Macrocycles (MCs) have become an increasing area of interest for drug design efforts, especially for classically “difficult” targets like protein-protein interactions (PPIs). And although there are many examples of successful MC drugs derived from natural products, there is little information about the characteristics of compounds with effective pharmacological and physicochemical properties. In this dissertation, I describe the development of design guidelines for new MC drugs based on a representative set of known inhibitor MCs and their target proteins. Analysis of both the individual MC structures and their interactions in the protein complex resulted in identification of several structural and physicochemical features likely to promote favorable binding and bioavailability. Additionally, investigation of the binding sites on the proteins suggest that MCs can bind targets conventionally considered “non-druggable,” strengthening the argument for exploring MC compounds to increase the druggable target space. Furthermore, this work includes the application of the proposed design guidelines to the development of synthetic MC libraries for a PPI target, the NEMO/IKKβ complex.

Detection and analysis of protein-ligand binding sites is an important area of research in drug discovery. The FTMap web server is an established computational method for detection of binding hot spots, or regions on the protein surface that contribute disproportionately to the ligand binding free energy. This body of work primarily focuses on the utilization and advancement of FTMap for the study of protein-ligand interactions and their applications to drug discovery. First, the driving forces behind why some proteins require compounds beyond Lipinski’s rule-of-five (bRo5) guidelines are evaluated for 37 protein targets. Three types of proteins are identified on the basis of their binding hot spots, described by FTMap, and their ligand binding affinity profiles. We describe the multifaceted motivations for bRo5 drug discovery for each group of targets, including increased binding affinity, improved selectivity, decreased toxicity, and decreased off-target effects. Second, the conservation of surface binding properties in protein models is evaluated, with particular emphasis on their utility in drug discovery. Here, the probe-binding locations determined by FTMap are used to generate a binding fingerprint, and the Pearson correlation between the binding fingerprint of an experimental structure and a predicted model indicates the level of surface property conservation, without any knowledge of the protein function a priori. This analysis was performed on the protein models submitted to the Critical Assessment of Techniques for Protein Structure Prediction (CASP) rounds 12 and 14, and results were correlated with well-established structure quality metrics. Third, development of the publicly-available FTMove web server (https://ftmove.bu.edu) is described for detection of binding sites and their respective strengths across multiple different conformations of a protein. FTMove was tested on 22 proteins with known allosteric binding sites, and reliably identified both the orthosteric and allosteric binding sites as highly ranked binding sites. The results yield important insight into the dynamics and druggability of such binding sites. Finally, high throughput affinity purified, mass spectrometry data is evaluated for identification of protein-metabolite interactions (PMIs) in Escherichia coli. A detailed search for known PMIs in both the Protein Data Bank and KEGG database is described, and the resulting curated sets of 21 recovered and 37 potentially novel PMIs in E. Coli are presented. Finally, high confidence novel PMIs were evaluated with the template-based small molecule docking program, LigTBM. / 2023-01-26T00:00:00Z

Thesis by publication. / "August 2006" / Thesis (PhD)--Macquarie University, Division of Environmental & Life Sciences, Dept. of Biological Sciences & Dept. of Chemistry & Biomolecular Sciences), 2007. / Bibliography: leaves 157-183. / 1. Introduction -- 1.1. Proteomics and two-dimensional electrophoresis -- 1.2. A proteomic approach to study the filamentous fungus Trichoderma -- 1.3. Aims of the thesis -- 2. Materials and methods -- 3. Results and discussion -- 3.1. Method development for the display and identification of fungal proteins by 2DE and mass spectrometry -- 3.2. Discovery of novel determinants in the biological control of phytopathogens by Trichoderma atroviride -- 3.3. Summary and concluding remarks. / Trichoderma harzianum and T. atroviride are filamentous fungi commonly found in soil. Both display biocontrol capabilities against a range of phytopathogenic fungi including Rhizoctonia solani and Botrytis cinerea which are known pests of hundreds of commercially important crops including tomatoes, potatoes, beans, cucumber, strawberries, cotton and grapes. These Trichoderma species secrete a combination of enzymes degrading cell walls and antibiotics to overgrow and kill fungal phytopathogens. They are seen as an environmentally friendly alternative to chemical fungicides currengly used on crops. / A proteomic approach was taken to separate and identify proteins from a strain of T. harzianum with well established biocontrol properties. Several methods were developed in this thesis to display the whole proteome content and several subcellular proteome fractions from T. harzianum. Proteins were separated by two-dimensional electrophoresis and identified by mass spectrometric methods. The resulting proteomic maps represent the first extensive array of cellular and sub-cellular proteomes for T. harzianum. / Cellular protein patterns of T. atroviride (T. harzianum P1) grown on media containing either glucose or R. solani cell walls were compared by differential gel electrophoresis to identify a suite of new proteins involved in the biological control response. Twenty four T. atroviride protein spots up-regulated in the presence of the R. solani cell walls were identified by mass spectrometry and N-terminal sequencing. Proteins identified from this study included previously implicated enzymes degrading cell walls and three novel proteases, vacuolar serine protease, vacuolar protease A and trypsin-like protease. The genes encoding two of these proteases, vacuolar protease A and vacuolar serine protease have been cloned by degenerate primer PCR and genomic walking PCR and sequenced. The gene sequences and protein sequences derived from these genes have been partially characterised. / Mode of access: World Wide Web. / 194 leaves ill