Calculation of Shannon Entropy – in pits unit – for Amyloid-Beta Aggregation Protein Network

Abstract

Herein, with a Shannon entropic inference of networks, we provide evidence on a novel methodology to be used in network analysis. Our objective is to identify the key proteins in the pathogenesis of AD and to prioritize them in the AD network by their level of importance. Methods: We use an original computational methodology to approach the AD protein network. The method is based on calculating the level of disorder, i.e. the amount of information carried or Shannon’s entropy (CAIR), in proteins. We have provided an estimation to calculate the amount of mutual information between a protein and its respective network (EMIP). Results: After performing a thorough literature review, we report 97 proteins that have been shown to be principal in the AD pathogenesis. We have calculated the residue frequency and CAIR for all of the proteins included. Moreover, we report EMIP for all proteins and show that how it fits the contemporary knowledge about the disease. Our results further emphasize on the importance of Aβ cascade hypothesis and introduce some relatively unexplored targets for future therapeutics.