Resum

The project entitled “Sequential and structural determinants of protein aggregation” aims to study the factors that control protein deposition but also tries to develop new strategies to facilitate its comprehension.

Protein aggregation is related with an increasing number of human disorders such as Alzheimer’s disease, Parkinson disease or type II diabetes. Understanding the determinants that modulate the deposition process is a necessary step to develop new strategies to tackle these debilitating pathologies. Additionally, the accumulation of heterologous protein as intracellular aggregates during recombinant expression represents one of the main problems in down stream processing. Accordingly, understanding the factors behind the production of recombinant protein might lead to new avenues to increase the solubility and functionality of recombinant proteins. During the development of the present thesis we have used a wide range of techniques to analyse protein aggregation process in three different frameworks: in vitro, in vivo and in silico. The depositional properties of polypeptides differing in structure, sequence, and function were studied. The data obtained reveal the importance of the intrinsic polypeptide chain properties to protein aggregation and reveal the general rules controlling polypeptide deposition. This information permitted the development of an algorithm able to locate key depositional regions and calculate the global aggregation propensity of a protein starting from their amino acid sequence. This tool can be used for the analysis of the aggregation properties of large protein sets as show here for cytosolic bacterial proteins.

Overall, the results collected in the present thesis could be valuable for biomedicine area suggesting new therapeutic targets to fight against depositional diseases as well as new approaches to increase the protein quality during protein production. It is also shown that folding and aggregation turn two be two side of the same coin that compete with each other.

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