Dynamic structural science: exploring energy landscapes in complex enzyme systems

Proteins are dynamic molecules. Motions within a protein molecule can be localised (e.g. bond vibrations, backbone and side chain motions) occuring on relatively fast timescales, or large scale motions (domain motions, conformational changes and slow breathing modes) that typically occur on the millisecond to second timescale. Localised fast motions can influence the chemistry in enzyme active sites; larger scale motions bring active sites together, or facilitate long range communication, for example in the transfer of electrons over large distances in redox enzymes, information transfer through signalling cascades or the folding of protein molecules. These large scale motions give rise to the concept of energy landscapes - that is the free energy surface that accommodates all conformations of the protein macromolecule that are populated. The distribution of conformational states across this landscape can be perturbed, for example by ligand or drug binding, natural variation in sequence (polymorphisms) or partner protein binding. Our knowledge of the spatial distribution and temporal exploration of these landscapes is at best limited, attributed in the main to the lack of general structural and biophysical tools to capture this information. The three dimensional structures of 'rigid' protein modules are readily accessed using conventional approaches (crystallography, NMR spectroscopy). How multiple modules communicate in complex protein systems however is not accessible using these techniques. In this application we aim to develop robust experimental methods using state-of-the-art spectroscopic, kinetic and computational methods that enable investigators to study the spatial and temporal properties of landscapes and their remodelling by small molecule/protein binding. We aim to develop these methods using mammalian nitric oxide synthases, redox enzymes that are constructed from multiple functional domain the chemistry of which is coupled to major dynamical excursions during the course of the enzyme catalysed reaction. We aim to define the structures of multiple conformational states across the landscape, define the timeconstants for their interconversion and assess the functional importance of these structural transitions in the catalytic cycle of the enzyme. By providing atomic level spatial and time resolved information on the functional dynamics in nitric oxide synthase enzymes we envisage that new opportunities will accrue to develop selective inhibitors that interfere with dynamical processes linked to function. This will reinvigorate the search for isoform specific inhibitors of these enzymes, and also provide general tools for similar analysis of other dynamic systems from which function and therapeutic intervention can be studied.

Conformational control limits most electron transfer (ET) reactions in biology, but we lack general insight into the extent of conformational space explored, and specifically the properties of the associated energy landscape. In this proposal we will unite pulsed electron-electron double resonance (ELDOR) studies of various radical forms of nitric oxide synthase (NOS) - a mammalian NADPH-linked diflavin oxidoreductase required for NO generation and signalling - with functional studies of internal ET to gain new insight into the extent and properties of the energy landscape for conformationally controlled ET. This will be complemented by studies employing high pressure EPR and stopped-flow spectrscopy, fluorescence energy transfer and freeze trapping to experimentally access the energy landscape. Computational and SAXS methods will provide additonal constraints from which to analyse our pulsed ELDOR distance measurements. This will assist in the construction of higher order (dynamic) protein structures for NOS through triangulation methods. In supporting work we have identified multiple conformations of di-semiquinoid NOS, which point to a rugged and more complex energy landscape than that inferred from simple models (bimodal open and closed states) derived from the crystal structures of NOS reductase. We now aim to map the dynamic properties of this complex landscape and correlate our observations with functional data on electron transfer and catalysis - information that on the long term will provide new opportunities for therapeutic intervention in the NOS family of isoenzymes. We suggest our approach is general that can be used to gain new insight into energy landscapes for a variety of complex and dynamic protein systems.

In the 21st century a major challenge in structural biology is the development of enabling technology to inform on the spatial and temporal properties of dynamic and complex macromolecules. In general, traditional structural biology approaches provide static snapshots of macromolecular structure; information on dynamical properties is more difficult to obtain and in the main relies on computational and spectroscopic (e.g. NMR) methods. Increasingly, the importance of conformational/energy landscapes in macromolecular function is being recognised, for example in relation to folding transitions, signalling cascades and catalysis. The concept of landscapes is central to biological function, but tools to interrogate their spatial and temporal properties at atomic resolution are lacking. The transient nature of higher order structure is formed from the multiple interactions between structured domains across a landscape, or from transitions of disordered regions to more ordered structures. It is these landscapes (and their remodelling through ligand and partner protein binding) that control function and provide new opportunities for therapeutic intervention of biological function. We will develop new tools to identify and study the interchangeability of higher order structure in dynamic protein systems using mammalian nitric oxide synthase as a target protein system. These tools will be of general use across the structural biology community. They will enable new areas of inquiry into higher order structure in general, and will relate dynamical structural excursions to protein function. In the longer term these tools will also present new opportunities in drug discovery programmes that aim to target, for example, dynamic protein-protein interfaces. The beneficiaries are therefore both academic and commercial. There are potential long term benefits for the health care professions through the development of novel therapeutic strategies (improving the quality of life) and for wealth creation (underpinning drug discovery programmes). With specific reference to nitric oxide synthases, there is a real need to develop new strategies for selective therapeutic intervention. To date the focus has been on targeted intervention of NO generation through the development of active site (heme oxygenase domain) inhibitors. These programmes have generally failed to identify isoform specific reagents that target differentially the iNOS, eNOS and nNOS isoforms. An understanding of higher order stucture (at both the spatial and temporal levels) that is linked to NOS function will provide new opportunities for inhibitor design by targetting protein interfaces that form transiently between redox domain modules. Staff working on this project will gain new skills in the integration of dynamic EPR datasets with computational and functional studies. These skills will translate to other projects concerned with the analysis of higher order protein structure. Training will be in new quantitative biophysical methods, computational simulations and kinetic methods. The project will also lead to the development of unique instrument infrastructure within the UK academic sector. This unique environment and skill base will enable us to train and translate programmes involving dynamic structural analysis of macromolecules to other protein systems. Our strong link with Bruker (manufacturers of our advanced EPR instruments) will ensure that commercial opportunities in the application of ELDOR, high pressure EPR and time resolved EPR are identified and explored optimally to facilitate 'take up' of our methods by other workers.