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The ability to sense and respond to changes in cellular oxygen levels is critical for aerobic organisms and requires a molecular oxygen sensor. The prototypical sensor is the oxygen-dependent enzyme PHD: hypoxia inhibits its ability to hydroxylate the transcription factor HIF, causing HIF to accumulate and trigger the classic HIF-dependent hypoxia response. A small handful of other oxygen sensors are known, all of which are oxygen-dependent enzymes. However, hundreds of oxygen-dependent enzymes exist among aerobic organisms, raising the possibility that additional sensors remain to be discovered. This review summarizes known and potential hypoxia sensors among human O 2 -dependent enzymes and highlights their possible roles in hypoxia-related adaptation and diseases.

Pathway docking ( in silico docking of metabolites to several enzymes and binding proteins in a metabolic pathway) enables the discovery of a catabolic pathway for the osmolyte trans -4-hydroxy- l -proline betaine. Structural key to predicting enzyme function Overprediction and database annotation errors in genome-sequencing projects have caused much confusion because of the difficulty of assigning valid functions to the proteins identified. These authors use structure-guided approaches for predicting the substrate specificities of several enzymes encoded by a bacterial gene cluster to correctly predict the in vitro activity of an enzyme of unknown function and identify the catabolic pathway in which it participates in cells. The substrate-liganded pose predicted by virtual library screening was confirmed experimentally, enzyme activities in the predicted pathway were confirmed by in vitro assays and genetic analyses, the intermediates were identified by metabolomics, and repression of the genes encoding the pathway by high salt concentrations was established by transcriptomics. This study establishes the utility of structure-guided functional predictions for the discovery of new metabolic pathways. Assigning valid functions to proteins identified in genome projects is challenging: overprediction and database annotation errors are the principal concerns 1 . We and others 2 are developing computation-guided strategies for functional discovery with ‘metabolite docking’ to experimentally derived 3 or homology-based 4 three-dimensional structures. Bacterial metabolic pathways often are encoded by ‘genome neighbourhoods’ (gene clusters and/or operons), which can provide important clues for functional assignment. We recently demonstrated the synergy of docking and pathway context by ‘predicting’ the intermediates in the glycolytic pathway in Escherichia coli 5 . Metabolite docking to multiple binding proteins and enzymes in the same pathway increases the reliability of in silico predictions of substrate specificities because the pathway intermediates are structurally similar. Here we report that structure-guided approaches for predicting the substrate specificities of several enzymes encoded by a bacterial gene cluster allowed the correct prediction of the in vitro activity of a structurally characterized enzyme of unknown function (PDB 2PMQ), 2-epimerization of trans -4-hydroxy- l -proline betaine (tHyp-B) and cis -4-hydroxy- d -proline betaine (cHyp-B), and also the correct identification of the catabolic pathway in which Hyp-B 2-epimerase participates. The substrate-liganded pose predicted by virtual library screening (docking) was confirmed experimentally. The enzymatic activities in the predicted pathway were confirmed by in vitro assays and genetic analyses; the intermediates were identified by metabolomics; and repression of the genes encoding the pathway by high salt concentrations was established by transcriptomics, confirming the osmolyte role of tHyp-B. This study establishes the utility of structure-guided functional predictions to enable the discovery of new metabolic pathways.

Preventing the biogenesis of disease-relevant proteins is an attractive therapeutic strategy, but attempts to target essential protein biogenesis factors have been hampered by excessive toxicity. Here we describe KZR-8445, a cyclic depsipeptide that targets the Sec61 translocon and selectively disrupts secretory and membrane protein biogenesis in a signal peptide-dependent manner. KZR-8445 potently inhibits the secretion of pro-inflammatory cytokines in primary immune cells and is highly efficacious in a mouse model of rheumatoid arthritis. A cryogenic electron microscopy structure reveals that KZR-8445 occupies the fully opened Se61 lateral gate and blocks access to the lumenal plug domain. KZR-8445 binding stabilizes the lateral gate helices in a manner that traps select signal peptides in the Sec61 channel and prevents their movement into the lipid bilayer. Our results establish a framework for the structure-guided discovery of novel therapeutics that selectively modulate Sec61-mediated protein biogenesis. A selective inhibitor of Sec61 blocks protein entry into the secretory pathway and has therapeutic efficacy in rheumatoid arthritis. A cryo-EM structure of the inhibited Sec61 provides a model for client-selective protein translocation inhibition.

One of the many factors involved in determining the distribution and metabolism of a compound is the strength of its binding to human serum albumin. While experimental and QSAR approaches for determining binding to albumin exist, various factors limit their ability to provide accurate binding affinity for novel compounds. Thus, to complement the existing tools, we have developed a structure-based model of serum albumin binding. Our approach for predicting binding incorporated the inherent flexibility and promiscuity known to exist for albumin. We found that a weighted combination of the predicted logP and docking score most accurately distinguished between binders and nonbinders. This model was successfully used to predict serum albumin binding in a large test set of therapeutics that had experimental binding data.

Sodium-dependent glucose transporters (SGLTs) exploit sodium gradients to transport sugars across the plasma membrane. Due to their role in renal sugar reabsorption, SGLTs are targets for the treatment of type 2 diabetes. Current therapeutics are phlorizin derivatives that contain a sugar moiety bound to an aromatic aglycon tail. Here, we develop structural models of human SGLT1/2 in complex with inhibitors by combining computational and functional studies. Inhibitors bind with the sugar moiety in the sugar pocket and the aglycon tail in the extracellular vestibule. The binding poses corroborate mutagenesis studies and suggest a partial closure of the outer gate upon binding. The models also reveal a putative Na + binding site in hSGLT1 whose disruption reduces the transport stoichiometry to the value observed in hSGLT2 and increases inhibition by aglycon tails. Our work demonstrates that subtype selectivity arises from Na + -regulated outer gate closure and a variable region in extracellular loop EL5. Sodium-dependent glucose transporters (SGLTs) transport sugars across the plasma membrane and play important roles in renal sugar reabsorption. Here authors develop structural models of human SGLT1/2 (hSGLT1/2) in complex with inhibitors which helps to understand inhibitor subtype selectivity.

A single trimethylated species is obtained in an on-resin N-methylation reaction of a cyclic hexapeptide. This regioselectivity is driven by conformation and the presence of intramolecular hydrogen bonds, and is correlated with membrane permeability of the peptides. Backbone N-methylation is common among peptide natural products and has a substantial impact on both the physical properties and the conformational states of cyclic peptides. However, the specific impact of N-methylation on passive membrane diffusion in cyclic peptides has not been investigated systematically. Here we report a method for the selective, on-resin N-methylation of cyclic peptides to generate compounds with drug-like membrane permeability and oral bioavailability. The selectivity and degree of N-methylation of the cyclic peptide was dependent on backbone stereochemistry, suggesting that conformation dictates the regiochemistry of the N-methylation reaction. The permeabilities of the N -methyl variants were corroborated by computational studies on a 1,024-member virtual library of N -methyl cyclic peptides. One of the most permeable compounds, a cyclic hexapeptide (molecular mass = 755 Da) with three N -methyl groups, showed an oral bioavailability of 28% in rat.

Background Autosomal dominant mutations in α-synuclein, TDP-43 and tau are thought to predispose to neurodegeneration by enhancing protein aggregation. While a subset of α-synuclein, TDP-43 and tau mutations has been shown to increase the structural propensity of these proteins toward self-association, rates of aggregation are also highly dependent on protein steady state concentrations, which are in large part regulated by their rates of lysosomal degradation. Previous studies have shown that lysosomal proteases operate precisely and not indiscriminately, cleaving their substrates at very specific linear amino acid sequences. With this knowledge, we hypothesized that certain coding mutations in α-synuclein, TDP-43 and tau may lead to increased protein steady state concentrations and eventual aggregation by an alternative mechanism, that is, through disrupting lysosomal protease cleavage recognition motifs and subsequently conferring protease resistance to these proteins. Results To test this possibility, we first generated comprehensive proteolysis maps containing all of the potential lysosomal protease cleavage sites for α-synuclein, TDP-43 and tau. In silico analyses of these maps indicated that certain mutations would diminish cathepsin cleavage, a prediction we confirmed utilizing in vitro protease assays. We then validated these findings in cell models and induced neurons, demonstrating that mutant forms of α-synuclein, TDP-43 and tau are degraded less efficiently than wild type despite being imported into lysosomes at similar rates. Conclusions Together, this study provides evidence that pathogenic mutations in the N-terminal domain of α-synuclein (G51D, A53T), low complexity domain of TDP-43 (A315T, Q331K, M337V) and R1 and R2 domains of tau (K257T, N279K, S305N) directly impair their own lysosomal degradation, altering protein homeostasis and increasing cellular protein concentrations by extending the degradation half-lives of these proteins. These results also point to novel, shared, alternative mechanism by which different forms of neurodegeneration, including synucleinopathies, TDP-43 proteinopathies and tauopathies, may arise. Importantly, they also provide a roadmap for how the upregulation of particular lysosomal proteases could be targeted as potential therapeutics for human neurodegenerative disease.

The progressive failure of protein homeostasis is a hallmark of aging and a common feature in neurodegenerative disease. As the enzymes executing the final stages of autophagy, lysosomal proteases are key contributors to the maintenance of protein homeostasis with age. We previously reported that expression of granulin peptides, the cleavage products of the neurodegenerative disease protein progranulin, enhance the accumulation and toxicity of TAR DNA binding protein 43 (TDP-43) in Caenorhabditis elegans (C. elegans). In this study we show that C. elegans granulins are produced in an age- and stress-dependent manner. Granulins localize to the endolysosomal compartment where they impair lysosomal protease expression and activity. Consequently, protein homeostasis is disrupted, promoting the nuclear translocation of the lysosomal transcription factor HLH-30/TFEB, and prompting cells to activate a compensatory transcriptional program. The three C. elegans granulin peptides exhibited distinct but overlapping functional effects in our assays, which may be due to amino acid composition that results in distinct electrostatic and hydrophobicity profiles. Our results support a model in which granulin production modulates a critical transition between the normal, physiological regulation of protease activity and the impairment of lysosomal function that can occur with age and disease.

There is significant interest in identifying and characterizing allosteric sites in enzymes such as protein kinases both for understanding allosteric mechanisms as well as for drug discovery. Here, we apply a site-directed technology, disulfide trapping, to interrogate structurally and functionally how an allosteric site on the Ser/Thr kinase, 3-phosphoinositide-dependent kinase 1 (PDK1)--the PDK1-interacting-fragment (PIF) pocket--is engaged by an activating peptide motif on downstream substrate kinases (PIFtides) and by small molecule fragments. By monitoring pairwise disulfide conjugation between PIFtide and PDK1 cysteine mutants, we defined the PIFtide binding orientation in the PIF pocket of PDK1 and assessed subtle relationships between PIFtide positioning and kinase activation. We also discovered a variety of small molecule fragment disulfides (< 300 Da) that could either activate or inhibit PDK1 by conjugation to the PIF pocket, thus displaying greater functional diversity than is displayed by PIFtides conjugated to the same sites. Biochemical data and three crystal structures provided insight into the mechanism of action of the best fragment activators and inhibitors. These studies show that disulfide trapping is useful for characterizing allosteric sites on kinases and that a single allosteric site on a protein kinase can be exploited for both activation and inhibition by small molecules.

P-glycoprotein (P-gp) is an ATP-dependent transport protein that is selectively expressed at entry points of xenobiotics where, acting as an efflux pump, it prevents their entering sensitive organs. The protein also plays a key role in the absorption and blood-brain barrier penetration of many drugs, while its overexpression in cancer cells has been linked to multidrug resistance in tumors. The recent publication of the mouse P-gp crystal structure revealed a large and hydrophobic binding cavity with no clearly defined sub-sites that supports an \"induced-fit\" ligand binding model. We employed flexible receptor docking to develop a new prediction algorithm for P-gp binding specificity. We tested the ability of this method to differentiate between binders and nonbinders of P-gp using consistently measured experimental data from P-gp efflux and calcein-inhibition assays. We also subjected the model to a blind test on a series of peptidic cysteine protease inhibitors, confirming the ability to predict compounds more likely to be P-gp substrates. Finally, we used the method to predict cellular metabolites that may be P-gp substrates. Overall, our results suggest that many P-gp substrates bind deeper in the cavity than the cyclic peptide in the crystal structure and that specificity in P-gp is better understood in terms of physicochemical properties of the ligands (and the binding site), rather than being defined by specific sub-sites.