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Deorphanizing Peptides Using Structure Prediction.

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Bibliographic Details
Title:	Deorphanizing Peptides Using Structure Prediction.
Authors:	Teufel F; Digital Science & Innovation, Novo Nordisk A/S, Måløv 2760, Denmark.; Department of Biology, University of Copenhagen Copenhagen 2200, Denmark., Refsgaard JC; Digital Science & Innovation, Novo Nordisk A/S, Måløv 2760, Denmark., Kasimova MA; Digital Science & Innovation, Novo Nordisk A/S, Måløv 2760, Denmark., Deibler K; Digital Science & Innovation, Novo Nordisk A/S, Seattle 98109, Washington, United States., Madsen CT; Global Translation, Novo Nordisk A/S, Måløv 2760, Denmark., Stahlhut C; Digital Science & Innovation, Novo Nordisk A/S, Måløv 2760, Denmark., Grønborg M; Global Translation, Novo Nordisk A/S, Måløv 2760, Denmark., Winther O; Department of Biology, University of Copenhagen, Copenhagen 2200, Denmark.; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby 2800, Denmark.; Department of Genomic Medicine, Copenhagen University Hospital/Rigshospitalet, Copenhagen 2100, Denmark., Madsen D; Digital Science & Innovation, Novo Nordisk A/S, Måløv 2760, Denmark.
Source:	Journal of chemical information and modeling [J Chem Inf Model] 2023 May 08; Vol. 63 (9), pp. 2651-2655. Date of Electronic Publication: 2023 Apr 24.
Publication Type:	Letter
Journal Info:	Publisher: American Chemical Society Country of Publication: United States NLM ID: 101230060 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-960X (Electronic) Linking ISSN: 15499596 NLM ISO Abbreviation: J Chem Inf Model Subsets: MEDLINE
Database:	MEDLINE Ultimate

Description
ISSN:	1549-960X
DOI:	10.1021/acs.jcim.3c00378