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 Karczyńska , Andriy Kryshtafovych , Alexander Leitner , Józef Adam Liwo , Emilia Lubecka , Bohdan Monastyrskyy , Guillaume Pagès , Juri Rappsilber , Adam Sieradzan , Celina Sikorska , Esben Trabjerg , Andras Fiser
AbstractWith 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.
|Journal series||Proteins-Structure Function and Bioinformatics, [Proteins: Structure, Function and Genetics], ISSN 0887-3585, e-ISSN 1097-0134, (N/A 100 pkt)|
|Publication size in sheets||0.7|
|Keywords in English||CASP13, chemical crosslinking/mass spectrometry, chemical-crosslink-assisted protein structuremodeling|
|ASJC Classification||; ;|
|Score||= 100.0, 28-01-2020, ArticleFromJournal|
|Publication indicators||= 2; : 2016 = 0.747; : 2018 = 2.501 (2) - 2018=2.285 (5)|
|Citation count*||6 (2020-03-27)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.