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A Computational Simulation of Determination of Characteristic Frequency for Identification of Hot Spots in Proteins

Sidhartha Sankar Sahoo1, Malaya Kumar Hota1,

1Department of Electronics and Telecommunication Engineering, Synergy Institute of Engineering & Technology, Dhenkanal 759001, Odisha, India

American Journal of Systems and Software. 2014, 2(3), 81-84. DOI: 10.12691/ajss-2-3-5
Published online: August 25, 2017

Abstract

Proteins perform their functions by interaction with other molecules known as target. Protein-target interactions are very specific in nature and occur at predefined locations in proteins known as hotspots. For successful protein-target interaction both protein and target must share common spectral component known as characteristic frequency. Characteristic frequency is very importance since it forms basis for protein-target interactions, thus an approach for determination of characteristic frequency in proteins using discrete cosine transform (DCT) is illustrated in this paper. The performance of the proposed method is observed to be better than existing approaches and is illustrated using simulation examples.

Keywords:

proteins, Electron Ion Interaction Potential (EIIP), consensus spectrum, resonant recognition model (RRM), characteristic frequency, Discrete Cosine Transform (DCT)
[1]  Alberts, B., Bray, D., Johnson, A., Lewis, J., Raff, M., Roberts, K., and Walter P., “Essential Cell Biology”, Garland Publishing, New York, 1998.
 
[2]  Bogan, A. A. and Thorn, K. S., “Anatomy of hot spots in protein interfaces”, Journal of Molecular Biology, 280 (1). 1-9. 1998.View Article  PubMed 
 
[3]  Cosic, I., “Macromolecular bioactivity: is it resonant interaction between macro-molecules? – theory and applications”, IEEE Trans. on Biomedical Engr., 41 (12). 1101-1114. Dec. 1994.View Article  PubMed 
 
[4]  Vaidyanathan, P. P. and Yoon, B.J., “The role of signal-processing concepts in genomics and proteomics”, Journal of the Franklin Institute, 341 (1-2). 111-135. 2004.View Article 
 
[5]  Ramachandran, P., Antoniou, A. and Vaidyanathan, P. P., “Identification and location of hot spots in proteins using the short-time discrete Fourier transform”, in Proc. 38th Asilomar Conf. Signals, Systems, Computers, Pacific Grove, CA. 1656–1660. Nov. 2004.
 
[6]  Ramachandran, P. and Antoniou, A., “Localization of hot spots in proteins using digital filters”, in Proc. IEEE Int. Symp. Signal Processing and Information Technology, Vancouver, BC, Canada. 926–931. Aug. 2006.
 
[7]  Sahu, S.S. and Panda, G., “Efficient Localization of Hot Spot in Proteins Using A Novel S-Transform Based Filtering Approach”, IEEE/ACM Transaction on Computational Biology and Bioinformatics, 8 (5). 1235-1246. 2011.View Article 
 
[8]  Kasparek, J., Maderankova, D. and Tkacz, E., “Protein Hotspot Prediction Using S-Transform. In Information Technologies in Biomedicine”, Springer International Publishing. 3. 327-336. 2014. PubMed 
 
[9]  Sharma, A. and Singh, R., “Determination of Characteristic Frequency in Proteins using Chirp Z-transform”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 2 (6). June 2013.
 
[10]  Swiss-Prot Protein Knowledgebase. Swiss Inst. Bioinformatics (SIB). [Online]. Available: http://us.expasy.org/sprot/.
 
[11]  Protein Data Bank (PDB), Research Collaboratory for Structural Bioinformatics (RCSB). [Online]. Available: http://www.rcsb.org/pdb/.
 
[12]  Yadav, Y. and Wadhwani, S., “Identification of Characteristic frequency in Proteins using Power Spectral Density”, International Journal of Advances in Electronics Engineering, 1 (1). 342-346. 2011.