期刊
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
卷 89, 期 12, 页码 1901-1910出版社
WILEY
DOI: 10.1002/prot.26232
关键词
CASP14; contact prediction; deep convolutional residual neural network; protein folding
This paper reports the performance and mechanism of the tFold framework in CASP14, achieving outstanding results in the long-range contact prediction task.
In this paper, we report our tFold framework's performance on the inter-residue contact prediction task in the 14th Critical Assessment of protein Structure Prediction (CASP14). Our tFold framework seamlessly combines both homologous sequences and structural decoys under an ultra-deep network architecture. Squeeze-excitation and axial attention mechanisms are employed to effectively capture inter-residue interactions. In CASP14, our best predictor achieves 41.78% in the averaged top-L precision for long-range contacts for all the 22 free-modeling (FM) targets, and ranked 1st among all the 60 participating teams. The tFold web server is now freely available at: .
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