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

Author:

Chojnowski GrzegorzORCID,Simpkin Adam J.,Leonardo Diego A.,Seifert-Davila WolframORCID,Vivas-Ruiz Dan E.,Keegan Ronan M.,Rigden Daniel J.ORCID

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.

Funder

Biotechnology and Biological Sciences Research Council

Publisher

International Union of Crystallography (IUCr)

Subject

Condensed Matter Physics,General Materials Science,Biochemistry,General Chemistry

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