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Online Journal of Bioinformatics ©
Volume 16 (1): 29-50, 2015.
Support vector machine to predict human death domain protein-protein interactions
1,*Prakash A. Nemade, 2Kamal R. Pardasani
1Department of Bioinformatics, Maulana Azad National Institute of Technology, 2Department of Mathematics, Maulana Azad National Institute of Technology, Bhopal, India
Nemade PA, Pardasani KA., Support vector machine to predict human death domain protein-protein interactions, Onl J Bioinform., 16 (1): 29-50, 2015. Protein-Protein Interactions (PPIs) regulate DNA transcription, replication, metabolic cycles and signaling cascades and cell death via apoptosis and necrosis in eukaryotic cells. Apoptosis an orderly cellular suicide program, is critical for development and homeostasis of multi-cellular organisms. Failure to control apoptosis can have catastrophic consequences. The cascade of reactions by Caspase, CARD, NLRP, NOD, FADD, DEDD, POP, Myd88 proteins are involved in the process of cell death. High throughput experimental methods for determining PPIs are time consuming, expensive generating huge amounts of PPI data. There is need to develop computational methods to efficiently and accurately predict PPIs. We describe a model for predicting human death domain (DD) PPI based on seven physicochemical, biochemical & structural features of amino acids monomers of proteins. Protein primary sequences are encoded into sequential features represented by descriptors. Then, the Support Vector Machine and Sequential Minimal Optimization of WEKA tool is employed to classify interacting and non-interacting protein pairs. The various kernel functions were evaluated to build the model and it was observed that libSVM with linear kernel was found to be best on the basis of performance measures. The validation has been performed by 10 fold cross validation technique. The optimum model gives accuracy of 75% in predicting human DD-PPI. Such models can be useful in providing PPI information of DD proteins which can be useful in understanding the molecular mechanisms involved in cell death taking place due to ageing, programmed cell death and various diseases. It may through some light on the study of cancerous cell and gerontology.
Keywords: Protein-Protein Interactions, Cell Death, Support Vector Machine, Apoptosis, Death domain, Death effector domain, Caspase recruitment domain, Pyrin domain, Caspases, Myd88.
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