Radiation damage remains one of the major impediments to accurate structure solution in macromolecular crystallography. The artefacts of radiation damage can manifest as structural changes that result in incorrect biological interpretations being drawn from a model, they can reduce the resolution to which data can be collected and they can even prevent structure solution entirely. In this article, we discuss how to identify and mitigate against the effects of radiation damage at each stage in the macromolecular crystal structure-solution pipeline.

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.

Differential sensing attempts to mimic the mammalian senses of smell and taste to identify analytes and complex mixtures. In place of hundreds of complex, membrane-bound G-protein coupled receptors, differential sensors employ arrays of small molecules. Here we show that arrays of computationally designed de novo peptides provide alternative synthetic receptors for differential sensing. We use self-assembling α-helical barrels (αHBs) with central channels that can be altered predictably to vary their sizes, shapes and chemistries. The channels accommodate environment-sensitive dyes that fluoresce upon binding. Challenging arrays of dye-loaded barrels with analytes causes differential fluorophore displacement. The resulting fluorimetric fingerprints are used to train machine-learning models that relate the patterns to the analytes. We show that this system discriminates between a range of biomolecules, drink, and diagnostically relevant biological samples. As αHBs are robust and chemically diverse, the system has potential to sense many analytes in various settings.

Background Saliva is easily obtainable non-invasively and potentially suitable for detecting both current and previous SARS-CoV-2 infection, but there is limited evidence on the utility of salivary antibody testing for community surveillance. Methods We established 6 ELISAs detecting IgA and IgG antibodies to whole SARS-CoV-2 spike protein, to its receptor binding domain region and to nucleocapsid protein in saliva. We evaluated diagnostic performance, and using paired saliva and serum samples, correlated mucosal and systemic antibody responses. The best-performing assays were field-tested in 20 household outbreaks. Results We demonstrate in test accuracy ( N = 320), spike IgG (ROC AUC: 95.0%, 92.8–97.3%) and spike IgA (ROC AUC: 89.9%, 86.5–93.2%) assays to discriminate best between pre-pandemic and post COVID-19 saliva samples. Specificity was 100% in younger age groups (0–19 years) for spike IgA and IgG. However, sensitivity was low for the best-performing assay (spike IgG: 50.6%, 39.8–61.4%). Using machine learning, diagnostic performance was improved when a combination of tests was used. As expected, salivary IgA was poorly correlated with serum, indicating an oral mucosal response whereas salivary IgG responses were predictive of those in serum. When deployed to household outbreaks, antibody responses were heterogeneous but remained a reliable indicator of recent infection. Intriguingly, unvaccinated children without confirmed infection showed evidence of exposure almost exclusively through specific IgA responses. Conclusions Through robust standardisation, evaluation and field-testing, this work provides a platform for further studies investigating SARS-CoV-2 transmission and mucosal immunity with the potential for expanding salivo-surveillance to other respiratory infections in hard-to-reach settings.

Low-volume antibody assays can be used to track SARS-CoV-2 infection rates in settings where active testing for virus is limited and remote sampling is optimal. We developed 12 ELISAs detecting total or antibody isotypes to SARS-CoV-2 nucleocapsid, spike protein or its receptor binding domain (RBD), 3 anti-RBD isotype specific luciferase immunoprecipitation system (LIPS) assays and a novel Spike-RBD bridging LIPS total-antibody assay. We utilized pre-pandemic (n=984) and confirmed/suspected recent COVID-19 sera taken pre-vaccination rollout in 2020 (n=269). Assays measuring total antibody discriminated best between pre-pandemic and COVID-19 sera and were selected for diagnostic evaluation. In the blind evaluation, two of these assays (Spike Pan ELISA and Spike-RBD Bridging LIPS assay) demonstrated >97% specificity and >92% sensitivity for samples from COVID-19 patients taken >21 days post symptom onset or PCR test. These assays offered better sensitivity for the detection of COVID-19 cases than a commercial assay which requires 100-fold larger serum volumes. This study demonstrates that low-volume in-house antibody assays can provide good diagnostic performance, and highlights the importance of using well-characterized samples and controls for all stages of assay development and evaluation. These cost-effective assays may be particularly useful for seroprevalence studies in low and middle-income countries.

Radiation damage remains one of the major bottlenecks to accurate structure solution in protein crystallography. It can induce structural and chemical changes in protein crystals, and is hence an important consideration when assessing the quality and biological veracity of crystal structures in repositories like the Protein Data Bank (PDB). However, detection of radiation damage artefacts has traditionally proved very challenging. To address this, here we introduce the B net metric. B net summarises in a single value the extent of damage suffered by a crystal structure by comparing the B -factor values of damage-prone and non-damage-prone atoms in a similar local environment. After validating that B net successfully detects damage in 23 different crystal structures previously characterised as damaged, we calculate B net values for 93,978 PDB crystal structures. Our metric highlights a range of damage features, many of which would remain unidentified by the other summary statistics typically calculated for PDB structures.

Saliva is easily obtainable non-invasively and potentially suitable for detecting both current and previous SARS-CoV-2 infection. We established 6 standardised enzyme linked immunosorbent assays (ELISA) capable of detecting IgA and IgG antibodies to whole SARS-CoV-2 spike protein, to its receptor binding domain region and to nucleocapsid protein in saliva. In test accuracy (n=320), we found that spike IgG performed best (ROC AUC: 95.0%, 92.8-97.3%), followed by spike IgA (ROC AUC: 89.9%, 86.5-93.2%) for discriminating between pre-pandemic and post COVID-19 saliva samples. Using machine learning, diagnostic performance was improved when a combination of tests was used. As expected, salivary IgA was poorly correlated with serum, indicating an oral mucosal response whereas salivary IgG responses were predictive of those in serum. When deployed to 20 household outbreaks undergoing Delta and Omicron infection, antibody responses were heterogeneous but remained a reliable indicator of recent infection. Intriguingly, unvaccinated children showed evidence of exposure almost exclusively through specific IgA responses in the absence of evidence of viral infection. We have provided robust standardisation, evaluation, and field-testing of salivary antibody assays as tools for monitoring SARS-CoV-2 immune responses. Future work should focus on investigating salivary antibody responses following infection and vaccination to understand patterns of SARS-CoV-2 transmission and inform ongoing vaccination strategies.

De novo protein design is advancing rapidly. However, most designs are for single states. Here we report a de novo designed peptide that forms multiple α-helical-bundle states that are accessible and interconvertible under the same conditions. Usually in such designs amphipathic α helices associate to form compact structures with consolidated hydrophobic cores. However, recent rational and computational designs have delivered open α-helical barrels with functionalisable cavities. By placing glycine judiciously in the helical interfaces of an α-helical barrel, we obtain both open and compact states in a single protein crystal. Molecular dynamics simulations indicate a free-energy landscape with multiple and interconverting states. Together, these findings suggest a frustrated system in which steric interactions that maintain the open barrel and the hydrophobic effect that drives complete collapse are traded-off. Indeed, addition of a hydrophobic co-solvent that can bind within the barrel affects the switch between the states both in silico and experimentally.

ABSTRACTThe rational design of linear peptides that assemble controllably and predictably in water is challenging. Sequences must encode unique target structures and avoid alternative states. However, the stabilizing and discriminating non-covalent forces available are weak in water. Nonetheless, for α-helical coiled-coil assemblies considerable progress has been made in rationalde novodesign. In these, sequence repeats of nominally hydrophobic (h) and polar (p) residues,hpphppp, direct the assembly of amphipathic helices into dimeric to tetrameric bundles. Expanding this pattern tohpphhphcan produce larger α-helical barrels. Here, we show that pentamers to nonamers are achieved simply by varying the residue at one of thesehsites. In L/I-K-E-I-A-x-Z repeats, decreasing the size of Z from threonine to serine to alanine to glycine gives progressively larger oligomers. X-ray crystal structures of the resulting α-helical barrels rationalize this: side chains at Z point directly into the helical interfaces, and smaller residues allow closer helix contacts and larger assemblies.

During macromolecular crystallography (MX) data collection one or more crystals are exposed to a high flux of ionising radiation, which even at cryo-temperatures can damage the crystal(s), causing structural and chemical changes.If sufficiently severe, this damage can prevent solution of the crystal structure.However, even when structure solution remains possible, specific damage artefacts can confuse the biological conclusions drawn from a structure: hence their identification is important.Traditionally however the detection of specific radiation damage artefacts within crystal structures has proven difficult.To address this problem, previously the Garman group developed the BDamage metric [1] , calculated by the CCP4 [2] program RABDAM [3] .BDamage is a per-atom metric that highlights potential sites of specific radiation damage as atoms with high B-factor values as compared to other atoms in a similar local environment in the parent crystalline structure.Whilst this metric is useful at identifying damage artefacts in individual structures, unfortunately BDamage values can not be compared between different structures.To address this limitation, here we present a derivative of the BDamage metric, Bnet, a per-structure metric that can be used to compare the relative damage suffered by different protein crystal structures.After validating that Bnet is an appropriate metric on a dataset of structures known to contain specific damage artefacts, we use Bnet to analyse the specific radiation damage present in a dataset of 94,145 protein crystal structures in the Protein Data Bank (PDB).Notably, many of the structures identified as damaged by Bnet, and which on closer inspection contain obvious damage artefacts, have reasonable or excellent values for the metrics typically reported for PDB structures.

Radiation damage remains one of the major limitations to accurate structure determination in protein crystallography (PX). Despite the use of cryo-cooling techniques, it is highly probable that a number of the structures deposited in the Protein Data Bank (PDB) have suffered substantial radiation damage as a result of the high flux densities of third generation synchrotron X-ray sources. Whereas the effects of global damage upon diffraction pattern reflection intensities are readily detectable, traditionally the (earlier onset) site-specific structural changes induced by radiation damage have proven difficult to identify within individual PX structures. More recently, however, development of the B Damage metric has helped to address this problem. B Damage is a quantitative, per-atom metric identifies potential sites of specific damage by comparing the atomic B -factor values of atoms that occupy a similar local packing density environment in the structure. Building upon this past work, this article presents a program, RABDAM , to calculate the B Damage metric for all selected atoms within any standard-format PDB or mmCIF file. RABDAM provides several useful outputs to assess the extent of damage suffered by an input PX structure. This free and open-source software will allow assessment and improvement of the quality of PX structures both previously and newly deposited in the PDB.

In human aortic smooth muscle cells, prostaglandin E2 (PGE2) stimulates adenylyl cyclase (AC) and attenuates the increase in intracellular free Ca2+ concentration evoked by activation of histamine H1 receptors. The mechanisms are not resolved. We show that cAMP mediates inhibition of histamine-evoked Ca2+ signals by PGE2 Exchange proteins activated by cAMP were not required, but the effects were attenuated by inhibition of cAMP-dependent protein kinase (PKA). PGE2 had no effect on the Ca2+ signals evoked by protease-activated receptors, heterologously expressed muscarinic M3 receptors, or by direct activation of inositol 1,4,5-trisphosphate (IP3) receptors by photolysis of caged IP3 The rate of Ca2+ removal from the cytosol was unaffected by PGE2, but PGE2 attenuated histamine-evoked IP3 accumulation. Substantial inhibition of AC had no effect on the concentration-dependent inhibition of Ca2+ signals by PGE2 or butaprost (to activate EP2 receptors selectively), but it modestly attenuated responses to EP4 receptors, activation of which generated less cAMP than EP2 receptors. We conclude that inhibition of histamine-evoked Ca2+ signals by PGE2 occurs through "hyperactive signaling junctions," wherein cAMP is locally delivered to PKA at supersaturating concentrations to cause uncoupling of H1 receptors from phospholipase C. This sequence allows digital signaling from PGE2 receptors, through cAMP and PKA, to histamine-evoked Ca2+ signals.

Ccr4-Not is a conserved protein complex that shortens the 3' poly(A) tails of eukaryotic mRNAs to regulate transcript stability and translation into proteins. RNA-binding proteins are thought to facilitate recruitment of Ccr4-Not to certain mRNAs, but lack of an in-vitro-reconstituted system has slowed progress in understanding the mechanistic details of this specificity. Here, we generate a fully recombinant Ccr4-Not complex that removes poly(A) tails from RNA substrates. The intact complex is more active than the exonucleases alone and has an intrinsic preference for certain RNAs. The RNA-binding protein Mmi1 is highly abundant in preparations of native Ccr4-Not. We demonstrate a high-affinity interaction between recombinant Ccr4-Not and Mmi1. Using in vitro assays, we show that Mmi1 accelerates deadenylation of target RNAs. Together, our results support a model whereby both RNA-binding proteins and the sequence context of mRNAs influence deadenylation rate to regulate gene expression.