Nature Communications (Oct 2019)

A deep learning framework to predict binding preference of RNA constituents on protein surface

  • Jordy Homing Lam,
  • Yu Li,
  • Lizhe Zhu,
  • Ramzan Umarov,
  • Hanlun Jiang,
  • Amélie Héliou,
  • Fu Kit Sheong,
  • Tianyun Liu,
  • Yongkang Long,
  • Yunfei Li,
  • Liang Fang,
  • Russ B. Altman,
  • Wei Chen,
  • Xuhui Huang,
  • Xin Gao

DOI
https://doi.org/10.1038/s41467-019-12920-0
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 13

Abstract

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Interactions between proteins and RNA are an important mechanism for post-transcriptional regulation, but predicting these interactions is difficult. Through a deep learning approach, here the authors predict RNA-binding sites and binding preference based on the local physicochemical properties of the protein surface.