SNB‐PSSM: A spatial neighbor‐based PSSM used for protein–RNA binding site prediction

Abstract Protein–RNA interactions play essential roles in a wide variety of biological processes. Recognition of RNA‐binding residues on proteins has been a challenging problem. Most of methods utilize the position‐specific scoring matrix (PSSM). It has been found that considering the evolutionary information of sequence neighboring residues can improve the prediction. In this work, we introduce a novel method SNB‐PSSM (spatial neighbor–based PSSM) combined with the structure window scheme where the evolutionary information of spatially neighboring residues is considered. The results show our method consistently outperforms the standard and smoothed PSSM methods. Tested on multiple datasets, this approach shows an encouraging performance compared with RNABindRPlus, BindN+, PPRInt, xypan, Predict_RBP, SpaPF, PRNA, and KYG, although is inferior to RNAProSite, RBscore, and aaRNA. In addition, since our method is not sensitive to protein structure changes, it can be applied well on binding site predictions of modeled structures. Thus, the result also suggests the evolution of binding sites is spatially cooperative. The proposed method as an effective tool of considering evolutionary information can be widely used for the nucleic acid–/protein‐binding site prediction and functional motif finding.