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.