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Cooperative Changes in Solvent Exposure Identify Cryptic Pockets,Switches, and Allosteric Coupling
Authors:Justin R Porter  Katelyn E Moeder  Carrie A Sibbald  Maxwell I Zimmerman  Kathryn M Hart  Michael J Greenberg  Gregory R Bowman
Institution:1. Department of Biochemistry & Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri;2. Department of Chemistry, Williams College, Williamstown, Massachusetts;3. Department of Biomedical Engineering and Center for Biological Systems Engineering, Washington University in St. Louis, St. Louis, Missouri
Abstract:Proteins are dynamic molecules that undergo conformational changes to a broad spectrum of different excited states. Unfortunately, the small populations of these states make it difficult to determine their structures or functional implications. Computer simulations are an increasingly powerful means to identify and characterize functionally relevant excited states. However, this advance has uncovered a further challenge: it can be extremely difficult to identify the most salient features of large simulation data sets. We reasoned that many functionally relevant conformational changes are likely to involve large, cooperative changes to the surfaces that are available to interact with potential binding partners. To examine this hypothesis, we introduce a method that returns a prioritized list of potentially functional conformational changes by segmenting protein structures into clusters of residues that undergo cooperative changes in their solvent exposure, along with the hierarchy of interactions between these groups. We term these groups exposons to distinguish them from other types of clusters that arise in this analysis and others. We demonstrate, using three different model systems, that this method identifies experimentally validated and functionally relevant conformational changes, including conformational switches, allosteric coupling, and cryptic pockets. Our results suggest that key functional sites are hubs in the network of exposons. As a further test of the predictive power of this approach, we apply it to discover cryptic allosteric sites in two different β-lactamase enzymes that are widespread sources of antibiotic resistance. Experimental tests confirm our predictions for both systems. Importantly, we provide the first evidence, to our knowledge, for a cryptic allosteric site in CTX-M-9 β-lactamase. Experimentally testing this prediction did not require any mutations and revealed that this site exerts the most potent allosteric control over activity of any pockets found in β-lactamases to date. Discovery of a similar pocket that was previously overlooked in the well-studied TEM-1 β-lactamase demonstrates the utility of exposons.
Keywords:Corresponding author
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