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

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, Esben TrabjergAndras Fiser*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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
Pages (from-to)1283-1297
Number of pages15
JournalProteins: Structure, Function, and Bioinformatics
Volume87
Issue number12
Early online date30 Sept 2019
DOIs
Publication statusE-pub ahead of print - 30 Sept 2019

Keywords / Materials (for Non-textual outputs)

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

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