There are different conformational states of proteins characterized by different Gibbs free energy levels, manifested in folding-unfolding dynamics, for example. Recently, a set of protein states, which require relatively small amount of folding energies, emerged as subjects of intensive research, and proteins or regions characterized by the presence of these states have been termed as ‘Intrinsically Disordered Proteins’ (IDP) and ‘Intrinsically Disordered Protein Regions’ (IDPR), respectively. Predisposition for intrinsic disorder of a query protein is encoded in its amino acid sequence and composition, and can be rather accurately predicted using several intrinsic disorder algorithms. Since pathology of many human diseases can be driven by proteins characterized by high intrinsic disorder scores, research on various disease-associated proteins is often started with the analysis of their intrinsic disorder propensities. In this work, I utilized computational approaches based on the concept of intrinsic disorder to address three health-related issues. To this end, I developed a novel computational platform for disorder-based drug discovery and applied this tool for finding inhibitors of the cancer-related MBD2-NuRD complex, utilized molecular dynamic simulations to explain the effects of mutations on the functionality of the X-linked protoporphyria-related protein ALAS, and used bioinformatics tools to examine the effects ofcardiomyopathy-related mutations in cardiac troponin.
Since the complex between the Methyl-CpG-binding domain protein 2 (MBD2) and the Nucleosome Remodeling Deacetylase complex (NuRD) specifically binds to the mCpG-island and blocks tumor suppressor gene expression, finding an inhibitor of this MBD2-NuRD complex is hypothesized to be important for the development of novel anti-cancer drugs. I found that the site, which is responsible for the MBD2 interaction with thetranscriptional repressor p66-α (p66α, which is a part of the NuRD complex), is characterized by a specific disorder-to-order transition pattern, this pattern showed a remarkable similarity to the disorder-to-order pattern of the Myc transcription factor binding site for the Max transcription factor. Importantly, several inhibitors of the Myc-Max interaction targeting the disorder-to-order transition site of Myc were previously described. By applying molecular docking at the disorder-to-order transition site of MBD2, two compounds were identified and further evaluated through molecular dynamics simulations. Anti-leukemia and anti-metastasis effectiveness of these compounds was demonstrated in dedicated in vitro and in vivo experiments conducted by our collaborators.
In relation to the defective protein associated with the X-linked protoporphyria (XLPP), the hepta-variant of mouse erythroid 5-aminolevulinate synthase (mALAS2), previously shown to be characterized by a remarkable acceleration of the reaction rate, was investigated through molecular dynamics simulations. In this study, a loop to β-strand transition was observed, and this observation was crucial for a better understanding of the previously described rate-enhancing effects of seven simultaneous variations in the active loop site of this protein.
Finally, a wide spectrum of bioinformatics tools was applied to carefully analyze a potential role of intrinsic disorder in a set of cardiomyopathy-related mutations in the components of human cardiac troponin. This analysis revealed that, in comparison with the wild type troponin, chains containing the disease-associated mutations were typically characterized by a local decrease in intrinsic disorder propensity. These mutations affected some disorder-based protein-protein interaction sites and caused remarkable rearrangements of the complex pattern of post-translational modifications.
Therefore, this work illustrates that inclusion of the protein intrinsic disorder analysis into the arsenal of techniques used by the biomedical researchers represents an important and promising approach that provides novel inputs for the better understanding of protein behavior in relation to human disease at the molecular level. Techniques and methods developed and utilized in this study will significantly contribute to future biomedical research.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-8113 |
| Date | 29 June 2017 |
| Creators | Na, Insung |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
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