Prediction and disorderliness of hub proteins

Protein-Protein Interaction (PPI) networks are important as they provide clues about thefunctions of individual proteins as well as enable system level analyses of cellular processes. Predicting hubproteins, the highly connected proteins in PPI networks, is a challenging computational problem. Thispaper 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 anamino acid attribute Transfer Free Energy to Surface (TFES) to distinguish hub proteins from non-hubproteins. Also an analysis of disorderliness in hub proteins revealed that some amino acids have highercomposition in hub than in non-hub.