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findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM

Authors :
Grzegorz Chojnowski
Adam J. Simpkin
Diego A. Leonardo
Wolfram Seifert-Davila
Dan E. Vivas-Ruiz
Ronan M. Keegan
Daniel J. Rigden
Source :
IUCrJ, Vol 9, Iss 1, Pp 86-97 (2022)
Publication Year :
2022
Publisher :
International Union of Crystallography, 2022.

Abstract

Although experimental protein-structure determination usually targets known proteins, chains of unknown sequence are often encountered. They can be purified from natural sources, appear as an unexpected fragment of a well characterized protein or appear as a contaminant. Regardless of the source of the problem, the unknown protein always requires characterization. Here, an automated pipeline is presented for the identification of protein sequences from cryo-EM reconstructions and crystallographic data. The method's application to characterize the crystal structure of an unknown protein purified from a snake venom is presented. It is also shown that the approach can be successfully applied to the identification of protein sequences and validation of sequence assignments in cryo-EM protein structures.

Details

Language :
English
ISSN :
20522525
Volume :
9
Issue :
1
Database :
Directory of Open Access Journals
Journal :
IUCrJ
Publication Type :
Academic Journal
Accession number :
edsdoj.1c2d178143c4afebef407a453f3cfb8
Document Type :
article
Full Text :
https://doi.org/10.1107/S2052252521011088