{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T18:36:43Z","timestamp":1792175803723,"version":"4.4.0"},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T00:00:00Z","timestamp":1761868800000},"content-version":"vor","delay-in-days":309,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000268","name":"Biotechnology and Biological Sciences Research Council","doi-asserted-by":"publisher","award":["BB\/T008709\/1"],"award-info":[{"award-number":["BB\/T008709\/1"]}],"id":[{"id":"10.13039\/501100000268","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014013","name":"UK Research and Innovation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100014013","id-type":"DOI","asserted-by":"publisher"}]},{"name":"comprising the Biotechnology and Biological Sciences Research Council","award":["BB\/X018156\/1"],"award-info":[{"award-number":["BB\/X018156\/1"]}]},{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","award":["MR\/R020973\/1"],"award-info":[{"award-number":["MR\/R020973\/1"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","award":["MR\/X005895\/1"],"award-info":[{"award-number":["MR\/X005895\/1"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/Y018842\/1"],"award-info":[{"award-number":["EP\/Y018842\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,26]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Tuberculosis, caused by Mycobacterium tuberculosis, remains a global health challenge driven by rising antibiotic resistance. Antimicrobial peptides offer a promising alternative due to membrane-disruptive activity and low resistance potential, yet the scarcity of TB-specific AMP data constrains targeted development. We present a reproducible deep learning protocol that integrates long short-term memory networks with transfer learning to classify and generate TB-active peptides.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Classifiers were pretrained on a large corpus of general AMPs and fine-tuned on curated TB-specific sequences using frozen encoder and full backpropagation strategies. We benchmarked four model variants [unidirectional and bidirectional long short-term memories (LSTMs), with and without attention] on a held-out TB test set; the unidirectional LSTM with a frozen encoder achieved the best performance (accuracy 90%, AUC 0.97). In parallel, LSTM-based generative models were trained to produce de novo TB-active peptides. A generator trained exclusively on TB data produced 94 of 100 peptides predicted as antimicrobial by AMP Scanner, outperforming transfer learning-based generators. Generated peptides were evaluated for antimicrobial activity, toxicity, structure, and AMP-like physicochemical traits, and four candidates shared \u226584% identity with known TB-AMPs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The complete model and data can be found at: https:\/\/github.com\/linfeng-wang\/TB-AMP-design.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioadv\/vbaf274","type":"journal-article","created":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T13:27:12Z","timestamp":1761744432000},"source":"Crossref","is-referenced-by-count":5,"title":["Long short-term memory-based deep learning model for the discovery of antimicrobial peptides targeting\n                    <i>Mycobacterium tuberculosis<\/i>"],"prefix":"10.1093","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0464-7250","authenticated-orcid":false,"given":"Linfeng","family":"Wang","sequence":"first","affiliation":[{"name":"Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine , London WC1E 7HT,","place":["United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1403-6138","authenticated-orcid":false,"given":"Susana","family":"Campino","sequence":"additional","affiliation":[{"name":"Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine , London WC1E 7HT,","place":["United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8985-9265","authenticated-orcid":false,"given":"Taane G","family":"Clark","sequence":"additional","affiliation":[{"name":"Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine , London WC1E 7HT,","place":["United Kingdom"]},{"name":"Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine , London WC1E 7HT,","place":["United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8323-7019","authenticated-orcid":false,"given":"Jody E","family":"Phelan","sequence":"additional","affiliation":[{"name":"Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine , London WC1E 7HT,","place":["United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,10,31]]},"reference":[{"key":"2025111103064630800_vbaf274-B1","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"},{"key":"2025111103064630800_vbaf274-B2","doi-asserted-by":"publisher","first-page":"104778","DOI":"10.1016\/j.compbiomed.2021.104778","article-title":"iAtbP-Hyb-EnC: prediction of antitubercular peptides via heterogeneous feature representation and genetic algorithm based ensemble learning model","volume":"137","author":"Akbar","year":"2021","journal-title":"Comput Biol Med"},{"key":"2025111103064630800_vbaf274-B3","doi-asserted-by":"publisher","author":"Akiba","DOI":"10.1145\/3292500.3330701"},{"key":"2025111103064630800_vbaf274-B4","doi-asserted-by":"publisher","first-page":"102068","DOI":"10.1016\/j.jksuci.2024.102068","article-title":"RNN-LSTM: from applications to modeling techniques and beyond\u2014systematic review","volume":"36","author":"Al-Selwi","year":"2024","journal-title":"J King Saud Univ Comput Inform Sci"},{"key":"2025111103064630800_vbaf274-B5","doi-asserted-by":"publisher","first-page":"1697","DOI":"10.1038\/s41598-018-19752-w","article-title":"AmPEP: sequence-based prediction of antimicrobial peptides using distribution patterns of amino acid properties and random forest","volume":"8","author":"Bhadra","year":"2018","journal-title":"Sci Rep"},{"key":"2025111103064630800_vbaf274-B6","doi-asserted-by":"publisher","first-page":"411","DOI":"10.3390\/antibiotics11030411","article-title":"Novel antimicrobial peptides designed using a recurrent neural network reduce mortality in experimental sepsis","volume":"11","author":"Bolatchiev","year":"2022","journal-title":"Antibiotics"},{"key":"2025111103064630800_vbaf274-B7","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1186\/1471-2105-10-421","article-title":"BLAST+: architecture and applications","volume":"10","author":"Camacho","year":"2009","journal-title":"BMC Bioinformatics"},{"key":"2025111103064630800_vbaf274-B8","doi-asserted-by":"publisher","first-page":"bbae644","DOI":"10.1093\/bib\/bbae644","article-title":"TG-CDDPM: text-guided antimicrobial peptides generation based on conditional denoising diffusion probabilistic model","volume":"26","author":"Cao","year":"2025","journal-title":"Brief Bioinform"},{"key":"2025111103064630800_vbaf274-B9","doi-asserted-by":"crossref","first-page":"D377","DOI":"10.1093\/nar\/gkac933","article-title":"CAMPR4: a database of natural and synthetic antimicrobial peptides","volume":"51","author":"Gawde","year":"2023","journal-title":"Nucleic Acids Res"},{"key":"2025111103064630800_vbaf274-B10","author":"Global Tuberculosis Report 2024","year":"2024"},{"key":"2025111103064630800_vbaf274-B11","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1038\/s41597-019-0154-y","article-title":"DRAMP 2.0, an updated data repository of antimicrobial peptides","volume":"6","author":"Kang","year":"2019","journal-title":"Sci Data"},{"key":"2025111103064630800_vbaf274-B12","doi-asserted-by":"publisher","first-page":"972","DOI":"10.1016\/j.csbj.2019.06.024","article-title":"AtbPpred: a robust sequence-based prediction of anti-tubercular peptides using extremely randomized trees","volume":"17","author":"Manavalan","year":"2019","journal-title":"Comput Struct Biotechnol J"},{"key":"2025111103064630800_vbaf274-B13","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1802.03426","article-title":"UMAP: uniform manifold approximation and projection for dimension reduction","author":"McInnes","year":"2020"},{"key":"2025111103064630800_vbaf274-B14","doi-asserted-by":"crossref","first-page":"e4792","DOI":"10.1002\/pro.4792","article-title":"UCSF ChimeraX: tools for structure building and analysis","volume":"32","author":"Meng","year":"2023","journal-title":"Prot Sci"},{"key":"2025111103064630800_vbaf274-B15","author":"Meeting Report of the WHO Expert Consultation on the Definition of Extensively Drug-Resistant Tuberculosis","year":"2020"},{"key":"2025111103064630800_vbaf274-B16","doi-asserted-by":"publisher","first-page":"431","DOI":"10.3390\/pharmaceutics15020431","article-title":"CSM-toxin: a web-server for predicting protein toxicity","volume":"15","author":"Morozov","year":"2023","journal-title":"Pharmaceutics"},{"key":"2025111103064630800_vbaf274-B17","doi-asserted-by":"publisher","first-page":"2753","DOI":"10.1093\/bioinformatics\/btx285","article-title":"modlAMP: python for antimicrobial peptides","volume":"33","author":"M\u00fcller","year":"2017","journal-title":"Bioinformatics"},{"key":"2025111103064630800_vbaf274-B18","doi-asserted-by":"publisher","first-page":"323","DOI":"10.3390\/ph14040323","article-title":"Antimicrobial peptides as potential anti-tubercular leads: a concise review","volume":"14","author":"Oliveira","year":"2021","journal-title":"Pharmaceuticals"},{"key":"2025111103064630800_vbaf274-B19","doi-asserted-by":"publisher","author":"Paszke","year":"2019","DOI":"10.48550\/arXiv.1912.01703"},{"key":"2025111103064630800_vbaf274-B20","first-page":"2825","article-title":"Scikit-learn: machine learning in python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J Mach Learn Res"},{"key":"2025111103064630800_vbaf274-B21","doi-asserted-by":"publisher","first-page":"4216","DOI":"10.1038\/s41467-024-48588-4","article-title":"Mycobacterium tuberculosis suppresses host antimicrobial peptides by dehydrogenating L-alanine","volume":"15","author":"Peng","year":"2024","journal-title":"Nat Commun"},{"key":"2025111103064630800_vbaf274-B22","doi-asserted-by":"publisher","first-page":"D288","DOI":"10.1093\/nar\/gkaa991","article-title":"DBAASP v3: database of antimicrobial\/cytotoxic activity and structure of peptides as a resource for development of new therapeutics","volume":"49","author":"Pirtskhalava","year":"2021","journal-title":"Nucleic Acids Res"},{"key":"2025111103064630800_vbaf274-B23","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1038\/s42003-025-07615-w","article-title":"Prediction of hemolytic peptides and their hemolytic concentration","volume":"8","author":"Rathore","year":"2025","journal-title":"Commun Biol"},{"key":"2025111103064630800_vbaf274-B24","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1186\/s12859-021-04305-2","article-title":"Co-AMPpred for in silico-aided predictions of antimicrobial peptides by integrating composition-based features","volume":"22","author":"Singh","year":"2021","journal-title":"BMC Bioinformatics"},{"key":"2025111103064630800_vbaf274-B25","doi-asserted-by":"publisher","first-page":"D609","DOI":"10.1093\/nar\/gkae1010","article-title":"UniProt: the universal protein knowledgebase in 2025","volume":"53","author":"The UniProt Consortium","year":"2025","journal-title":"Nucleic Acids Res"},{"key":"2025111103064630800_vbaf274-B26","doi-asserted-by":"publisher","first-page":"bay025","DOI":"10.1093\/database\/bay025","article-title":"AntiTbPdb: a knowledgebase of anti-tubercular peptides","volume":"2018","author":"Usmani","year":"2018","journal-title":"Database (Oxford)"},{"key":"2025111103064630800_vbaf274-B27","doi-asserted-by":"publisher","first-page":"2740","DOI":"10.1093\/bioinformatics\/bty179","article-title":"Deep learning improves antimicrobial peptide recognition","volume":"34","author":"Veltri","year":"2018","journal-title":"Bioinformatics"},{"key":"2025111103064630800_vbaf274-B28","doi-asserted-by":"publisher","first-page":"471","DOI":"10.3390\/biom11030471","article-title":"Deep learning for novel antimicrobial peptide design","volume":"11","author":"Wang","year":"2021","journal-title":"Biomolecules"},{"key":"2025111103064630800_vbaf274-B29","doi-asserted-by":"publisher","first-page":"D1087","DOI":"10.1093\/nar\/gkv1278","article-title":"APD3: the antimicrobial peptide database as a tool for research and education","volume":"44","author":"Wang","year":"2016","journal-title":"Nucleic Acids Res"},{"key":"2025111103064630800_vbaf274-B30","doi-asserted-by":"publisher","first-page":"17100","DOI":"10.1038\/s41598-023-44341-x","article-title":"Mixed infections in genotypic drug-resistant Mycobacterium tuberculosis","volume":"13","author":"Wang","year":"2023","journal-title":"Sci Rep"},{"key":"2025111103064630800_vbaf274-B31","doi-asserted-by":"publisher","author":"Witten","year":"2019","DOI":"10.1101\/692681"},{"key":"2025111103064630800_vbaf274-B32","doi-asserted-by":"publisher","first-page":"bbad240","DOI":"10.1093\/bib\/bbad240","article-title":"iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities","volume":"24","author":"Xu","year":"2023","journal-title":"Brief Bioinform"}],"container-title":["Bioinformatics Advances"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformaticsadvances\/advance-article-pdf\/doi\/10.1093\/bioadv\/vbaf274\/65044853\/vbaf274.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformaticsadvances\/article-pdf\/5\/1\/vbaf274\/65044853\/vbaf274.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformaticsadvances\/article-pdf\/5\/1\/vbaf274\/65044853\/vbaf274.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T08:06:53Z","timestamp":1762848413000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformaticsadvances\/article\/doi\/10.1093\/bioadv\/vbaf274\/8307124"}},"subtitle":[],"editor":[{"given":"Michael","family":"Gromiha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2024,12,26]]},"references-count":32,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,12,26]]}},"URL":"https:\/\/doi.org\/10.1093\/bioadv\/vbaf274","relation":{},"ISSN":["2635-0041"],"issn-type":[{"value":"2635-0041","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2025]]},"published":{"date-parts":[[2024,12,26]]},"article-number":"vbaf274"}}