FRETpredict: A Python package for FRET efficiency predictions using rotamer libraries.

Montepietra, Daniele; Tesei, Giulio; Martins, João M; Kunze, Micha B A; Best, Robert B; Lindorff-Larsen, Kresten

Montepietra, Daniele; Tesei, Giulio; Martins, João M; Kunze, Micha B A; Best, Robert B; Lindorff-Larsen, Kresten.

Afiliación

Montepietra D; Department of Physics, Computer Science and Mathematics, University of Modena and Reggio Emilia, Via Campi 213/A 41125 Modena, Italy.
Tesei G; Istituto Nanoscienze - CNR-NANO, Center S3, via G. Campi 213/A, 41125 Modena, Italy.
Martins JM; Structural Biology and NMR Laboratory & the Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
Kunze MBA; Structural Biology and NMR Laboratory & the Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
Best RB; Structural Biology and NMR Laboratory & the Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
Lindorff-Larsen K; Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.

bioRxiv ; 2023 Jan 28.

Article en En | MEDLINE | ID: mdl-36789411

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: BioRxiv Año: 2023 Tipo del documento: Article País de afiliación: Italia

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