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

Journal: Proteins
Published Date:

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.

Authors

  • Tao Shen
    Shanghai Chenpon Pharmaceutical Co., Ltd., Shanghai, China.
  • Jiaxiang Wu
    Tencent AI Lab, Shenzhen, China.
  • Haidong Lan
    Tencent AI Lab, Shenzhen, China.
  • Liangzhen Zheng
    Tencent AI Lab, Shenzhen, China.
  • Jianguo Pei
    Software and Services Group, Intel Corporation, Shanghai, China.
  • Sheng Wang
    Intensive Care Medical Center, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, People's Republic of China.
  • Wei Liu
    Department of Radiation Oncology, Mayo Clinic, Scottsdale, AZ, United States.
  • Junzhou Huang