NMR and Computational Characterization of Protein Structure and Ligand Binding

Nuclear magnetic resonance (NMR) techniques combined with computational methods such as docking and cheminformatics were used to characterize protein structure and ligand binding. The thioredoxin system of Mycobacterium tuberculosis consists of a thioredoxin reductase and at least three thioredoxins. This system is responsible for maintaining the cellular protein thiol redox state in normal state. This maintenance is important as the bacterium is engulfed by the human macrophage. Here it is bombarded by reactive oxygen and nitrogen species in an attempt to disrupt normal cellular function in part by perturbing the protein thiols. To this end, the solution structures of the three thioredoxins, A, B, and C, in the oxidized state were solved by NMR. Additionally, the reduced form of thioredoxin C was solved as well. Docking and NMR chemical shit pertubation experiments show promise for the inhibition of the thioredoxin C-thioredoxin reductase catalytic turnover. Automated docking is the process of computationally predicting how tightly a ligand binds to a protein and the correct orientation. The docking of an in-house collection of 10,590 chemicals into a protein called dual specificity phosphatase 5 identified potential ligands. These compounds were characterized as inhibitors in a phosphatase assay and as ligands in NMR chemical shift perturbation experiments. Based on a promising lead compound, additional chemicals were identified using cheminformatics and subjected to the same experimental verification

A general computational tool for structure synthesis

Synthesis of structures is a very difficult task even with only a small number of components that form a system; yet it is the catalyst of innovation. Molecular structures and nanostructures typically have a large number of similar components but different connections, which manifests a more challenging task for their synthesis. This thesis presents a novel method and its related algorithms and computer programs for the synthesis of structures. This novel method is based on several concepts: (1) the structure is represented by a graph and further by the adjacency matrix; and (2) instead of only exploiting the eigenvalue of the adjacency matrix, both the eigenvalue and the eigenvector are exploited; specifically the components of the eigenvector have been found very useful in algorithm development. This novel method is called the Eigensystem method. The complexity of the Eigensystem method is equal to that of the famous program called Nauty in the combinatorial world. However, the Eigensystem method can work for the weighted and both directed and undirected graph, while the Nauty program can only work for the non-weighted and both directed and undirected graph. The cause for this is the different philosophies underlying these two methods. The Nauty program is based on the recursive component decomposition strategy, which could involve some unmanageable complexities when dealing with the weighted graph, albeit no such an attempt has been reported in the literature. It is noted that in practical applications of structure synthesis, weighted graphs are more useful than non-weighted graphs for representing physical systems. Pivoted at the Eigensystem method, this thesis presents the algorithms and computer programs for the three fundamental problems in structure synthesis, namely the isomorphism/automorphism, the unique labeling, and the enumeration of the structures or graphs