Energy Landscape View of the Amyloid Aggregator in Protein Folding Problem

Samson O Aisida; Collins U Ibeji; Chibuike D Umeh; Rasheed S Lawal; Doris O Okoroh

Abstract

Energy Landscape View of the Amyloid Aggregator in Protein Folding Problem

Author(s): Samson O Aisida, Collins U Ibeji, Chibuike D Umeh, Rasheed S Lawal, Doris O Okoroh

Amyloid protein aggregation is the basis of many neurodegenerative disorders such as Alzheimer’s, Parkinson’s, type II diabetes, Huntington’s disease and cancer related diseases. These neurodegenerative diseases are associated with aberration of a specific protein affecting its structure-function processes. In this paper, we report a study of the amyloid aggregator using numerical simulations that employ a coarse-grained Monte Carlo method in combination with a diagonally-pull moves neighbourhood search strategy in order to build the hydrophobic-core using the Hydrophobic-Polar energy model on 2D lattice to investigate the misfolded proteins that are susceptible to amyloid aggregates and obtain the pathways to folding landscape. It is evident that multiple pathways which are intermediates prone are responsible for the amyloid related diseases. The simulation reveals the thermodynamics of structural transitions during aggregation and uncovers the intriguing interconnections between the aggregated prone protein and human neurodegenerative diseases. We determine the aggregation pathway by studying aggregation states of 65-mer and 85-mer globular protein and discuss the role of the energy landscape in the management of misfolded proteins. This method is highly effective with the coupled moves and simplifies the complexity of the existing Monte Carlo (MC) and makes it consistent for the native structure prediction (NSP) when compared to other state-of-the-arts approaches.

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