Biology subjects

Bowman, G. R.

Publications and source records attributed to Bowman, G. R..

4 recordsLinked to original sources

bioRxiv2018

Enspara: Modeling molecular ensembles with scalable data structures and parallel computing

Markov state models (MSMs) are quantitative models of protein dynamics that are useful for uncovering the structural fluctuations that proteins undergo, as well as the mechanisms of these conformational changes. Given the enormity of conformational space, there has been ongoing interest in identifying a small number of states that capture the essential features of a protein. Generally, this is achieved by making assumptions about the properties of relevant features--for example, that the most important features are those that change slowly. An alternative strategy is to keep as many degrees of freedom as possible and subsequently learn from the model which of the features are most important. In these larger models, however, traditional approaches quickly become computationally intractable. In this paper, we present enspara, a library for working with MSMs that provides several novel algorithms and specialized data structures that dramatically improve the scalability of traditional MSM methods. This includes ragged arrays for minimizing memory requirements, MPI-parallelized implementations of compute-intensive operations, and a flexible framework for model estimation.

biophysics↗

bioRxiv2018

Exposons exploit cooperative changes in solvent exposure to detect cryptic allosteric sites and other functionally-relevant conformational transitions

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 datasets. 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 {beta}-lactamase enzymes that are widespread sources of antibiotic resistance. Experimental tests confirm our predictions for both systems. Importantly, we provide the first evidence for a cryptic allosteric site in CTX-M-9 {beta}-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 {beta}-lactamases to date. Discovery of a similar pocket that was previously overlooked in the well-studied TEM-1 {beta}-lactamase demonstrates the utility of exposons.

biophysics↗

bioRxiv2018

Simulation of spontaneous G protein activation reveals a new intermediate driving GDP unbinding

Activation of heterotrimeric G proteins is a key step in many signaling cascades. However, a complete mechanism for this process, which requires allosteric communication between binding sites that are ~30 [A] apart, remains elusive. We construct an atomically-detailed model of G protein activation by combining three powerful computational methods; metadynamics, Markov state models (MSMs), and CARDS analysis of correlated motions. We uncover a mechanism that is consistent with a wide variety of structural and biochemical data. Surprisingly, the rate-limiting step for GDP release correlates with tilting rather than translation of the GPCR-binding helix 5. {beta}-Strands 1-3 and helix 1 emerge as hubs in the allosteric network that links conformational changes in the GPCR-binding site to disordering of the distal nucleotide-binding site and consequent GDP release. Our approach and insights provide foundations for understanding disease-implicated G protein mutants, illuminating slow events in allosteric networks, and examining unbinding processes with slow off-rates.

biophysics↗

bioRxiv2017

An evolutionary switch in the specificity of an endosomal CORVET tether underlies formation of regulated secretory vesicles in the ciliate Tetrahymena thermophila

In the endocytic pathway of animals, two related complexes, called CORVET (Class C Core Vacuole/Endosome Transport) and HOPS (Homotypic fusion and protein sorting), act as both tethers and fusion factors for early and late endosomes, respectively. Mutations in CORVET or HOPS lead to trafficking defects and contribute to human disease including immune dysfunction. HOPS and CORVET are conserved throughout eukaryotes but remarkably, in the ciliate Tetrahymena thermophila, the HOPS-specific subunits are absent while CORVET-specific subunits have proliferated. VPS8 (Vacuolar Protein Sorting), a CORVET subunit, expanded to 6 paralogs in Tetrahymena. This expansion correlated with loss of HOPS within a ciliate subgroup including the Oligohymenophorea, which contains Tetrahymena. As uncovered via forward genetics, a single VPS8 paralog in Tetrahymena (VPS8A) is required to synthesize prominent secretory granules called mucocysts. More specifically,{triangleup} vps8a cells fail to deliver a subset of cargo proteins to developing mucocysts, instead accumulating that cargo in vesicles also bearing the mucocyst sorting receptor, Sor4p. Surprisingly, although this transport step relies on CORVET, it does not appear to involve early endosomes. Instead, Vps8a associates with the late endosomal/lysosomal marker Rab7, indicating target specificity switching occurred in CORVET subunits during the evolution of ciliates. Mucocysts belong to a markedly diverse and understudied class of protist secretory organelles called extrusomes. Our results underscore that biogenesis of mucocysts depends on endolysosomal trafficking, revealing parallels with invasive organelles in apicomplexan parasites and suggesting that a wide array of secretory adaptations in protists, like in animals, depend on mechanisms related to lysosome biogenesis.\n\nAbbreviations

cell biology↗