| Literature DB >> 31569265 |
J Eduardo Fajardo1,2, Rojan Shrestha1,2, Nelson Gil1,2, Adam Belsom3, Silvia N Crivelli4, Cezary Czaplewski5, Krzysztof Fidelis6, Sergei Grudinin7, Mikhail Karasikov8,9,10, Agnieszka S Karczyńska5, Andriy Kryshtafovych6, Alexander Leitner11, Adam Liwo5,12, Emilia A Lubecka13, Bohdan Monastyrskyy6, Guillaume Pagès7, Juri Rappsilber2,14, Adam K Sieradzan5, Celina Sikorska5, Esben Trabjerg11, Andras Fiser1,2.
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.Entities:
Keywords: CASP13; chemical crosslinking/mass spectrometry; chemical-crosslink-assisted protein structure modeling
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Year: 2019 PMID: 31569265 PMCID: PMC6851497 DOI: 10.1002/prot.25816
Source DB: PubMed Journal: Proteins ISSN: 0887-3585