Literature DB >> 34473376

When homologous sequences meet structural decoys: Accurate contact prediction by tFold in CASP14-(tFold for CASP14 contact prediction).

Tao Shen1, Jiaxiang Wu1, Haidong Lan1, Liangzhen Zheng1, Jianguo Pei1, Sheng Wang1, Wei Liu1, Junzhou Huang1.   

Abstract

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: https://drug.ai.tencent.com/console/en/tfold.
© 2021 Wiley Periodicals LLC.

Entities:  

Keywords:  CASP14; contact prediction; deep convolutional residual neural network; protein folding

Mesh:

Substances:

Year:  2021        PMID: 34473376     DOI: 10.1002/prot.26232

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  5 in total

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4.  Combining Cryo-EM Density Map and Residue Contact for Protein Secondary Structure Topologies.

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Journal:  Molecules       Date:  2021-11-22       Impact factor: 4.927

Review 5.  Protein design via deep learning.

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  5 in total

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