Hot spots localization in proteins by optimized short time Ramanujan Fourier transform

Specific functions in biological processes are dependent on protein-protein interactions. Hot spot residues play a key role in the determination of these interactions and have wide applications in engineering proteins and drug discovery. Experimental techniques to identify hotspots are often labor intensive and expensive. Also, most of the computational methods which have been developed are structure based and need some training. In this work, hotspots have been identified by sequence information alone using the Resonant Recognition Model (RRM). The proposed method uses characteristic period in place of traditionally used characteristic frequency by RRM-based methods. The characteristic period has been extracted from the consensus spectrum of protein families using the Ramanujan Fourier Transform (RFT). Position-period plots for proteins have been generated using Short Time RFT (ST-RFT) with a Gaussian window. Hot spots have been identified by thresholding of the signal corresponding to the protein's characteristic period in the ST-RFT. To enhance the performance of the ST-RFT, Gaussian window shape parameter has been optimized using concentration measure as a metric. Better sensitivity of this method has been observed compared to other reported RRM-based methods. Since the method is model independent it does not requires any training and can be readily used for any protein sequence provided its interface residues and protein family are known.