Statistical properties of Fibril growth from misfolded proteins

Abstract

Consulta en la Biblioteca ETSI Industriales (Riunet)

[ES] Proteins take part in very important biological processes and in recent years it has been a focus of attention to characterise the structure that these molecules adopt in their functional native states. How they fold into their three dimensional structures is directly related to the way that reactions in these processes take place. Investigation demonstrates that wrong folded proteins are responsible for the development of diseases such as Alzheimer’s or type II diabetes and that is why misfolded proteins are important in biochemical research. To study proteins folding many in vitro experiments have been carried out. For example some studies explain how non dangerous misfolded proteins behave and then apply it to dangerous misfolded proteins (Kunes & Cox, 2005). Other studies investigate how proteins become folded or misfolded. (Tuomas & Knowles, 2009) (Xue & Homans, 2005).The main objective of the study of fibril growth is to understand why and how proteins attain the misfolded structure. Hopefully in the not too distant future will be able to control protein misfolding and improve the therapeutic strategies to combat the misfolding diseases. This project consists of the study of the statistical properties of fibril growth by building a computer programme based on the MonteCarlo method. The project models the fibril growth kinetics without the necessity of laboratory studies and allows the experiments to take place in different conditions in a fast and economic way. The methodology of work was to build an algorithm with FORTRAN able to simulate the fibril growth reaction: nucleation, elongation and fragmentation and, the fibrils size distribution. The results provided by the programme coincide with the ones modelled by theoretical equations; where the results of mass concentration lead to sigmoidal kinetics curves according to the main kinetic models of fibril growth. The lag phase of growth rate, calculated as the line tangent to the sigmoidal curve slope, coincides with the analytical values of the model equations (Tuomas & Knowles, 2009) and the fibrils size distribution behaves as an exponential distribution agreeing with different previous investigations (Kunes & Cox, 2005). This project can be used to help to understand the misfolding process and polymer physics should enable the rational design of drugs to combat the rapidly expanding family of misfolding diseases (Dobson, 2003, Nature).