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Critical assessment of methods of protein structure prediction (CASP)-Round XIV
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 4626788
Author(s) Kryshtafovych, Andriy; Schwede, Torsten; Topf, Maya; Fidelis, Krzysztof; Moult, John
Author(s) at UniBasel Schwede, Torsten
Year 2021
Title Critical assessment of methods of protein structure prediction (CASP)-Round XIV
Journal Proteins: Structure, Function, and Bioinformatics
Volume 89
Number 12
Pages / Article-Number 1607-1617
Keywords CASP; alphafold; community wide experiment; protein folding; protein structure prediction
Mesh terms Amino Acid Sequence; Computational Biology; Models, Statistical; Molecular Dynamics Simulation; Protein Conformation; Protein Folding; Proteins, metabolism; Sequence Analysis, Protein; Software
Abstract Critical assessment of structure prediction (CASP) is a community experiment to advance methods of computing three-dimensional protein structure from amino acid sequence. Core components are rigorous blind testing of methods and evaluation of the results by independent assessors. In the most recent experiment (CASP14), deep-learning methods from one research group consistently delivered computed structures rivaling the corresponding experimental ones in accuracy. In this sense, the results represent a solution to the classical protein-folding problem, at least for single proteins. The models have already been shown to be capable of providing solutions for problematic crystal structures, and there are broad implications for the rest of structural biology. Other research groups also substantially improved performance. Here, we describe these results and outline some of the many implications. Other related areas of CASP, including modeling of protein complexes, structure refinement, estimation of model accuracy, and prediction of inter-residue contacts and distances, are also described.
Publisher Wiley-Blackwell
ISSN/ISBN 0887-3585 ; 1097-0134
edoc-URL https://edoc.unibas.ch/84744/
Full Text on edoc Available
Digital Object Identifier DOI 10.1002/prot.26237
PubMed ID http://www.ncbi.nlm.nih.gov/pubmed/34533838
ISI-Number WOS:000704287100001
Document type (ISI) Journal Article
 
   

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02/05/2024