Discovering and Manipulating Macromolecular Conformational Ensembles

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PROJECT SUMMARY Macromolecules fluctuate between different structural states of a conformational ensemble. One of the major effects of ligands and mutations is to change the relative stability of these different states. However, most of our structural biology modeling revolves around a paradigm of distinct and singular structures. Our major goal is to move beyond static images of biological macromolecules, while retaining the ability to interrogate the resulting models to improve ligand design and mutational engineering. We are also interested in creating experimental methods to perturb the relative populations of these conformations, using temperature or chemical perturbation to bring them into the window where they can be observed and modeled. In two previous grants supported by NIGMS, we have focused three primary technologies: 1) ensemble modeling, where alternative conformations present in X-ray (and now, increasingly, cryoEM) density maps are explicitly identified and refined as a conformational ensemble or multiconformer model; 2) multitemperature crystallography, where the temperature of X-ray data collection is shifted, while avoiding radiation damage, to change the relative balance of different populations; 3) model validation, where the density at specific points is quantified to support or falsify modelling. We have applied these paradigms broadly and collaboratively, with a commitment to open methods and software. Two major foci have been: 1) ligand discovery using combinations of multitemperature crystallography and empirical X-ray fragment screening (most notably to identify new ways to allosterically inhibit the phosphatase PTP1B); 2) protein mutational engineering (most notably in the context of protein design and in understanding the relationship between conformation dynamics and catalysis). With MIRA support, we will continue our computational developments to further improve cryoEM modeling of alternative conformations, to perform large scale test of the effects of ligand binding on protein conformational heterogeneity, to improve validation and comparison of distinct ensemble model types, and to quantify density signals for alternative conformations, hydrogens, and modifications. In parallel, our experimental work will focus on the structural basis of new ligands to counter antibiotic resistance and on defining the conformational landscape of the oligomeric enzyme glutamine synthetase. Our experimental work provides an important testbed for new computational innovations and ways to validate the importance of newly modeled alternative conformations. MIRA support will also enable us to conduct our research in a transparent and open manner, dedicating ourselves further into early data disclosure (e.g. preprints and posts on our website) and data reuse (e.g. deposition of primary diffraction and EM data), which are already paying dividends by enabling other researchers. In summary, our research will create robust experimental and computational methods to access conformational ensembles and provide avenues to exploit conformational heterogeneity for useful ends.