Biological molecules interact through multiple weak bonds, which define the specificity and the affinity of the interaction. One would expect that the total strength of this interaction would equal the sum of all the contributing weak bonds in isolation. However this is not the case, and interactions are often much weaker or stronger than expected (known as cooperativity). This often corresponds with the function of the molecules. The majority of functional biological molecules are proteins, the large macromolecules that are encoded by DNA. Proteins that bind to rare nutrients (biotin or iron) or highly unstable structures (rate-defining intermediates of chemical reactions) bind more tightly than expected, whereas other proteins bind and release abundant molecules quickly (for example the reactants and products of biochemical reactions, like glucose or lactate), but must still bind specifically. This is most striking in enzymes, which speed up biochemical reactions by binding to rate-defining intermediates of chemical reactions (transition states). They must also bind to the reactants and products of the reactions, which are very similar in chemistry to the transition state, but must be bound much more weakly. The focus of this study is how enzymes combine these two modes of binding in their reaction cycles, and how they use their intrinsic flexibility to do so. We wish to test whether structural tightening provides a mechanism of achieving this discrimination. NMR allows the measurement of the properties of individual atoms within large molecules, but there is a size limit to the size of molecules that can be studied. Over time this size limit is increasing as technology improves and is now at a stage where large enzymes like phosphoglycerate kinase (PGK) can be studied. This project will use this technology to determine the contributions that different atoms within this enzyme make to the binding of the transition state of the reaction it catalyses, using stable chemicals that resemble it (called transition state analogues). The conclusions should be broadly applicable to other enzymes. An understanding of this process is vital to the design inhibitors of enzymes for use as therapeutic agents (drugs) and to technologies that use enzymes out of their biological context, for example bioremediation. It will also help the theoretical understanding of how important biological molecules work.

Investigation of Macrophage Function in an Immunologically Privileged Site. The unique phenotype of the testicular macrophage demands understanding, and this project has the potential to open up an entirely new direction of research. The basic information so generated could facilitate development of strategies to alter either host or donor tissue macrophage functions in order to prevent rejection responses in humans, and be used in the development of new anti-inflammatory drugs. Such technologies will have application in development of novel therapeutics for transplantation and the treatment of chronic inflammatory diseases.

Development of a predictive model for the retention of sports officials. The Australian sport system is facing a critical shortage of sports officials. Over five years the number of officials has declined by 120,000 (26%). Research has not examined the efficacy of organisational support strategies to arrest this decline. Based on commitment, stress and the mediating effect of organisational support this project addresses the retention issue by developing a predictive model of the factors that influence stay/leave behaviour of officials. The outcomes will contribute to a range of evidence-based strategies that will help maximise retention of officials. The project will enhance the sustainability of the Australian sport system and advance retention behaviour research in the emerging field of sport management.

A new source of bivalent molecules from nature. This project aims to describe a new class of naturally occurring multivalent molecules termed secreted cysteine-rich repeat proteins (SCREPs). Multivalency is a key feature of molecular interaction in biology, underlying the high specificity and potency found in many proteins. Focusing on bivalent peptides, the project will generate a database of bioactive SCREPs with similarity to known bioactive peptides, and develop new recombinant methods for their production. The project will use advanced nuclear magnetic resonance spectroscopy to characterise members of this new class, providing new insights into the design of bivalent and multivalent peptides and establishing a new source of molecules with applications in the rapidly growing biotechnology sector.

Hydrologic extremes (floods and intense precipitations) are among Earth’s most common natural hazards and cause considerable loss of life and economic damage. Despite this, some of their key characteristics are still poorly understood at the global scale. The IPCC thus reports “a lack of evidence and thus low confidence regarding the sign of trend in the magnitude and/or frequency of floods on a global scale”. More generally, the space-time variability of hydrologic extremes is yet to be thoroughly described at the global scale. As a striking illustration, the recent initiative “23 unsolved problems in Hydrology that would revolutionise research in the 21st century” of the International Association of Hydrological Sciences includes questions such as: are the characteristics of extreme hydrologic events changing and if so why? How do extremes around the world teleconnect with each other and with other factors? Why do extreme-rich/poor periods exist? It is vital to fill these knowledge gaps to inform design, safety and financial procedures and to improve hazard preparedness and response. The project’s ambition is hence to better understand the global space-time variability of hydrologic extremes, using a three-pillar research strategy based on methodological innovation, extensive data analysis and proof-of-concept case studies. The specific objectives are to: 1. Develop a statistical framework to describe the global-scale variability of extremes in relation to climate; 2. Analyse global precipitation/streamflow datasets with the aim of quantifying teleconnections, spatial clustering, trends and extreme-rich/poor periods, along with their climate drivers; 3. Explore practical applications such as global early warning systems allowing international disaster response organisations to trigger early actions. Successful completion of the project will deliver new tools to analyse extremes at the global scale and will hence contribute to more efficient risk management.