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Its applications now encompass cellular image classification, genomic studies and drug discovery. While drug development traditionally focused deep learning applications on small molecules, recent innovations have incorporated it in the discovery and development of biological molecules, particularly antibodies. Researchers have devised novel techniques to streamline antibody development, combining in vitro and in silico methods. In particular, computational power expedites lead candidate generation, scaling and potential antibody development against complex antigens. This survey highlights significant advancements in protein design and optimization, specifically focusing on antibodies. This includes various aspects such as design, folding, antibody\u2013antigen interactions docking and affinity maturation.<\/jats:p>","DOI":"10.1093\/bib\/bbae307","type":"journal-article","created":{"date-parts":[[2024,7,4]],"date-time":"2024-07-04T00:03:39Z","timestamp":1720051419000},"source":"Crossref","is-referenced-by-count":53,"title":["Antibody design using deep learning: from sequence and structure design to affinity maturation"],"prefix":"10.1093","volume":"25","author":[{"given":"Sara","family":"Joubbi","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Pisa , Largo B. Pontecorvo, 3, 56127, Pisa, Italy"},{"name":"Data Science for Health (DaScH) Lab, Fondazione Toscana Life Sciences , Via Fiorentina, 1, 53100, Siena, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessio","family":"Micheli","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Pisa , Largo B. 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