Sequence-Based Prediction of RNA-Binding Residues in Proteins

Methods Mol Biol. 2017:1484:205-235. doi: 10.1007/978-1-4939-6406-2_15.

Abstract

Identifying individual residues in the interfaces of protein-RNA complexes is important for understanding the molecular determinants of protein-RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein-RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein-RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner.

Keywords: Binding site prediction; FastRNABindR; Homology-based prediction; Machine learning; PS-PRIP; Protein–RNA interfaces; RNA-binding proteins (RBPs); RNABindRPlus; Ribonucleoprotein particles (RNPs); SNBRFinder.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Amino Acid Sequence / genetics
  • Binding Sites
  • Computational Biology
  • Protein Binding
  • Proteins / chemistry
  • Proteins / genetics*
  • RNA-Binding Proteins / chemistry
  • RNA-Binding Proteins / genetics*
  • Software*

Substances

  • Proteins
  • RNA-Binding Proteins