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Proteins. 2019 Dec;87(12):1058-1068. doi: 10.1002/prot.25819. Epub 2019 Oct 24.

Assessing the accuracy of contact predictions in CASP13.

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Department of Systems and Computational Biology, and Department of Biochemistry, Albert Einstein College of Medicine, Bronx, New York.
Genome Center, University of California, Davis, California.


The accuracy of sequence-based tertiary contact predictions was assessed in a blind prediction experiment at the CASP13 meeting. After 4 years of significant improvements in prediction accuracy, another dramatic advance has taken place since CASP12 was held 2 years ago. The precision of predicting the top L/5 contacts in the free modeling category, where L is the corresponding length of the protein in residues, has exceeded 70%. As a comparison, the best-performing group at CASP12 with a 47% precision would have finished below the top 1/3 of the CASP13 groups. Extensively trained deep neural network approaches dominate the top performing algorithms, which appear to efficiently integrate information on coevolving residues and interacting fragments or possibly utilize memories of sequence similarities and sometimes can deliver accurate results even in the absence of virtually any target specific evolutionary information. If the current performance is evaluated by F-score on L contacts, it stands around 24% right now, which, despite the tremendous impact and advance in improving its utility for structure modeling, also suggests that there is much room left for further improvement.


CASP13; contact prediction; protein structure modeling

[Available on 2020-12-01]

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