Nature Communications (May 2021)

Structure-based protein function prediction using graph convolutional networks

  • Vladimir Gligorijević,
  • P. Douglas Renfrew,
  • Tomasz Kosciolek,
  • Julia Koehler Leman,
  • Daniel Berenberg,
  • Tommi Vatanen,
  • Chris Chandler,
  • Bryn C. Taylor,
  • Ian M. Fisk,
  • Hera Vlamakis,
  • Ramnik J. Xavier,
  • Rob Knight,
  • Kyunghyun Cho,
  • Richard Bonneau

DOI
https://doi.org/10.1038/s41467-021-23303-9
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 14

Abstract

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The rapid increase in the number of proteins in sequence databases and the diversity of their functions challenge computational approaches for automated function prediction. Here, the authors introduce DeepFRI, a Graph Convolutional Network for predicting protein functions by leveraging sequence features extracted from a protein language model and protein structures.