Your browser doesn't support javascript.
Sequence-assignment validation in cryo-EM models with checkMySequence.
Chojnowski, Grzegorz.
  • Chojnowski G; European Molecular Biology Laboratory, Hamburg Unit, Notkestrasse 85, 22607 Hamburg, Germany.
Acta Crystallogr D Struct Biol ; 78(Pt 7): 806-816, 2022 Jul 01.
Article in English | MEDLINE | ID: covidwho-1922451
ABSTRACT
The availability of new artificial intelligence-based protein-structure-prediction tools has radically changed the way that cryo-EM maps are interpreted, but it has not eliminated the challenges of map interpretation faced by a microscopist. Models will continue to be locally rebuilt and refined using interactive tools. This inevitably results in occasional errors, among which register shifts remain one of the most difficult to identify and correct. Here, checkMySequence, a fast, fully automated and parameter-free method for detecting register shifts in protein models built into cryo-EM maps, is introduced. It is shown that the method can assist model building in cases where poorer map resolution hinders visual interpretation. It is also shown that checkMySequence could have helped to avoid a widely discussed sequence-register error in a model of SARS-CoV-2 RNA-dependent RNA polymerase that was originally detected thanks to a visual residue-by-residue inspection by members of the structural biology community. The software is freely available at https//gitlab.com/gchojnowski/checkmysequence.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Artificial Intelligence / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Acta Crystallogr D Struct Biol Year: 2022 Document Type: Article Affiliation country: S2059798322005009

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Artificial Intelligence / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Acta Crystallogr D Struct Biol Year: 2022 Document Type: Article Affiliation country: S2059798322005009