 ,","place":["China"]}]},{"given":"Xingchen","family":"Liu","sequence":"additional","affiliation":[{"name":"Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen 518172 ,","place":["China"]}]},{"given":"Yun","family":"Tang","sequence":"additional","affiliation":[{"name":"Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University , No. 75, Boai Street, Hsinchu 300 ,","place":["Taiwan"]},{"name":"Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B), National Yang Ming Chiao Tung University , No. 75, Boai Street, Hsinchu 300 ,","place":["Taiwan"]}]},{"given":"Zhenglong","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Science and Engineering, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen, 518172 ,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0283-7712","authenticated-orcid":false,"given":"Tzong-Yi","family":"Lee","sequence":"additional","affiliation":[{"name":"Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University , No. 75, Boai Street, Hsinchu 300 ,","place":["Taiwan"]},{"name":"Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B), National Yang Ming Chiao Tung University , No. 75, Boai Street, Hsinchu 300 ,","place":["Taiwan"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4554-6827","authenticated-orcid":false,"given":"Lantian","family":"Yao","sequence":"additional","affiliation":[{"name":"Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen 518172 ,","place":["China"]},{"name":"School of Science and Engineering, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen, 518172 ,","place":["China"]}]},{"given":"Ying-Chih","family":"Chiang","sequence":"additional","affiliation":[{"name":"Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen 518172 ,","place":["China"]},{"name":"School of Science and Engineering, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen, 518172 ,","place":["China"]},{"name":"School of Medicine, The Chinese University of Hong Kong , Shenzhen, 2001 Longxiang Boulevard, Longgang District, Shenzhen, 518172 ,","place":["China"]}]}],"member":"286","published-online":{"date-parts":[[2025,9,11]]},"reference":[{"key":"2025091102205186900_ref1","doi-asserted-by":"publisher","first-page":"492","DOI":"10.1007\/s00018-022-04451-7","article-title":"Neuropeptides and small-molecule amine transmitters: cooperative signaling in the nervous system","volume":"79","author":"Eiden","year":"2022","journal-title":"Cell Mol Life Sci"},{"key":"2025091102205186900_ref2","doi-asserted-by":"publisher","first-page":"764","DOI":"10.1126\/science.adl1788","article-title":"Grabbing neuropeptide signals in the brain","volume":"382","author":"Romanov","year":"2023","journal-title":"Science"},{"key":"2025091102205186900_ref3","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.ejphar.2009.10.015","article-title":"Neuropeptides from concept to online database www.neuropeptides.nl","volume":"626","author":"Burbach","year":"2010","journal-title":"Eur J Pharmacol"},{"key":"2025091102205186900_ref4","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1002\/jssc.200700450","article-title":"Peptidomics: the integrated approach of ms, hyphenated techniques and bioinformatics for neuropeptide analysis","volume":"31","author":"Boonen","year":"2008","journal-title":"J Sep Sci"},{"key":"2025091102205186900_ref5","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms11436","article-title":"Analytic framework for peptidomics applied to large-scale neuropeptide identification","volume":"7","author":"Secher","year":"2016","journal-title":"Nat Commun"},{"key":"2025091102205186900_ref6","doi-asserted-by":"publisher","first-page":"5129","DOI":"10.1038\/s41598-019-41538-x","article-title":"NeuroPIpred: a tool to predict, design and scan insect neuropeptides","volume":"9","author":"Agrawal","year":"2019","journal-title":"Sci Rep"},{"key":"2025091102205186900_ref7","doi-asserted-by":"publisher","first-page":"3732","DOI":"10.1021\/acs.jproteome.0c00276","article-title":"Prediction of neuropeptides from sequence information using ensemble classifier and hybrid features","volume":"19","author":"Bin","year":"2020","journal-title":"J Proteome Res"},{"key":"2025091102205186900_ref8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/bib\/bbab167","article-title":"NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning","volume":"22","author":"Hasan","year":"2021","journal-title":"Brief Bioinform"},{"key":"2025091102205186900_ref9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/bib\/bbab310","article-title":"NeuroPpred-fuse: an interpretable stacking model for prediction of neuropeptides by fusing sequence information and feature selection methods","volume":"22","author":"Jiang","year":"2021","journal-title":"Brief Bioinform"},{"key":"2025091102205186900_ref10","first-page":"1","article-title":"NeuroPred-PLM: an interpretable and robust model for neuropeptide prediction by protein language model","volume":"24","author":"Wang","year":"2023","journal-title":"Brief Bioinform"},{"key":"2025091102205186900_ref11","doi-asserted-by":"crossref","first-page":"3150","DOI":"10.1093\/bioinformatics\/bts565","article-title":"CD-HIT: Accelerated for clustering the next-generation sequencing data","volume":"28","author":"Limin","year":"2012","journal-title":"Bioinformatics"},{"key":"2025091102205186900_ref12","doi-asserted-by":"crossref","first-page":"btad468","DOI":"10.1093\/bioinformatics\/btad468","article-title":"BERTrand\u2014Peptide: TCR binding prediction using bidirectional encoder representations from transformers augmented with random TCR pairing","volume":"39","author":"Myronov","year":"2023","journal-title":"Bioinformatics"},{"key":"2025091102205186900_ref13","article-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015"},{"key":"2025091102205186900_ref14","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1186\/s13059-022-02780-1","article-title":"iDNA-ABF: multi-scale deep biological language learning model for the interpretable prediction of dna methylations","volume":"23","author":"Jin","year":"2022","journal-title":"Genome Biol"},{"key":"2025091102205186900_ref15","doi-asserted-by":"crossref","first-page":"bbae460","DOI":"10.1093\/bib\/bbae460","article-title":"ACP-CapsPred: an explainable computational framework for identification and functional prediction of anticancer peptides based on capsule network","volume":"25","author":"Yao","year":"2024","journal-title":"Brief Bioinform"},{"key":"2025091102205186900_ref16","article-title":"Med42\u2013evaluating fine-tuning strategies for medical LLMs: full-parameter vs. parameter-efficient approaches","author":"Christophe","year":"2024"},{"key":"2025091102205186900_ref17","doi-asserted-by":"publisher","first-page":"1123","DOI":"10.1126\/science.ade2574","article-title":"Evolutionary-scale prediction of atomic-level protein structure with a language model","volume":"379","author":"Lin","year":"2023","journal-title":"Science"},{"key":"2025091102205186900_ref18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40537-016-0043-6","article-title":"A survey of transfer learning","volume":"3","author":"Weiss","year":"2016","journal-title":"J Big Data"},{"key":"2025091102205186900_ref19","volume":"30","journal-title":"Advances in Neural Information Processing Systems"},{"key":"2025091102205186900_ref20","first-page":"183","article-title":"Incorporating efficient radial basis function networks and significant amino acid pairs for predicting gtp binding sites in transport proteins","volume":"17","author":"Le","year":"2016","journal-title":"BMC Bioinf"},{"key":"2025091102205186900_ref21","doi-asserted-by":"crossref","first-page":"bbad319","DOI":"10.1093\/bib\/bbad319","article-title":"Sequence-based prediction model of protein crystallization propensity using machine learning and two-level feature selection","volume":"24","author":"Le","year":"2023","journal-title":"Brief Bioinform"},{"key":"2025091102205186900_ref22","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/0263-7855(96)00018-5","article-title":"VMD: visual molecular dynamics","volume":"14","author":"Humphrey","year":"1996","journal-title":"J Mol Graph"},{"key":"2025091102205186900_ref23","doi-asserted-by":"publisher","first-page":"W39","DOI":"10.1093\/nar\/gkv416","article-title":"The MEME suite","volume":"43","author":"Bailey","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2025091102205186900_ref24","doi-asserted-by":"publisher","first-page":"E671","DOI":"10.1152\/ajpendo.00492.2002","article-title":"Glucagon and regulation of glucose metabolism","volume":"284","author":"Jiang","year":"2003","journal-title":"Am J PhysiolEndocrinol Metabo"},{"key":"2025091102205186900_ref25","doi-asserted-by":"crossref","first-page":"dsad003","DOI":"10.1093\/dnares\/dsad003","article-title":"Chromosome-level genome assembly of phrynocephalus forsythii using third-generation DNA sequencing and Hi-C analysis","volume":"30","author":"Qi","year":"2023","journal-title":"DNA Res"},{"key":"2025091102205186900_ref26","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1038\/s41467-022-28510-6","article-title":"Structural basis of neuropeptide Y signaling through Y1 receptor","volume":"13","author":"Park","year":"2022","journal-title":"Nat Commun"},{"key":"2025091102205186900_ref27","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1038\/s41421-024-00670-3","article-title":"Structural basis for recognition of 26RFa by the pyroglutamylated RFamide peptide receptor","volume":"10","author":"Jin","year":"2024","journal-title":"Cell Dis"},{"key":"2025091102205186900_ref28","doi-asserted-by":"publisher","first-page":"7990","DOI":"10.1093\/nar\/17.19.7990","article-title":"Nucleotide sequence of a full length cDNA clone encoding the oxytocin-neurophysin I precursor isolated from the ovine corpus luteum","volume":"17","author":"Jones","year":"1989","journal-title":"Nucleic Acids Res"},{"key":"2025091102205186900_ref29","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1038\/s41586-024-07487-w","article-title":"Accurate structure prediction of biomolecular interactions with AlphaFold 3","volume":"630","author":"Abramson","year":"2024","journal-title":"Nature"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/26\/5\/bbaf466\/64238023\/bbaf466.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/26\/5\/bbaf466\/64238023\/bbaf466.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T06:21:02Z","timestamp":1757571662000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbaf466\/8250822"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,31]]},"references-count":29,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,8,31]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbaf466","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2025,9]]},"published":{"date-parts":[[2025,8,31]]},"article-number":"bbaf466"}}