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

Chojnowski G.; Simpkin A.J.; Leonardo D.A.; Seifert-Davila W.; Vivas-Ruiz D.E.; Keegan R.M.; Rigden D.J. · IUCrJ (2022) · DOI: 10.1107/s2052252521011088

Resumen

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.

Instituciones: Universidad Nacional Mayor de San Marcos