In this thesis we implement an ensemble of sequence analysis strategies aimed at identifying functional and structural protein features. The first part of this work was dedicated to two case studies of specific proteins analyzed to provide candidate functional positions for experimental validation: the protein alpha-synuclein (αsyn) and the alanine racemases protein family. In the case of αsyn, the objective was to predict its aggregation prone regions. For the alanine racemase protein family, the scope was to predict sites responsible for substrate specificity. In these two studies, computational predictions allowed systematically exploring potentially functionally relevant protein sites in an efficient manner that may not be possible to implement with traditional experimental approaches. Our strategy provided a powerful forecasting tool for the selection of candidate sites to be later verified experimentally.
In the second part, we analyze the role of intrinsic disorder (ID) as a modulator of protein function in different organisms and cellular processes, which is largely unexplored. As key components of the diverse cellular pathways, disordered proteins are often involved in many diseases, including cancer and neurodegenerative diseases. Thus, there is an impeding need to unveil the general principles underlying the role of ID in proteins. We provide a multi-scale analysis of the involvement of ID in protein function starting with a large-scale analysis at genomic level of the role of ID in Arabidopsis, zooming in into the specific processes of vesicular trafficking in Human and yeast, and finally focusing on specific proteins of diverse organisms.
The results of this thesis provide a better understanding of the functional roles mediated by ID in different organisms and biological processes, such as acting as flexible linkers connecting structured domains, mediating protein-protein interactions, and assisting the quick assembly of large macromolecular complexes. In addition, we present evidence of the use of ID as a mechanism to increase the complexity of protein and biological networks, and as a means to increase the adaptability of proteins in specific processes. Thus, our results contribute to elucidating the relationship between network and organismal complexity and ID, while they also provide evidence of the evolutionary advantages offered by ID.
| Identifer | oai:union.ndltd.org:RICE/oai:scholarship.rice.edu:1911/72021 |
| Date | 16 September 2013 |
| Creators | Pietrosemoli, Natalia |
| Contributors | Ma, Jianpeng |
| Source Sets | Rice University |
| Language | English |
| Detected Language | English |
| Type | thesis, text |
| Format | application/pdf |
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