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Stocco, M. Artigues-Lleixa, A. Hunklinger, T. Widatalla, M. Guell, N. Ferruz, Guiding generative protein language models with reinforcement learning, arXiv preprint arXiv:2412.12979."},{"key":"10.1016\/j.cbpa.2026.102728_bib43","unstructured":"F. Stocco, M. Garibbo, N. 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Butcher, R. Krishna, R. Mitra, R. I. Brent, Y. Li, N. Corley, P. T. Kim, J. Funk, S. Mathis, S. 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Abrudan, S. P. Ojeda, C. K. Joshi, M. Greenig, F. Engelberger, A. Khmelinskaia, J. Meiler, M. Vendruscolo, T. P. Knowles, Multi-state protein design with dynamicmpnn, arXiv preprint arXiv:2507.21938 ."},{"key":"10.1016\/j.cbpa.2026.102728_bib69","doi-asserted-by":"crossref","first-page":"eadv9817","DOI":"10.1126\/science.adv9817","article-title":"Scalable emulation of protein equilibrium ensembles with generative deep learning","volume":"389","author":"Lewis","year":"2025","journal-title":"Science"},{"key":"10.1016\/j.cbpa.2026.102728_bib70","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1126\/science.ads0018","article-title":"Simulating 500 million years of evolution with a language model","volume":"387","author":"Hayes","year":"2025","journal-title":"Science"},{"key":"10.1016\/j.cbpa.2026.102728_bib71","doi-asserted-by":"crossref","first-page":"1070","DOI":"10.1038\/s41586-023-06728-8","article-title":"Illuminating protein space with a programmable generative model","volume":"623","author":"Ingraham","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.cbpa.2026.102728_bib72","series-title":"The fourteenth international conference on learning representations","article-title":"Scaling atomistic protein binder design with generative pretraining and test-time compute","author":"Didi","year":"2026"},{"key":"10.1016\/j.cbpa.2026.102728_bib73","first-page":"2025","article-title":"Scaling unlocks broader generation and deeper functional understanding of proteins","author":"Bhatnagar","year":"2025","journal-title":"bioRxiv"},{"key":"10.1016\/j.cbpa.2026.102728_bib74","first-page":"2025","article-title":"Genome modeling and design across all domains of life with Evo 2","author":"Brixi","year":"2025","journal-title":"bioRxiv"},{"key":"10.1016\/j.cbpa.2026.102728_bib75","first-page":"2026","article-title":"Generalise or memorise? Benchmarking ligand-conditioned protein generation from sequence-only data","author":"Vicente-Sola","year":"2026","journal-title":"bioRxiv"},{"key":"10.1016\/j.cbpa.2026.102728_bib76","doi-asserted-by":"crossref","DOI":"10.1016\/j.greenca.2025.03.005","article-title":"Protein language model empowered the robust ASR-driven PET hydrolase featured with two PET binding motifs","author":"Song","year":"2025","journal-title":"Green Carbon"},{"key":"10.1016\/j.cbpa.2026.102728_bib77","unstructured":"P. W. Egea, F. Delhommel, G. Mustafa, F. Leiss-Maier, L. Klimper, T. Badmann, A. Heider, I. Wille, M. Groll, M. Sattler, et al., Inter-domain flexibility and AI-guided sequence optimization enhance de novo enzyme function ."},{"key":"10.1016\/j.cbpa.2026.102728_bib78","doi-asserted-by":"crossref","first-page":"4154","DOI":"10.1021\/acssynbio.4c00624","article-title":"GRACE: generative redesign in artificial computational enzymology","volume":"13","author":"Hu","year":"2024","journal-title":"ACS Synth Biol"},{"key":"10.1016\/j.cbpa.2026.102728_bib79","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1038\/s41586-025-09298-z","article-title":"Design of highly functional genome editors by modelling CRISPR\u2013cas sequences","volume":"645","author":"Ruffolo","year":"2025","journal-title":"Nature"},{"key":"10.1016\/j.cbpa.2026.102728_bib80","doi-asserted-by":"crossref","DOI":"10.1016\/j.biortech.2025.133081","article-title":"Computational-assisted protein engineering to develop thermostable and highly active catalase for industrial and biocatalytic applications","volume":"437","author":"Xu","year":"2025","journal-title":"Bioresour Technol"},{"key":"10.1016\/j.cbpa.2026.102728_bib81","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1038\/s41587-024-02214-2","article-title":"Computational scoring and experimental evaluation of enzymes generated by neural networks","volume":"43","author":"Johnson","year":"2025","journal-title":"Nat Biotechnol"},{"key":"10.1016\/j.cbpa.2026.102728_bib82","article-title":"Replicating PET hydrolytic activity by positioning active sites with smaller synthetic protein scaffolds","volume":"12","author":"Ding","year":"2025","journal-title":"Adv Sci"},{"key":"10.1016\/j.cbpa.2026.102728_bib83","unstructured":"K. Seki, A. B. Guo, D. Akpinaroglu, T. Kortemme, A combinatorial mutational map of active non-native protein kinases by deep learning guided sequence design, bioRxiv ."},{"key":"10.1016\/j.cbpa.2026.102728_bib84","doi-asserted-by":"crossref","first-page":"774","DOI":"10.1038\/s41586-023-05696-3","article-title":"De novo design of luciferases using deep learning","volume":"614","author":"Yeh","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.cbpa.2026.102728_bib85","first-page":"2024","article-title":"Multi-purpose controllable protein generation via prompted language models","author":"Wang","year":"2024","journal-title":"bioRxiv"},{"key":"10.1016\/j.cbpa.2026.102728_bib86","unstructured":"Y. Tan, R. Wang, B. Wu, L. Hong, B. Zhou, Retrieval-enhanced mutation mastery: augmenting zero-shot prediction of protein language model, arXiv preprint arXiv:2410.21127 ."},{"key":"10.1016\/j.cbpa.2026.102728_bib87","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.2313809121","article-title":"Context-dependent design of induced-fit enzymes using deep learning generates well-expressed, thermally stable and active enzymes","volume":"121","author":"Zimmerman","year":"2024","journal-title":"Proc Natl Acad Sci"},{"key":"10.1016\/j.cbpa.2026.102728_bib88","doi-asserted-by":"crossref","first-page":"6273","DOI":"10.1038\/s41467-024-50571-y","article-title":"Context-aware geometric deep learning for protein sequence design","volume":"15","author":"Krapp","year":"2024","journal-title":"Nat Commun"},{"key":"10.1016\/j.cbpa.2026.102728_bib89","doi-asserted-by":"crossref","first-page":"630","DOI":"10.1038\/s41422-024-00989-2","article-title":"Zero-shot prediction of mutation effects with multimodal deep representation learning guides protein engineering","volume":"34","author":"Cheng","year":"2024","journal-title":"Cell Res"},{"key":"10.1016\/j.cbpa.2026.102728_bib90","doi-asserted-by":"crossref","first-page":"1680","DOI":"10.1038\/s41467-026-68384-6","article-title":"Sequence-based generative AI design of versatile tryptophan synthases","volume":"17","author":"Lambert","year":"2026","journal-title":"Nat Commun"},{"key":"10.1016\/j.cbpa.2026.102728_bib91","doi-asserted-by":"crossref","first-page":"15284","DOI":"10.1021\/acs.jafc.4c03126","article-title":"Engineering a robust UDP-glucose pyrophosphorylase for enhanced biocatalytic synthesis via ProteinMPNN and ancestral sequence reconstruction","volume":"72","author":"Li","year":"2024","journal-title":"J Agric Food Chem"}],"container-title":["Current Opinion in Chemical Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1367593126000773?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1367593126000773?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T20:36:57Z","timestamp":1788986217000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1367593126000773"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":91,"alternative-id":["S1367593126000773"],"URL":"https:\/\/doi.org\/10.1016\/j.cbpa.2026.102728","relation":{},"ISSN":["1367-5931"],"issn-type":[{"value":"1367-5931","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Generative artificial intelligence for enzyme design and biocatalysis","name":"articletitle","label":"Article Title"},{"value":"Current Opinion in Chemical Biology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cbpa.2026.102728","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. 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