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OJBTM
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
ABSTRACT
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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