Actions of Agonists, Fipronil and Ivermectin on the Predominant In Vivo Splice and Edit Variant (RDLbd, I/V) of the Drosophila GABA Receptor Expressed in Xenopus laevis Oocytes

Ionotropic GABA receptors are the targets for several classes of insecticides. One of the most widely-studied insect GABA receptors is RDL (resistance to dieldrin), originally isolated from Drosophila melanogaster. RDL undergoes alternative splicing and RNA editing, which influence the potency of GABA. Most work has focussed on minority isoforms. Here, we report the first characterisation of the predominant native splice variant and RNA edit, combining functional characterisation with molecular modelling of the agonist-binding region. The relative order of agonist potency is GABA> muscimol> TACA> β-alanine. The I/V edit does not alter the potency of GABA compared to RDLbd. Docking calculations suggest that these agonists bind and activate RDLbdI/V through a similar binding mode. TACA and β-alanine are predicted to bind with lower affinity than GABA, potentially explaining their lower potency, whereas the lower potency of muscimol and isoguvacine cannot be explained structurally from the docking calculations. The A301S (resistance to dieldrin) mutation reduced the potency of antagonists picrotoxin, fipronil and pyrafluprole but the I/V edit had no measurable effect. Ivermectin suppressed responses to GABA of RDLbdI/V, RDLbd and RDLbdI/VA301S. The dieldrin resistant variant also showed reduced sensitivity to Ivermectin. This study of a highly abundant insect GABA receptor isoform will help the design of new insecticides

Mutationmapper: a tool to aid the mapping of protein mutation data

There has been a rapid increase in the amount of mutational data due to, amongst other things, an increase in single nucleotide polymorphism (SNP) data and the use of site-directed mutagenesis as a tool to help dissect out functional properties of proteins. Many manually curated databases have been developed to index point mutations but they are not sustainable with the ever-increasing volume of scientific literature. There have been considerable efforts in the automatic extraction of mutation specific information from raw text involving use of various text-mining approaches. However, one of the key problems is to link these mutations with its associated protein and to present this data in such a way that researchers can immediately contextualize it within a structurally related family of proteins. To aid this process, we have developed an application called MutationMapper. Point mutations are extracted from abstracts and are validated against protein sequences in Uniprot as far as possible. Our methodology differs in a fundamental way from the usual text-mining approach. Rather than start with abstracts, we start with protein sequences, which facilitates greatly the process of validating a potential point mutation identified in an abstract. The results are displayed as mutations mapped on to the protein sequence or a multiple sequence alignment. The latter enables one to readily pick up mutations performed at equivalent positions in related proteins. We demonstrate the use of MutationMapper against several examples including a single sequence and multiple sequence alignments. The application is available as a web-service at http://mutationmapper.bioch.ox.ac.uk

Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes.

BackgroundGeneral translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood.ResultsHere, we show that these sequence features specify 42-81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25-60 nucleotide segments within mRNA 5' regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5' regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA.ConclusionsOur work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell

Statistical Analysis on the Performance of Molecular Mechanics Poisson-Boltzmann Surface Area versus Absolute Binding Free Energy Calculations: Bromodomains as a Case Study.

Binding free energy calculations that make use of alchemical pathways are becoming increasingly feasible thanks to advances in hardware and algorithms. Although relative binding free energy (RBFE) calculations are starting to find widespread use, absolute binding free energy (ABFE) calculations are still being explored mainly in academic settings due to the high computational requirements and still uncertain predictive value. However, in some drug design scenarios, RBFE calculations are not applicable and ABFE calculations could provide an alternative. Computationally cheaper end-point calculations in implicit solvent, such as molecular mechanics Poisson−Boltzmann surface area (MMPBSA) calculations, could too be used if one is primarily interested in a relative ranking of affinities. Here, we compare MMPBSA calculations to previously performed absolute alchemical free energy calculations in their ability to correlate with experimental binding free energies for three sets of bromodomain−inhibitor pairs. Different MMPBSA approaches have been considered, including a standard single-trajectory protocol, a protocol that includes a binding entropy estimate, and protocols that take into account the ligand hydration shell. Despite the improvements observed with the latter two MMPBSA approaches, ABFE calculations were found to be overall superior in obtaining correlation with experimental affinities for the test cases considered. A difference in weighted average Pearson (rp) and Spearman (rs) correlations of 0.25 and 0.31 was observed when using a standard single-trajectory MMPBSA setup (rp = 0.64 and rs = 0.66 for ABFE; rp = 0.39 and rs = 0.35 for MMPBSA). The best performing MMPBSA protocols returned weighted average Pearson and Spearman correlations that were about 0.1 inferior to ABFE calculations: rp = 0.55 and rs = 0.56 when including an entropy estimate, and rp = 0.53 and rs = 0.55 when including explicit water molecules. Overall, the study suggests that ABFE calculations are indeed the more accurate approach, yet there is also value in MMPBSA calculations considering the lower compute requirements, and if agreement to experimental affinities in absolute terms is not of interest. Moreover, for the specific protein−ligand systems considered in this study, we find that including an explicit ligand hydration shell or a binding entropy estimate in the MMPBSA calculations resulted in significant performance improvements at a negligible computational cost

Accurate calculation of the absolute free energy of binding for drug molecules

Accurate prediction of binding affinities has been a central goal of computational chemistry for decades, yet remains elusive. Despite good progress, the required accuracy for use in a drug-discovery context has not been consistently achieved for drug-like molecules. Here, we perform absolute free energy calculations based on a thermodynamic cycle for a set of diverse inhibitors binding to bromodomain-containing protein 4 (BRD4) and demonstrate that a mean absolute error of 0.6 kcal mol−1 can be achieved. We also show a similar level of accuracy (1.0 kcal mol−1) can be achieved in pseudo prospective approach. Bromodomains are epigenetic mark readers that recognize acetylation motifs and regulate gene transcription, and are currently being investigated as therapeutic targets for cancer and inflammation. The unprecedented accuracy offers the exciting prospect that the binding free energy of drug-like compounds can be predicted for pharmacologically relevant targets

Large-scale analysis of water stability in bromodomain binding pockets with grand canonical Monte Carlo

Conserved water molecules are of interest in drug design, as displacement of such waters can lead to higher affinity ligands, and in some cases, contribute towards selectivity. Bromodomains, small protein domains involved in the epigenetic regulation of gene transcription, display a network of four conserved water molecules in their binding pockets and have recently been the focus of intense medicinal chemistry efforts. Understanding why certain bromodomains have displaceable water molecules and others do not is extremely challenging, and it remains unclear which water molecules in a given bromodomain can be targeted for displacement. Here we estimate the stability of the conserved water molecules in 35 bromodomains via binding free energy calculations using all-atom grand canonical Monte Carlo simulations. Encouraging quantitative agreement to the available experimental evidence is found. We thus discuss the expected ease of water displacement in different bromodomains and the implications for ligand selectivity

Muscle acetylcholine receptor conversion into chloride conductance at positive potentials by a single mutation

Charge selectivity forms the basis of cellular excitation or inhibition by Cys-loop ligand-gated ion channels (LGICs), and is essential for physiological receptor function. There are no reports of naturally occurring mutations in LGICs associated with the conversion of charge selectivity. Here, we report on a CHRNA1 mutation (α1Leu251Arg) in a patient with congenital myasthenic syndrome associated with transformation of the muscle acetylcholine receptor (AChR) into an inhibitory channel. Performing patch-clamp experiments, the AChR was found to be converted into chloride conductance at positive potentials, whereas whole-cell currents at negative potentials, although markedly reduced, were still carried by sodium. Umbrella sampling molecular dynamics simulations revealed constriction of the channel pore radius to 2.4 Å as a result of the mutation, which required partial desolvation of the ions in order to permeate the pore. Ion desolvation was associated with an energetic penalty that was compensated for by the favorable electrostatic interaction of the positively charged arginines with chloride. These findings reveal a mechanism for the transformation of the muscle AChR into an inhibitory channel in a clinical context

Dynamo constraints on the long-term evolution of Earth's magnetic field strength

Elucidating the processes in the liquid core that have produced observed palaeointensity changes over the last 3.5 Gyr is crucial for understanding the dynamics and long-term evolution of Earth’s deep interior. We combine numerical geodynamo simulations with theoretical scaling laws to investigate the variation of Earth’s magnetic field strength over geological time. Our approach follows the study of Aubert et al., adapted to include recent advances in numerical simulations, mineral physics and palaeomagnetism. We first compare the field strength within the dynamo region and on the core–mantle boundary (CMB) between a suite of 314 dynamo simulations and two power-based theoretical scaling laws. The scaling laws are both based on a Quasi-Geostropic (QG) force balance at leading order and a Magnetic, Archimedian, and Coriolis (MAC) balance at first order and differ in treating the characteristic length scale of the convection as fixed (QG-MAC-fixed) or determined as part of the solution (QG-MAC-free). When the data set is filtered to retain only simulations with magnetic to kinetic energy ratios greater than at least two we find that the internal field together with the root-mean-square and dipole CMB fields exhibit power-law behaviour that is compatible with both scalings within uncertainties arising from different heating modes and boundary conditions. However, while the extrapolated intensity based on the QG-MAC-free scaling matches Earth’s modern CMB field, the QG-MAC-fixed prediction shoots too high and also significantly overestimates palaeointensities over the last 3.5 Gyr. We combine the QG-MAC-free scaling with outputs from 275 realizations of core–mantle thermal evolution to construct synthetic true dipole moment (TDM) curves spanning the last 3.5 Gyr. Best-fitting TDMs reproduce binned PINT data during the Bruhnes and before inner core nucleation (ICN) within observational uncertainties, but PINT does not contain the predicted strong increase and subsequent high TDMs during the early stages of inner core growth. The best-fitting models are obtained for a present-day CMB heat flow of 11–16 TW, increasing to 17–22 TW at 4 Ga, and predict a minimum TDM at ICN

Utility of the FebriDx point-of-care assay in supporting a triage algorithm for medical admissions with possible COVID-19: an observational cohort study

Objective: To evaluate a triage algorithm used to identify and isolate patients with suspected COVID-19 among medical patients needing admission to hospital using simple clinical criteria and the FebriDx assay. Design:: Retrospective observational cohort. Setting Large acute National Health Service hospital in London, UK. Participants: All medical admissions from the emergency department between 10 August 2020 and 4 November 2020 with a valid SARS-CoV-2 RT-PCR result. Interventions: Medical admissions were triaged as likely, possible or unlikely COVID-19 based on clinical criteria. Patients triaged as possible COVID-19 underwent FebriDx lateral flow assay on capillary blood, and those positive for myxovirus resistance protein A (a host response protein) were managed as likely COVID-19. Primary outcome measures: Diagnostic accuracy (sensitivity, specificity and predictive values) of the algorithm and the FebriDx assay using SARS-CoV-2 RT-PCR from nasopharyngeal swabs as the reference standard. Results: 4.0% (136) of 3443 medical admissions had RT-PCR confirmed COVID-19. Prevalence of COVID-19 was 46% (80/175) in those triaged as likely, 4.1% (50/1225) in possible and 0.3% (6/2033) in unlikely COVID-19. Using a SARS-CoV-2 RT-PCR reference standard, clinical triage had sensitivity of 96% (95% CI 91% to 98%) and specificity of 61.5% (95% CI 59.8% to 63.1%), while the triage algorithm including FebriDx had sensitivity of 93% (95% CI 87% to 96%) and specificity of 86.4% (95% CI 85.2% to 87.5%). While 2033 patients were deemed not to require isolation using clinical criteria alone, the addition of FebriDx to clinical triage allowed a further 826 patients to be released from isolation, reducing the need for isolation rooms by 9.5 per day, 95% CI 8.9 to 10.2. Ten patients missed by the algorithm had mild or asymptomatic COVID-19. Conclusions: A triage algorithm including the FebriDx assay had good sensitivity and was useful to ‘rule-out’ COVID-19 among medical admissions to hospital