Molecular de-extinction of ancient antimicrobial peptides enabled by machine learning.

Maasch, Jacqueline R M A; Torres, Marcelo D T; Melo, Marcelo C R; de la Fuente-Nunez, Cesar

Maasch, Jacqueline R M A; Torres, Marcelo D T; Melo, Marcelo C R; de la Fuente-Nunez, Cesar.

Afiliación

Maasch JRMA; Department of Computer and Information Science, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therap
Torres MDT; Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, Department of Chemical a
Melo MCR; Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, Department of Chemical a
de la Fuente-Nunez C; Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, Department of Chemical a

Cell Host Microbe ; 31(8): 1260-1274.e6, 2023 08 09.

Article en En | MEDLINE | ID: mdl-37516110

Asunto(s)

Antiinfecciosos; Péptidos Antimicrobianos; Animales; Humanos; Ratones; Péptidos/farmacología; Antibacterianos/farmacología; Aprendizaje Automático; Péptido Hidrolasas; Pruebas de Sensibilidad Microbiana

Palabras clave

Denisovan; Neanderthal; antibiotic resistance; antibiotics; antimicrobial peptides; drug discovery; hominins; machine learning; mouse models; protein engineering

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Péptidos Antimicrobianos / Antiinfecciosos Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: Cell Host Microbe Asunto de la revista: MICROBIOLOGIA Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos

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