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

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.

SUBMITTER: Chojnowski G

PROVIDER: S-EPMC8733886 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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

Chojnowski Grzegorz G Simpkin Adam J AJ Leonardo Diego A DA Seifert-Davila Wolfram W Vivas-Ruiz Dan E DE Keegan Ronan M RM Rigden Daniel J DJ

IUCrJ 20211201 Pt 1

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 crystallographi ...[more]

PMID: 35059213

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