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Assessment of chemical-crosslink-assisted protein structure modeling in CASP13 |
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| Authors: | 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 Trabjerg Andras Fiser |
| Affiliation: | 1. Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York Department of Biochemistry, Albert Einstein College of Medicine, Bronx, New York;2. Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany;3. Department of Computer Science, UC Davis, Davis, California;4. Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland;5. Genome Center, University of California, Davis, California;6. University of Grenoble Alpes, CNRS, Grenoble, France;7. Center for Energy Systems, Skolkovo Institute of Science and Technology, Moscow, Russia Moscow Institute of Physics and Technology, Moscow, Russia Department of Computer Science, ETH Zurich, Zurich, Switzerland;8. Department of Biology, Institute of Molecular Systems Biology, Zurich, Switzerland;9. Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Republic of Korea;10. Institute of Informatics, Faculty of Mathematics, Physics, and Informatics, University of Gdańsk, Gdańsk, Poland;11. Department of Biochemistry, Albert Einstein College of Medicine, Bronx, New York Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK;12. Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York |
| 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. |
| Keywords: | CASP13 chemical crosslinking/mass spectrometry chemical-crosslink-assisted protein structure modeling |