SPOT-Seq-RNA: Predicting Protein–RNA Complex Structure and RNA-Binding Function by Fold Recognition and Binding Affinity Prediction

  • Yuedong Yang
  • Huiying Zhao
  • Jihua Wang
  • Yaoqi Zhou
Part of the Methods in Molecular Biology book series (MIMB, volume 1137)


RNA-binding proteins (RBPs) play key roles in RNA metabolism and post-transcriptional regulation. Computational methods have been developed separately for prediction of RBPs and RNA-binding residues by machine-learning techniques and prediction of protein–RNA complex structures by rigid or semiflexible structure-to-structure docking. Here, we describe a template-based technique called SPOT-Seq-RNA that integrates prediction of RBPs, RNA-binding residues, and protein–RNA complex structures into a single package. This integration is achieved by combining template-based structure-prediction software, SPARKS X, with binding affinity prediction software, DRNA. This tool yields reasonable sensitivity (46 %) and high precision (84 %) for an independent test set of 215 RBPs and 5,766 non-RBPs. SPOT-Seq-RNA is computationally efficient for genome-scale prediction of RBPs and protein–RNA complex structures. Its application to human genome study has revealed a similar sensitivity and ability to uncover hundreds of novel RBPs beyond simple homology. The online server and downloadable version of SPOT-Seq-RNA are available at


Fold recognition Binding affinity Protein–RNA complex structure Template-based structure prediction Knowledge-based energy function Protein–RNA interactions RNA-binding proteins Torsion-angle prediction Solvent accessible surface area Prediction SPOT-Seq-RNA 



Funding for this work was supported by the National Institutes of Health grants [GM R01 085003 and GM R01 067168 (Co-PI) to Y.Z.] and by the National Natural Science Foundation of China [grant 61271378 to J.W.].


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Yuedong Yang
    • 1
    • 2
    • 3
  • Huiying Zhao
    • 1
    • 2
  • Jihua Wang
    • 4
  • Yaoqi Zhou
    • 1
    • 2
    • 3
  1. 1.School of InformaticsIndiana University Purdue UniversityIndianapolisUSA
  2. 2.Center for Computational Biology and BioinformaticsIndiana University School of MedicineIndianapolisUSA
  3. 3.Institute for Glycomics and School of Information and Communication TechnologyGriffith UniversitySouthportAustralia
  4. 4.Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics and Department of PhysicsDezhou UniversityDezhouChina

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