A new computational approach for protein sequence similarity analysis and functional classification which is fast and easier compared to the conventional method is described. This technique uses Discrete Wavelet Transform decomposition followed by sequence correlation analysis. The technique can also be used for identifying the functional class of a newly obtained protein sequence. The classification was done using a sample set of 270 protein sequences obtained from organisms of diverse origins and functional classes, which gave a classification accuracy of 94.81%. Accuracy and reliability of the technique is verified by comparing the results with that obtained from NCBI.