Assessment of chemical‐crosslink‐assisted protein structure modeling in CASP13. Issue 12 (7th October 2019)

• Record Type: Journal Article
• Authors: Fajardo, J. Eduardo; Shrestha, Rojan; Gil, Nelson; Belsom, Adam; Crivelli, Silvia N.; Czaplewski, Cezary; Fidelis, Krzysztof; Grudinin, Sergei; Karasikov, Mikhail; Karczyńska, Agnieszka S.; Kryshtafovych, Andriy; Leitner, Alexander; Liwo, Adam; Lubecka, Emilia A.; Monastyrskyy, Bohdan; Pagès, Guillaume; Rappsilber, Juri; Sieradzan, Adam K.; Sikorska, Celina; Trabjerg, Esben; Fiser, Andras
• Is Part Of: Proteins. Volume 87:Issue 12(2019)
• Page Start: 1283
• Page End: 1297
• Publication Date: 2019-10-07
• Subjects: CASP13 -- chemical crosslinking/mass spectrometry -- chemical‐crosslink‐assisted protein structure modeling; Proteins -- Periodicals; Proteins -- Periodicals; 572.6
• DOI: 10.1002/prot.25816
• Languages: English
• ISSNs: 0887-3585

Abstract

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.