ComplexContact: a web server for inter-protein contact prediction using deep learning.

Journal: Nucleic acids research
Published Date:

Abstract

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

Authors

  • Hong Zeng
    School of Computer Science and Technology, Hangzhou Dianzi University, China.
  • Sheng Wang
    Intensive Care Medical Center, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, People's Republic of China.
  • Tianming Zhou
    Toyota Technological Institute at Chicago, USA.
  • Feifeng Zhao
    School of Computer Science and Technology, Hangzhou Dianzi University, China.
  • Xiufeng Li
    School of Computer Science and Technology, Hangzhou Dianzi University, China.
  • Qing Wu
    5 Department of Environmental and Occupational Health, School of Community Health Sciences, University of Nevada , Las Vegas, Nevada.
  • Jinbo Xu
    Toyota Technological Institute at Chicago, Chicago, IL 60615, USA.