Assessment of chemical-crosslink-assisted protein structure modeling in CASP13

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  • prot.25816

    Final published version, 3.13 MB, PDF document

  • J. Eduardo Fajardo
  • Rojan Shrestha
  • Nelson Gil
  • Adam Belsom
  • Silvia N. Crivelli
  • Cezary Czaplewski
  • Krzysztof Fidelis
  • Sergei Grudinin
  • Mikhail Karasikov
  • Agnieszka S. Karczyńska
  • Andriy Kryshtafovych
  • Alexander Leitner
  • Adam Liwo
  • Emilia A. Lubecka
  • Bohdan Monastyrskyy
  • Guillaume Pagès
  • Juri Rappsilber
  • Adam K. Sieradzan
  • Celina Sikorska
  • Andras Fiser

With the advance of experimental procedures obtaining chemical crosslinking information is becoming a fast and routine practice. Information on crosslinks can greatly enhance the accuracy of protein structure modeling. Here, we review the current state of the art in modeling protein structures with the assistance of experimentally determined chemical crosslinks within the framework of the 13th meeting of Critical Assessment of Structure Prediction approaches. This largest-to-date blind assessment reveals benefits of using data assistance in difficult to model protein structure prediction cases. However, in a broader context, it also suggests that with the unprecedented advance in accuracy to predict contacts in recent years, experimental crosslinks will be useful only if their specificity and accuracy further improved and they are better integrated into computational workflows.

Original languageEnglish
JournalProteins: Structure, Function and Bioinformatics
Volume87
Issue number12
Pages (from-to)1283-1297
Number of pages15
ISSN0887-3585
DOIs
Publication statusPublished - 1 Dec 2019
Externally publishedYes

Bibliographical note

Erratum: This article corrects the following:
J. Eduardo Fajardo Rojan Shrestha Nelson Gil Adam Belsom Silvia N. Crivelli Cezary Czaplewski Krzysztof Fidelis Sergei Grudinin Mikhail Karasikov Agnieszka S. Karczyńska … See all authors
First published:03 January 2020 https://doi.org/10.1002/prot.25867

    Research areas

  • CASP13, chemical crosslinking/mass spectrometry, chemical-crosslink-assisted protein structure modeling

ID: 238963690