Determination and comparison of specific activity of the HIF-prolyl hydroxylases

AbstractHypoxia-inducible factor (HIF) is a transcriptional complex that is regulated by oxygen sensitive hydroxylation of its α subunits by the prolyl hydroxylases PHD1, 2 and 3. To better understand the role of these enzymes in directing cellular responses to hypoxia, we derived an assay to determine their specific activity in both native cell extracts and recombinant sources of enzyme. We show that all three are capable of high rates of catalysis, in the order PHD2=PHD3>PHD1, using substrate peptides derived from the C-terminal degradation domain of HIF-α subunits, and that each demonstrates similar and remarkable sensitivity to oxygen, commensurate with a common role in signaling hypoxia

Nudging towards COVID-19 and influenza vaccination uptake in medically at-risk children : EPIC study protocol of randomised controlled trials in Australian paediatric outpatient clinics

Introduction: Children with chronic medical diseases are at an unacceptable risk of hospitalisation and death from influenza and SARS-CoV-2 infections. Over the past two decades, behavioural scientists have learnt how to design non-coercive ‘nudge’ interventions to encourage positive health behaviours. Our study aims to evaluate the impact of multicomponent nudge interventions on the uptake of COVID-19 and influenza vaccines in medically at-risk children. Methods and analyses: Two separate randomised controlled trials (RCTs), each with 1038 children, will enrol a total of approximately 2076 children with chronic medical conditions who are attending tertiary hospitals in South Australia, Western Australia and Victoria. Participants will be randomly assigned (1:1) to the standard care or intervention group. The nudge intervention in each RCT will consist of three text message reminders with four behavioural nudges including (1) social norm messages, (2) different messengers through links to short educational videos from a paediatrician, medically at-risk child and parent and nurse, (3) a pledge to have their child or themselves vaccinated and (4) information salience through links to the current guidelines and vaccine safety information. The primary outcome is the proportion of medically at-risk children who receive at least one dose of vaccine within 3 months of randomisation. Logistic regression analysis will be performed to determine the effect of the intervention on the probability of vaccination uptake. Ethics and dissemination: The protocol and study documents have been reviewed and approved by the Women’s and Children’s Health Network Human Research Ethics Committee (HREC/22/WCHN/2022/00082). The results will be published via peer-reviewed journals and presented at scientific meetings and public forums. Trial registration number: NCT05613751

Report on the sixth blind test of organic crystal structure prediction methods.

The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and `best practices' for performing CSP calculations. All of the targets, apart from a single potentially disordered Z' = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms.The organisers and participants are very grateful to the crystallographers who supplied the candidate structures: Dr. Peter Horton (XXII), Dr. Brian Samas (XXIII), Prof. Bruce Foxman (XXIV), and Prof. Kraig Wheeler (XXV and XXVI). We are also grateful to Dr. Emma Sharp and colleagues at Johnson Matthey (Pharmorphix) for the polymorph screening of XXVI, as well as numerous colleagues at the CCDC for assistance in organising the blind test. Submission 2: We acknowledge Dr. Oliver Korb for numerous useful discussions. Submission 3: The Day group acknowledge the use of the IRIDIS High Performance Computing Facility, and associated support services at the University of Southampton, in the completion of this work. We acknowledge funding from the EPSRC (grants EP/J01110X/1 and EP/K018132/1) and the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC through grant agreements n. 307358 (ERC-stG- 2012-ANGLE) and n. 321156 (ERC-AG-PE5-ROBOT). Submission 4: I am grateful to Mikhail Kuzminskii for calculations of molecular structures on Gaussian 98 program in the Institute of Organic Chemistry RAS. The Russian Foundation for Basic Research is acknowledged for financial support (14-03-01091). Submission 5: Toine Schreurs provided computer facilities and assistance. I am grateful to Matthew Habgood at AWE company for providing a travel grant. Submission 6: We would like to acknowledge support of this work by GlaxoSmithKline, Merck, and Vertex. Submission 7: The research was financially supported by the VIDI Research Program 700.10.427, which is financed by The Netherlands Organisation for Scientific Research (NWO), and the European Research Council (ERC-2010-StG, grant agreement n. 259510-KISMOL). We acknowledge the support of the Foundation for Fundamental Research on Matter (FOM). Supercomputer facilities were provided by the National Computing Facilities Foundation (NCF). Submission 8: Computer resources were provided by the Center for High Performance Computing at the University of Utah and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1053575. MBF and GIP acknowledge the support from the University of Buenos Aires and the Argentinian Research Council. Submission 9: We thank Dr. Bouke van Eijck for his valuable advice on our predicted structure of XXV. We thank the promotion office for TUT programs on advanced simulation engineering (ADSIM), the leading program for training brain information architects (BRAIN), and the information and media center (IMC) at Toyohashi University of Technology for the use of the TUT supercomputer systems and application software. We also thank the ACCMS at Kyoto University for the use of their supercomputer. In addition, we wish to thank financial supports from Conflex Corp. and Ministry of Education, Culture, Sports, Science and Technology. Submission 12: We thank Leslie Leiserowitz from the Weizmann Institute of Science and Geoffrey Hutchinson from the University of Pittsburgh for helpful discussions. We thank Adam Scovel at the Argonne Leadership Computing Facility (ALCF) for technical support. Work at Tulane University was funded by the Louisiana Board of Regents Award # LEQSF(2014-17)-RD-A-10 “Toward Crystal Engineering from First Principles”, by the NSF award # EPS-1003897 “The Louisiana Alliance for Simulation-Guided Materials Applications (LA-SiGMA)”, and by the Tulane Committee on Research Summer Fellowship. Work at the Technical University of Munich was supported by the Solar Technologies Go Hybrid initiative of the State of Bavaria, Germany. Computer time was provided by the Argonne Leadership Computing Facility (ALCF), which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357. Submission 13: This work would not have been possible without funding from Khalifa University’s College of Engineering. I would like to acknowledge Prof. Robert Bennell and Prof. Bayan Sharif for supporting me in acquiring the resources needed to carry out this research. Dr. Louise Price is thanked for her guidance on the use of DMACRYS and NEIGHCRYS during the course of this research. She is also thanked for useful discussions and numerous e-mail exchanges concerning the blind test. Prof. Sarah Price is acknowledged for her support and guidance over many years and for providing access to DMACRYS and NEIGHCRYS. Submission 15: The work was supported by the United Kingdom’s Engineering and Physical Sciences Research Council (EPSRC) (EP/J003840/1, EP/J014958/1) and was made possible through access to computational resources and support from the High Performance Computing Cluster at Imperial College London. We are grateful to Professor Sarah L. Price for supplying the DMACRYS code for use within CrystalOptimizer, and to her and her research group for support with DMACRYS and feedback on CrystalPredictor and CrystalOptimizer. Submission 16: R. J. N. acknowledges financial support from the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. [EP/J017639/1]. R. J. N. and C. J. P. acknowledge use of the Archer facilities of the U.K.’s national high-performance computing service (for which access was obtained via the UKCP consortium [EP/K014560/1]). C. J. P. also acknowledges a Leadership Fellowship Grant [EP/K013688/1]. B. M. acknowledges Robinson College, Cambridge, and the Cambridge Philosophical Society for a Henslow Research Fellowship. Submission 17: The work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. The work at the University of Silesia was supported by the Polish National Science Centre Grant No. DEC-2012/05/B/ST4/00086. Submission 18: We would like to thank Constantinos Pantelides, Claire Adjiman and Isaac Sugden of Imperial College for their support of our use of CrystalPredictor and CrystalOptimizer in this and Submission 19. The CSP work of the group is supported by EPSRC, though grant ESPRC EP/K039229/1, and Eli Lilly. The PhD students support: RKH by a joint UCL Max-Planck Society Magdeburg Impact studentship, REW by a UCL Impact studentship; LI by the Cambridge Crystallographic Data Centre and the M3S Centre for Doctoral Training (EPSRC EP/G036675/1). Submission 19: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 20: The work at New York University was supported, in part, by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1-0387 (MET and LV) and, in part, by the Materials Research Science and Engineering Center (MRSEC) program of the National Science Foundation under Award Number DMR-1420073 (MET and ES). The work at the University of Delaware was supported by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. Submission 21: We thank the National Science Foundation (DMR-1231586), the Government of Russian Federation (Grant No. 14.A12.31.0003), the Foreign Talents Introduction and Academic Exchange Program (No. B08040) and the Russian Science Foundation, project no. 14-43-00052, base organization Photochemistry Center of the Russian Academy of Sciences. Calculations were performed on the Rurik supercomputer at Moscow Institute of Physics and Technology. Submission 22: The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC). Submission 24: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 25: J.H. and A.T. acknowledge the support from the Deutsche Forschungsgemeinschaft under the program DFG-SPP 1807. H-Y.K., R.A.D., and R.C. acknowledge support from the Department of Energy (DOE) under Grant Nos. DE-SC0008626. This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DEAC02-05CH11231. Additional computational resources were provided by the Terascale Infrastructure for Groundbreaking Research in Science and Engineering (TIGRESS) High Performance Computing Center and Visualization Laboratory at Princeton University.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1107/S2052520616007447

Mechanisms of Hybrid Oligomer Formation in the Pathogenesis of Combined Alzheimer's and Parkinson's Diseases

Background: Misfolding and pathological aggregation of neuronal proteins has been proposed to play a critical role in the pathogenesis of neurodegenerative disorders. Alzheimer’s disease (AD) and Parkinson’s disease (PD) are frequent neurodegenerative diseases of the aging population. While progressive accumulation of amyloid b protein (Ab) oligomers has been identified as one of the central toxic events in AD, accumulation of a-synuclein (a-syn) resulting in the formation of oligomers and protofibrils has been linked to PD and Lewy body Disease (LBD). We have recently shown that Ab promotes a-syn aggregation and toxic conversion in vivo, suggesting that abnormal interactions between misfolded proteins might contribute to disease pathogenesis. However the molecular characteristics and consequences of these interactions are not completely clear. Methodology/Principal Findings: In order to understand the molecular mechanisms involved in potential Ab/a-syn interactions, immunoblot, molecular modeling, and in vitro studies with a-syn and Ab were performed. We showed in vivo in the brains of patients with AD/PD and in transgenic mice, Ab and a-synuclein co-immunoprecipitate and form complexes. Molecular modeling and simulations showed that Ab binds a-syn monomers, homodimers, and trimers, forming hybrid ringlike pentamers. Interactions occurred between the N-terminus of Ab and the N-terminus and C-terminus of a-syn. Interacting a-syn and Ab dimers that dock on the membrane incorporated additional a-syn molecules, leading to th

Report on the sixth blind test of organic crystal-structure prediction methods

The sixth blind test of organic crystal-structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal, and a bulky flexible molecule. This blind test has seen substantial growth in the number of submissions, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and "best practices" for performing CSP calculations. All of the targets, apart from a single potentially disordered Z` = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms

A distal arginine in oxygen-sensing heme-PAS domains is essential to ligand binding, signal transduction, and structure.

To evaluate the contributions of the G(beta)-2 arginine to signal transduction in oxygen-sensing heme-PAS domains, we replaced this residue with alanine in Bradyrhizobium japonicum FixL and examined the results on heme-domain structure, ligand binding, and kinase regulation. In the isolated R220A BjFixL heme-PAS domain, the iron-histidine bond was increased in length by 0.31 A, the heme flattened even without a ligand, and the interaction of a presumed regulatory loop (the FG loop) with the helix of heme attachment was weakened. Binding of carbon monoxide was similar for ferrous BjFixL and R220A BjFixL. In contrast, the level of binding of oxygen was dramatically lower (K(d) approximately 1.5 mM) for R220A BjFixL, and this was manifested as 60- and 3-fold lower on- and off-rate constants, respectively. Binding of cyanide followed the same pattern as binding of oxygen. The catalytic activity was 3-4-fold higher in the "on-state" unliganded forms of R220A BjFixL than in the corresponding BjFixL species. Cyanide regulation of this activity was strongly impaired, but some inhibition was nevertheless preserved. Carbon monoxide and nitric oxide regulation, although weak in BjFixL, were abolished from R220A BjFixL. We conclude that the G(beta)-2 arginine assists in the binding of oxygen to BjFixL but does not accomplish this by stabilizing the oxy form. This arginine is not absolutely required for regulation, although it is important for shifting a pre-existing kinase equilibrium toward the inactive state on binding of regulatory ligands. These findings support a regulatory model in which the heme-PAS domain operates as an ensemble that couples to the kinase rather than a mechanism driven by a single central switch

Signal Transduction and Phosphoryl Transfer by a FixL Hybrid Kinase with Low Oxygen Affinity: Importance of the Vicinal PAS Domain and Receiver Aspartate

FixL is a prototype for heme-based sensors, multidomain proteins that typically couple a histidine protein kinase activity to a heme-binding domain for sensing of diatomic gases such as oxygen, carbon monoxide, and nitric oxide. Despite the relatively well-developed understanding of FixL, the importance of some of its domains has been unclear. To explore the impact of domain–domain interactions on oxygen sensing and signal transduction, we characterized and investigated <i>Rhizobium etli</i> hybrid sensor <i>Re</i>FixL. In <i>Re</i>FixL, the core heme-containing PAS domain and kinase region is preceded by an N-terminal PAS domain of unknown function and followed by a C-terminal receiver domain. The latter resembles a target substrate domain that usually occurs independently of the kinase and contains a phosphorylatable aspartate residue. We isolated the full-length <i>Re</i>FixL as a soluble holoprotein with a single heme <i>b</i> cofactor. Despite a low affinity for oxygen (<i>K</i>_d for O₂ of 738 μM), the kinase activity was completely switched off by O₂ at concentrations well below the <i>K</i>_d. A deletion of the first PAS domain strongly increased the oxygen affinity but essentially prohibited autophosphorylation, although the truncated protein was competent to accept phosphoryl groups in trans. These studies provide new insights into histidyl–aspartyl phosphoryl transfers in two-component systems and suggest that the control of ligand affinity and signal transduction by PAS domains can be direct or indirect

A Simplified Model of Local Structure in Aqueous Proline Amino Acid Revealed by First-Principles Molecular Dynamics Simulations

Aqueous proline solutions are deceptively simple as they can take on complex roles such as protein chaperones, cryoprotectants, and hydrotropic agents in biological processes. Here, a molecular level picture of proline/water mixtures is developed. Car-Parrinello ab initio molecular dynamics (CPAIMD) simulations of aqueous proline amino acid at the B-LYP level of theory, performed using IBM's Blue Gene/L supercomputer and massively parallel software, reveal hydrogen-bonding propensities that are at odds with the predictions of the CHARMM22 empirical force field but are in better agreement with results of recent neutron diffraction experiments. In general, the CPAIMD (B-LYP) simulations predict a simplified structural model of proline/water mixtures consisting of fewer distinct local motifs. Comparisons of simulation results to experiment are made by direct evaluation of the neutron static structure factor S(Q) from CPAIMD (B-LYP) trajectories as well as to the results of the empirical potential structure refinement reverse Monte Carlo procedure applied to the neutron data