ISSN : 0975-3087
EISSN : 0975-9115
Mahalakshmi T.1, Achuthsankar S. Nair2
1Sree Narayana Institute of Technology, University of Kerala, Kollam, Kerala, India– 691010
2Centre for Bioinformatics, University of Kerala, Thiruvananthapuram, Kerala, India–695581
Received : - Accepted : - Published : 21-12-2009
Volume : 1 Issue : 2 Pages : 70 - 80
Int J Bioinformatics Res 1.2 (2009):70-80
DOI : http://dx.doi.org/10.9735/0975-3087.1.2.70-80
Keywords : Hub Proteins, Degree of Connectivity, Shannon Index, Transfer Free Energy to Surface
(TFES), disorder proteins, globular proteins
Conflict of Interest : None declared
Protein-Protein Interaction (PPI) networks are important as they provide clues about the functions of individual proteins as well as enable system level analyses of cellular processes. Predicting hub proteins, the highly connected proteins in PPI networks, is a challenging computational problem. This paper proposes a method for predicting hub proteins from sequence information with 76% accuracy, 84% sensitivity and 71% specificity. In this method, a biodiversity measure, Shannon Index, is used along with an amino acid attribute Transfer Free Energy to Surface (TFES) to distinguish hub proteins from non-hub proteins. Also an analysis of disorderliness in hub proteins revealed that some amino acids have higher composition in hub than in non-hub.
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