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Bowman, G. R.

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

36 records · Page 2Linked to original sources

A nepenthesin insert allosterically controls catalysis in the malaria parasite protease plasmepsin V

Plasmepsin V (PM V) is a pepsin-like aspartic protease essential for growth of the malaria parasite Plasmodium falciparum. Previous work has shown PM V to be an ER-resident protease that processes parasite proteins destined for export into the host cell. Depletion or inhibition of the enzyme is lethal during asexual replication within red blood cells, as well as during the formation of sexual stage gametocytes. The structure of the P. vivax PM V has been characterized by x-ray crystallography, revealing a canonical pepsin fold punctuated by structural features uncommon to secretory aspartic proteases. Here we use parasite genetics to probe these structural features by attempting to rescue lethal PM V depletion with various mutant enzymes. We find an unusual nepenthesin 1-type insert to be essential for parasite growth and PM V activity. Mutagenesis of the nepenthesin insert suggests that both its amino acid sequence and one of the two disulfide bonds that undergird its structure are required for the nepenthesin inserts role in PM V function. Molecular dynamics simulations paired with Markov state modelling suggest that the nepenthesin insert allosterically controls PM V catalysis through multiple mechanisms.

microbiology↗

Apolipoprotein E4 has extensive conformational heterogeneity in lipid free and bound forms

The {varepsilon}4-allele variant of Apolipoprotein E (ApoE4) is the strongest genetic risk factor for Alzheimers disease, though it only differs from its neutral counterpart ApoE3 by a single amino acid substitution. While ApoE4 influences the formation of plaques and neurofibrillary tangles, the structural determinants of pathogenicity remain undetermined due to limited structural information. We apply a combination of single-molecule spectroscopy and molecular dynamics simulations to construct an atomically-detailed model of monomeric ApoE4 and probe the effect of lipid association. Our data reveal that ApoE4 is far more disordered than previously thought and retains significant conformational heterogeneity after binding lipids. In particular, the behavior of the hinge region and C-terminal domain of ApoE4 differs substantially from that proposed in previous models and provides a crucial foundation for understanding how ApoE4 differs from non-pathogenic and protective variants of the protein.

biophysics↗

Intrinsically disordered pathogen effector alters the STAT1 dimer to prevent recruitment of co-transcriptional activators CBP/p300

Signal transducer and activator of transcription (STATs) proteins signal from cell-surface receptors to drive transcription of immune response genes. The parasite Toxoplasma gondii blocks STAT1-mediated gene expression by secreting the intrinsically disordered protein TgIST that traffics to the host nucleus, binds phosphorylated STAT1 dimers, and occupies nascent transcription sites that unexpectantly remain silenced. Here we define a core repeat region within internal repeats of TgIST that is necessary and sufficient to block STAT1-mediated gene expression. Cellular, biochemical, mutational, and structural studies demonstrate that the repeat region of TgIST adopts a helical conformation upon binding to STAT1 dimers. The binding interface is defined by a groove formed from two loops in the STAT1 SH2 domains that reorient during dimerization. TgIST binding to this newly exposed site at the STAT1 dimer interface altered its conformation and prevented recruitment of co-transcriptional activators, thus defining the mechanism of blocked transcription.

microbiology↗

Bexarotene derivatives modify responses in acute myeloid leukemia

The retinoids all-trans retinoic acid (ATRA) and bexarotene are active in acute myeloid leukemia (AML), but responses beyond acute promyelocytic leukemia (APL) have been more modest than APL responses. To determine whether chemical modification of bexarotene might augment retinoid responses in AML, we screened a series of 38 bexarotene derivatives for activity in a mouse MLL-AF9 leukemia cell line, which exhibits strong synergistic sensitivity to the combination of ATRA and bexarotene. We found that RXRA potency correlated with anti-leukemic activity and that only one compound (103-4) with dual RARA/RXRA activity was capable of ATRA-independent anti-leukemic activity. We evaluated bioisostere and cyclohexane modifications for potential resistance to P450 metabolism and found that bioisosteres reduced potency and that bezopyran, cyclopentane, and cyclohexene modifications only modestly reduced susceptibility to metabolism. Collectively, these studies provide a map of the structure-activity relationships of bexarotene with outcomes related to RXRA and RARA activity, corepressor binding, compound stability, and anti-leukemic potential.

cancer biology↗

Opening of a Cryptic Pocket in β-lactamase Increases Penicillinase Activity

Understanding the functional role of protein excited states has important implications in protein design and drug discovery. However, because these states are difficult to find and study, it is still unclear if excited states simply result from thermal fluctuations and generally detract from function or if these states can actually enhance protein function. To investigate this question, we consider excited states in {beta}-lactamases and particularly a subset of states containing a cryptic pocket which forms under the {Omega}-loop. Given the known importance of the {Omega}-loop and the presence of this pocket in at least two homologs, we hypothesized that these excited states enhance enzyme activity. Using thiol labeling assays to probe {Omega}-loop pocket dynamics and kinetic assays to probe activity, we find that while this pocket is not completely conserved across {beta}-lactamase homologs, those with the {Omega}-loop pocket have a higher activity against the substrate benzylpenicillin. We also find that this is true for TEM {beta}-lactamase variants with greater open {Omega}-loop pocket populations. We further investigate the open population using a combination of NMR CEST experiments and molecular dynamics simulations. To test our understanding of the {Omega}-loop pockets functional role, we designed mutations to enhance/suppress pocket opening and observed that benzylpenicillin activity is proportional to the probability of pocket opening in our designed variants. The work described here suggests that excited states containing cryptic pockets can be advantageous for function and may be favored by natural selection, increasing the potential utility of such cryptic pockets as drug targets.

biophysics↗

SARS-CoV-2 Nsp16 activation mechanism and a cryptic pocket with pan-coronavirus antiviral potential

Coronaviruses have caused multiple epidemics in the past two decades, in addition to the current COVID-19 pandemic that is severely damaging global health and the economy. Coronaviruses employ between twenty and thirty proteins to carry out their viral replication cycle including infection, immune evasion, and replication. Among these, nonstructural protein 16 (Nsp16), a 2-O-methyltransferase, plays an essential role in immune evasion. Nsp16 achieves this by mimicking its human homolog, CMTr1, which methylates mRNA to enhance translation efficiency and distinguish self from other. Unlike human CMTr1, Nsp16 requires a binding partner, Nsp10, to activate its enzymatic activity. The requirement of this binding partner presents two questions that we investigate in this manuscript. First, how does Nsp10 activate Nsp16? While experimentally-derived structures of the active Nsp16/Nsp10 complex exist, structures of inactive, monomeric Nsp16 have yet to be solved. Therefore, it is unclear how Nsp10 activates Nsp16. Using over one millisecond of molecular dynamics simulations of both Nsp16 and its complex with Nsp10, we investigate how the presence of Nsp10 shifts Nsp16s conformational ensemble in order to activate it. Second, guided by this activation mechanism and Markov state models (MSMs), we investigate if Nsp16 adopts inactive structures with cryptic pockets that, if targeted with a small molecule, could inhibit Nsp16 by stabilizing its inactive state. After identifying such a pocket in SARS-CoV-2 Nsp16, we show that this cryptic pocket also opens in SARS-CoV-1 and MERS, but not in human CMTr1. Therefore, it may be possible to develop pan-coronavirus antivirals that target this cryptic pocket. Statement of SignificanceCoronaviruses are a major threat to human health. These viruses employ molecular machines, called proteins, to infect host cells and replicate. Characterizing the structure and dynamics of these proteins could provide a basis for designing small molecule antivirals. In this work, we use computer simulations to understand the moving parts of an essential SARS-CoV-2 protein, understand how a binding partner turns it on and off, and identify a novel pocket that antivirals could target to shut this protein off. The pocket is also present in other coronaviruses but not in the related human protein, so it could be a valuable target for pan-coronavirus antivirals.

biophysics↗

VirB, a key transcriptional regulator of virulence plasmid genes in Shigella flexneri, forms DNA-binding site dependent foci in the bacterial cytoplasm

VirB is a key regulator of virulence genes located on the large virulence plasmid (pINV) of the bacterial pathogen Shigella flexneri. VirB is unusual in that it is not related to other transcriptional regulators, instead, it belongs to a protein family that primarily functions in plasmid and chromosome partitioning; exemplified by ParB. Despite this, VirB does not function to segregate DNA, but rather counters transcriptional silencing of virulence genes mediated by the nucleoid structuring protein, H-NS. Since ParB localizes subcellularly as discrete foci in the bacterial cytoplasm, we chose to investigate the subcellular localization of VirB to gain novel insight into how VirB functions as a transcriptional anti-silencer. To do this, a GFP-VirB fusion that retains the regulatory activity of VirB and yet, does not undergo significant protein degradation in S. flexneri, was used. Surprisingly, discrete fluorescent foci were observed in live wild-type S. flexneri cells and an isogenic virB mutant using fluorescence microscopy. In contrast, foci were rarely observed (<10%) in cells cured of pINV. Moreover, in the context of the fusion, amino acid substitutions in the DNA binding domain of VirB resulted in the fluorescent signal becoming entirely diffuse. Combined, these data demonstrate that the VirB:DNA interactions required for the transcriptional anti-silencing activity of VirB on pINV are a prerequisite for the subcellular localization of VirB in the bacterial cytoplasm. The significance of these findings, in light of the anti-silencing activity of VirB, is discussed. ImportanceThis study reveals the subcellular localization of VirB, a key transcriptional regulator of virulence genes found on the large virulence plasmid in Shigella. Fluorescent signals generated by an active GFP-VirB fusion form 2, 3, or 4 discrete foci in the bacterial cytoplasm, predominantly at the quarter cell position. These signals are completely dependent upon VirB interacting with its DNA binding site found either on the virulence plasmid or an engineered surrogate. Our findings: 1) provide novel insight into VirB:pINV interactions, 2) suggest that VirB may have utility as a DNA marker, and 3) raise questions about how and why this anti-silencing protein that controls virulence gene expression on pINV of Shigella spp. forms discrete foci/hubs within the bacterial cytoplasm.

microbiology↗

DiffNets: Self-supervised deep learning to identify the mechanistic basis for biochemical differences between protein variants

Understanding the structural determinants of a proteins biochemical properties, such as activity and stability, is a major challenge in biology and medicine. Comparing computer simulations of protein variants with different biochemical properties is an increasingly powerful means to drive progress. However, success often hinges on dimensionality reduction algorithms for simplifying the complex ensemble of structures each variant adopts. Unfortunately, common algorithms rely on potentially misleading assumptions about what structural features are important, such as emphasizing larger geometric changes over smaller ones. Here we present DiffNets, self-supervised autoencoders that avoid such assumptions, and automatically identify the relevant features, by requiring that the low-dimensional representations they learn are sufficient to predict the biochemical differences between protein variants. For example, DiffNets automatically identify subtle structural signatures that predict the relative stabilities of {beta}-lactamase variants and duty ratios of myosin isoforms. DiffNets should also be applicable to understanding other perturbations, such as ligand binding.

biophysics↗

Citizen Scientists Create an Exascale Computer to Combat COVID-19

SARS-CoV-2 has intricate mechanisms for initiating infection, immune evasion/suppression, and replication, which depend on the structure and dynamics of its constituent proteins. Many protein structures have been solved, but far less is known about their relevant conformational changes. To address this challenge, over a million citizen scientists banded together through the Folding@home distributed computing project to create the first exascale computer and simulate an unprecedented 0.1 seconds of the viral proteome. Our simulations capture dramatic opening of the apo Spike complex, far beyond that seen experimentally, which explains and successfully predicts the existence of cryptic epitopes. Different Spike homologues modulate the probabilities of open versus closed structures, balancing receptor binding and immune evasion. We also observe dramatic conformational changes across the proteome, which reveal over 50 cryptic pockets that expand targeting options for the design of antivirals. All data and models are freely available online, providing a quantitative structural atlas.

biophysics↗

The SARS-CoV-2 nucleocapsid protein is dynamic, disordered, and phase separates with RNA

The SARS-CoV-2 nucleocapsid (N) protein is an abundant RNA binding protein critical for viral genome packaging, yet the molecular details that underlie this process are poorly understood. Here we combine single-molecule spectroscopy with all-atom simulations to uncover the molecular details that contribute to N protein function. N protein contains three dynamic disordered regions that house putative transiently-helical binding motifs. The two folded domains interact minimally such that full-length N protein is a flexible and multivalent RNA binding protein. N protein also undergoes liquid-liquid phase separation when mixed with RNA, and polymer theory predicts that the same multivalent interactions that drive phase separation also engender RNA compaction. We offer a simple symmetry-breaking model that provides a plausible route through which single-genome condensation preferentially occurs over phase separation, suggesting that phase separation offers a convenient macroscopic readout of a key nanoscopic interaction.

biophysics↗

Computing and Optimizing Over All Fixed-Points of Discrete Systems on Large Networks

Equilibria, or fixed points, play an important role in dynamical systems across various domains, yet finding them can be computationally challenging. Here, we show how to efficiently compute all equilibrium points of discrete-valued, discrete-time systems on sparse networks. Using graph partitioning, we recursively decompose the original problem into a set of smaller, simpler problems that are easy to compute, and whose solutions combine to yield the full equilibrium set. This makes it possible to find the fixed points of systems on arbitrarily large networks meeting certain criteria. This approach can also be used without computing the full equilibrium set, which may grow very large in some cases. For example, one can use this method to check the existence and total number of equilibria, or to find equilibria that are optimal with respect to a given cost function. We demonstrate the potential capabilities of this approach with examples in two scientific domains: computing the number of fixed points in brain networks and finding the minimal energy conformations of lattice-based protein folding models.

neuroscience↗

Discovery of a cryptic allosteric site in Ebola's 'undruggable' VP35 protein using simulations and experiments

Protein-protein and protein-nucleic acid interactions are often considered difficult drug targets because the surfaces involved lack obvious druggable pockets. Cryptic pockets could present opportunities for targeting these interactions, but identifying and exploiting these pockets remains challenging. Here, we apply a general pipeline for identifying cryptic pockets to the interferon inhibitory domain (IID) of Ebola viral protein 35 (VP35). VP35 plays multiple essential roles in Ebolas replication cycle but lacks pockets that present obvious utility for drug design. Using adaptive sampling simulations and machine learning algorithms, we predict VP35 harbors a cryptic pocket that is allosterically coupled to a key dsRNA-binding interface. Thiol labeling experiments corroborate the predicted pocket and mutating the predicted allosteric network supports our model of allostery. Finally, covalent modifications that mimic drug binding allosterically disrupt dsRNA binding that is essential for immune evasion. Based on these successes, we expect our pipeline is equally applicable to other proteins.

biochemistry↗

Structural dynamics of isolated myosin motor domains encode differences in their mechanochemical cycles

Myosin motor domains perform an extraordinary diversity of biological functions despite sharing a common mechanochemical cycle. Motors are adapted to their function, in part, by tuning the thermodynamics and kinetics of steps in this cycle. However, it remains unclear how sequence encodes these differences, since biochemically distinct motors often have nearly indistinguishable crystal structures. We hypothesized that sequences produce distinct biochemical phenotypes by modulating the relative probabilities of an ensemble of conformations primed for different functional roles. To test this hypothesis, we modeled the distribution of conformations for twelve myosin motor domains by building Markov state models (MSMs) from an unprecedented two milliseconds of all-atom, explicit-solvent molecular dynamics simulations. Comparing motors reveals shifts in the balance between nucleotide-favorable and nucleotide-unfavorable P-loop conformations that predict experimentally-measured duty ratios and ADP release rates better than sequence or individual structures. This result demonstrates the power of an ensemble perspective for interrogating sequence-function relationships. Subject AreasBiochemistry and Chemical Biology, Structural Biology and Molecular Physics

biophysics↗

Spatial and temporal alterations in protein structure by EGF regulate cryptic cysteine oxidation

Stimulation of receptor tyrosine kinases (RTK) such as EGF locally increase reactive oxygen species (ROS) levels at the plasma membrane that oxidize cysteines in proteins to enhance downstream signaling. Spatial confinement of ROS is an important regulatory mechanism to redox signaling, but it remains unknown why stimulation of different receptor tyrosine kinases (RTKs) at the plasma membrane target distinct sets of downstream proteins. To uncover additional mechanisms specifying which cysteines are redox regulated by EGF stimulation, we performed time-resolved quantification of the oxidation of 4,200 cysteine sites subsequent to EGF stimulation in A431 cells. EGF induces three distinct spatiotemporal patterns of cysteine oxidation in functionally organized protein networks, consistent with the spatial confinement model. Unexpectedly, protein crystal structure analysis and molecular dynamic simulation indicate widespread redox regulation of cryptic cysteines that are only solvent exposed upon changes in protein conformation. Phosphorylation and increased flux of nucleotide substrates serve as two distinct modes by which EGF specifies which cryptic cysteines become solvent exposed and redox regulated. Since proteins structurally regulated by different RTKs or cellular perturbations are largely unique, solvent exposure and redox regulation of cryptic cysteines is an important mechanism contextually delineating redox signaling networks.\n\nSignificance StatementCellular redox processes are interconnected, but are not in equilibrium. Thus, understanding the redox biology of cells requires a systems-level, rather than reductionist, approach. Factors specifying which cysteines are redox regulated by a stimulus remain poorly characterized but are critical to understanding the fundamental properties of redox signaling networks. Here, we show that EGF stimulation induces oxidation of specific cysteines in 3 distinct spatiotemporal patterns. Redox regulated proteins include many proteins in the EGF pathway as well as many cysteines with known functional importance. Many redox regulated cysteines are cryptic and solvent exposed by changes in protein structure that were induced by EGF treatment. The novel finding that cryptic cysteines are redox regulated has important implications for how redox signaling networks are specified and regulated to minimize crosstalk. In addition, this time-resolved dataset of the redox kinetics of 4,200 cysteine sites is an important resource for others and is an important technological achievement towards systems-level understanding of cellular redox biology.

biochemistry↗

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↗

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↗

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↗

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↗