Predicting Proteome-Scale Protein Structure with Artificial Intelligence

Over a matter of months, the application of artificial intelligence and machine learning to the prediction of three-dimensional protein structures resulted in an explosion of knowledge that augurs well for accelerating the identification and targeting of “druggable” proteins.

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Bibliographische Detailangaben
Veröffentlicht in:	The New England journal of medicine 2021-12, Vol.385 (23), p.2191-2194
Hauptverfasser:	Burley, Stephen K, Arap, Wadih, Pasqualini, Renata
Format:	Artikel
Sprache:	eng
Schlagworte:	Amino acids Antigens Archives & records Artificial Intelligence Computational Biology Computer Simulation Computer terminals Coronaviruses COVID-19 Databases, Protein Drug resistance Epidermal growth factor Genetics Genetics General Genomes Hematology Humans Infectious Disease Kinases Learning algorithms Machine learning Mutation NMR Nuclear magnetic resonance Oncology Oncology General Polypeptides Protein Conformation Protein structure Proteins Proteome Proteomes Severe acute respiratory syndrome coronavirus 2 Vaccines
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Beschreibung
Zusammenfassung:	Over a matter of months, the application of artificial intelligence and machine learning to the prediction of three-dimensional protein structures resulted in an explosion of knowledge that augurs well for accelerating the identification and targeting of “druggable” proteins.
ISSN:	0028-4793 1533-4406
DOI:	10.1056/NEJMcibr2113027