IUCrJ (Jan 2022)

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

  • Grzegorz Chojnowski,
  • Adam J. Simpkin,
  • Diego A. Leonardo,
  • Wolfram Seifert-Davila,
  • Dan E. Vivas-Ruiz,
  • Ronan M. Keegan,
  • Daniel J. Rigden

DOI
https://doi.org/10.1107/S2052252521011088
Journal volume & issue
Vol. 9, no. 1
pp. 86 – 97

Abstract

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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.

Keywords