{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T18:57:27Z","timestamp":1773428247856,"version":"3.50.1"},"reference-count":178,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T00:00:00Z","timestamp":1657670400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"USFQ Collaboration Grant","award":["16885"],"award-info":[{"award-number":["16885"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Antibiotics"],"abstract":"<jats:p>In the last two decades many reports have addressed the application of artificial intelligence (AI) in the search and design of antimicrobial peptides (AMPs). AI has been represented by machine learning (ML) algorithms that use sequence-based features for the discovery of new peptidic scaffolds with promising biological activity. From AI perspective, evolutionary algorithms have been also applied to the rational generation of peptide libraries aimed at the optimization\/design of AMPs. However, the literature has scarcely dedicated to other emerging non-conventional in silico approaches for the search\/design of such bioactive peptides. Thus, the first motivation here is to bring up some non-standard peptide features that have been used to build classical ML predictive models. Secondly, it is valuable to highlight emerging ML algorithms and alternative computational tools to predict\/design AMPs as well as to explore their chemical space. Another point worthy of mention is the recent application of evolutionary algorithms that actually simulate sequence evolution to both the generation of diversity-oriented peptide libraries and the optimization of hit peptides. Last but not least, included here some new considerations in proteogenomic analyses currently incorporated into the computational workflow for unravelling AMPs in natural sources.<\/jats:p>","DOI":"10.3390\/antibiotics11070936","type":"journal-article","created":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T22:06:00Z","timestamp":1657749960000},"page":"936","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":50,"title":["Emerging Computational Approaches for Antimicrobial Peptide Discovery"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9908-2418","authenticated-orcid":false,"given":"Guillermin","family":"Ag\u00fcero-Chapin","sequence":"first","affiliation":[{"name":"CIIMAR\u2014Centro Interdisciplinar de Investiga\u00e7\u00e3o Marinha e Ambiental, Universidade do Porto, Terminal de Cruzeiros do Porto de Leix\u00f5es, Av. General Norton de Matos, s\/n, 4450-208 Porto, Portugal"},{"name":"Departamento de Biologia, Faculdade de Ci\u00eancias, Universidade do Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5222-3324","authenticated-orcid":false,"given":"Deborah","family":"Galpert-Ca\u00f1izares","sequence":"additional","affiliation":[{"name":"Departamento de Ciencia de la Computaci\u00f3n, Universidad Central Marta Abreu de Las Villas (UCLV), Santa Clara 54830, Cuba"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5211-972X","authenticated-orcid":false,"given":"Dany","family":"Dom\u00ednguez-P\u00e9rez","sequence":"additional","affiliation":[{"name":"CIIMAR\u2014Centro Interdisciplinar de Investiga\u00e7\u00e3o Marinha e Ambiental, Universidade do Porto, Terminal de Cruzeiros do Porto de Leix\u00f5es, Av. General Norton de Matos, s\/n, 4450-208 Porto, Portugal"},{"name":"Proquinorte, Unipessoal, Lda, Avenida 5 de Outubro, 124, 7\u00ba Piso, Avenidas Novas, 1050-061 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2721-1142","authenticated-orcid":false,"given":"Yovani","family":"Marrero-Ponce","sequence":"additional","affiliation":[{"name":"Universidad San Francisco de Quito (USFQ), Grupo de Medicina Molecular y Translacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades M\u00e9dicas and Instituto de Simulaci\u00f3n Computacional (ISC-USFQ), Diego de Robles y v\u00eda Interoce\u00e1nica, Quito 170157, Ecuador"}]},{"given":"Gisselle","family":"P\u00e9rez-Machado","sequence":"additional","affiliation":[{"name":"EpiDisease S.L\u2014Spin-Off of Centro de Investigaci\u00f3n Biom\u00e9dica en Red de Enfermedades Raras (CIBERER), 46980 Valencia, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9833-134X","authenticated-orcid":false,"given":"Marta","family":"Teijeira","sequence":"additional","affiliation":[{"name":"Departamento de Qu\u00edmica Org\u00e1nica, Facultade de Qu\u00edmica, Universidade de Vigo, 36310 Vigo, Spain"},{"name":"Instituto de Investigaci\u00f3n Sanitaria Galicia Sur, Hospital \u00c1lvaro Cunqueiro, 36213 Vigo, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1328-1732","authenticated-orcid":false,"given":"Agostinho","family":"Antunes","sequence":"additional","affiliation":[{"name":"CIIMAR\u2014Centro Interdisciplinar de Investiga\u00e7\u00e3o Marinha e Ambiental, Universidade do Porto, Terminal de Cruzeiros do Porto de Leix\u00f5es, Av. General Norton de Matos, s\/n, 4450-208 Porto, Portugal"},{"name":"Departamento de Biologia, Faculdade de Ci\u00eancias, Universidade do Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1016\/S0140-6736(21)02724-0","article-title":"Global burden of bacterial antimicrobial resistance in 2019: A systematic analysis","volume":"399","author":"Murray","year":"2022","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"S14459","DOI":"10.4137\/PMC.S14459","article-title":"Antibiotics and Bacterial Resistance in the 21st Century","volume":"6","author":"Fair","year":"2014","journal-title":"Perspect. Med. 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