Structural aspects of the Huntingtin protein investigated by biocomputing methods (2011)

Huntington’s disease (HD) is a neurodegenerative disorder which leads to death within a couple of decades. It causes uncontrolled movements, loss of intellectual faculties and emotional disturbance. HD is a familial disease, passed from parent to child through a mutation in a specific gene, the HTT gene. This gene provides the genetic information for a protein called "Huntingtin" (Htt). Part of this gene is constituted by a repeated triplet of the nucleotides cytosine-adenine-guanine. This triplet encodes for a particular amino acid, glutamine (whose one letter code symbol is "Q"). The number of triplets varies between individuals and generations. If the number of triplets consists of 36 or more the gene encodes for an altered form of the protein, called mutant Huntingtin protein (mut-Htt), with an elongated stretch of Qs (PolyQ). PolyQ, within mut-Htt, may interact abnormally with other proteins. It may also form, in a complex process called misfolding and aggregation, inclusion bodies (aggregates) within cells. The process can be affected rather dramatically by PolyQ's neighboring (or ‘flanking’) regions, in particular by the seventeen amino acids preceding the PolyQ, called N17. These regions may also modulate aggregation by interacting with cellular partners. The resulting aggregates may interfere with the transmission of information within neurons leading to brain damage. Here I have used computational methods to unravel key aspects of the PolyQ stability (i) (which may in turn explain their formation) and of the interactions between N17 and one of its putative cellular partners (ii). (i) By using classical molecular dynamics, I have shown that key factors contributing to PolyQ stability depend mainly on their ability to create a well organized net of tight intramolecular hydrogen-bond interaction. By using quantum-chemistry methods, I have discovered particular features of those interaction networks that are strictly connected with PolyQ polarity and the shape of their electron density. The latter has never been characterized before for such kind of systems. It may be very important to modulate aggregation properties of the PolyQ in mut-Htt.(ii) I have used simulation methods to predict the possible shapes (or conformations) that N17 assumes in aqueous solution. The prediction is fully consistent with the available experimental biophysical data. Hence, I used the results obtained from the simulations about N17 conformations to understand how it can interact with possible cellular partners. For this purpose, in the last part of the thesis, I created a model of N17 interaction with F-actin, which was identified experimentally as a possible mut-Htt interactor by Prof. M. Diamond (U. Washington, San Luis, US). F-actin has been observed to affect intracellular aggregation of mut-Htt. Our model has been successfully validated by a variety of in cell experiments performed by Prof. M. Diamond. It is able to give a reasonable explanation for the effect of F-actin on mut-Htt-aggregation. This approach is one of the first investigations employing biocomputing methods, to investigate Htt-interactor binding at the molecular level. In this thesis, we use several computer-based methods, from atomistic classical and quantum-mechanical simulations to bioinformatics techniques, to investigate a very important disease-linked protein. These approaches successfully allowed me to elucidate some of the crucial facets in HD mechanisms at a molecular level. The approaches are generally applicable and hence they are promising tools to clarify issues in other neurodegenerative diseases as well.