Publications by authors named "Adrian J Shepherd"

The emergence of SARS-CoV-2 variants has exacerbated the COVID-19 global health crisis. Thus far, all variants carry mutations in the spike glycoprotein, which is a critical determinant of viral transmission being responsible for attachment, receptor engagement and membrane fusion, and an important target of immunity. Variants frequently bear truncations of flexible loops in the N-terminal domain (NTD) of spike; the functional importance of these modifications has remained poorly characterised.

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E1 and E2 (E1E2), the fusion proteins of Hepatitis C Virus (HCV), are unlike that of any other virus yet described, and the detailed molecular mechanisms of HCV entry/fusion remain unknown. Hypervariable region-1 (HVR-1) of E2 is a putative intrinsically disordered protein tail. Here, we demonstrate that HVR-1 has an autoinhibitory function that suppresses the activity of E1E2 on free virions; this is dependent on its conformational entropy.

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Throughout its evolution, the human immune system has developed a plethora of strategies to diversify the antigenic peptide sequences that can be targeted by the CD8+ T cell response against pathogens and aberrations of self. Here we provide a general overview of the mechanisms that lead to the diversity of antigens presented by MHC class I complexes and their recognition by CD8+ T cells, together with a more detailed analysis of recent progress in two important areas that are highly controversial: the prevalence and immunological relevance of unconventional antigen peptides; and cross-recognition of antigenic peptides by the T cell receptors of CD8+ T cells.

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Objectives: Identification and validation of novel therapeutic targets is imperative to tackle the rise of drug resistance in tuberculosis. An essential Mur ligase-like gene (Rv3712), expected to be involved in cell-wall peptidoglycan (PG) biogenesis and conserved across mycobacteria, including the genetically depleted , was the primary focus of this study.

Methods: Biochemical analysis of Rv3712 was performed using inorganic phosphate release assays.

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Immunoglobulin genes are rarely considered as disease susceptibility genes despite their obvious and central contributions to immune function. This appears to be a consequence of historical views on antibody repertoire formation that no longer stand, and of difficulties that until recently surrounded the documentation of the suite of antibody genes in any individual. If these important genes are to be accessible to GWAS studies, allelic variation within the human population needs to be better documented, and a curated set of genomic variations associated with antibody genes needs to be formulated.

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CD81 plays a central role in a variety of physiological and pathological processes. Recent structural analysis of CD81 indicates that it contains an intramembrane cholesterol-binding pocket and that interaction with cholesterol may regulate a conformational switch in the large extracellular domain of CD81. Therefore, CD81 possesses a potential cholesterol-sensing mechanism; however, its relevance for protein function is thus far unknown.

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The glycoproteins of hepatitis C virus, E1E2, are unlike any other viral fusion machinery yet described, and are the current focus of immunogen design in HCV vaccine development; thus, making E1E2 both scientifically and medically important. We used pre-existing, but fragmentary, structures to model a complete ectodomain of the major glycoprotein E2 from three strains of HCV. We then performed molecular dynamic simulations to explore the conformational landscape of E2, revealing a number of important features.

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The adaptive immune system generates an incredible diversity of antigen receptors for B and T cells to keep dangerous pathogens at bay. The DNA sequences coding for these receptors arise by a complex recombination process followed by a series of productivity-based filters, as well as affinity maturation for B cells, giving considerable diversity to the circulating pool of receptor sequences. Although these datasets hold considerable promise for medical and public health applications, the complex structure of the resulting adaptive immune receptor repertoire sequencing (AIRR-seq) datasets makes analysis difficult.

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Article Synopsis
  • - VDJbase is a free database that provides detailed gene sequence data from studies of immune receptor repertoires, allowing researchers to investigate genetic differences in immunoglobulin and T cell receptor genes.
  • - The platform offers tools for users to visualize and analyze genotype and haplotype data, helping identify genetic predispositions to diseases by highlighting prevalent alleles in different populations.
  • - Users can access VDJbase without a login at https://www.vdjbase.org/, and all data and code are available for download under creative commons licenses.
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High-throughput sequencing of the adaptive immune receptor repertoire (AIRR-seq) is providing unprecedented insights into the immune response to disease and into the development of immune disorders. The accurate interpretation of AIRR-seq data depends on the existence of comprehensive germline gene reference sets. Current sets are known to be incomplete and unrepresentative of the degree of polymorphism and diversity in human and animal populations.

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Single missense mutations in the gene encoding the coagulation protein factor VIII give rise predominantly to non-severe hemophilia A. Despite only a single amino acid sequence difference between the replacement, therapeutic factor VIII and the patient's endogenous factor VIII, therapeutic factor VIII may still be perceived as foreign by the recipient's immune system and trigger an immune response (inhibitor). Inhibitor formation is a life-long risk for patients with non-severe hemophilia A treated with therapeutic factor VIII, but remains difficult to predict.

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The third variable (V3) loop of HIV-1 gp120 is an immunodominant region targeted by neutralizing antibodies (nAbs). Despite limited breadth, better characterization of the structural details of the interactions between these nAbs and their target epitopes would enhance our understanding of the mechanism of neutralization and facilitate designing better immunogens to induce nAbs with greater breadth. Recently, we isolated two anti-V3 neutralizing monoclonal antibodies (MAbs), 10A3 and 10A37, from a rabbit immunized with gp120 of the M group consensus sequence.

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In studying the binding of host antibodies to the surface antigens of pathogens, the structural and functional characterization of antibody-antigen complexes by X-ray crystallography and binding assay is important. However, the characterization requires experiments that are typically time consuming and expensive: thus, many antibody-antigen complexes are under-characterized. For vaccine development and disease surveillance, it is often vital to assess the impact of amino acid substitutions on antibody binding.

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Next-generation sequencing is making it possible to study the antibody repertoire of an organism in unprecedented detail, and, by so doing, to characterize its behavior in the response to infection and in pathological conditions such as autoimmunity and cancer. The polymorphic nature of the repertoire poses unique challenges that rule out the use of many commonly used NGS methods and require tradeoffs to be made when considering experimental design.We outline the main contexts in which antibody repertoire analysis has been used, and summarize the key tools that are available.

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Understanding metabolic pathways is one of the most important fields in bioscience in the post-genomic era, but curating metabolic pathways requires considerable man-power. As such there is a lack of reliable, experimentally verified metabolic pathways in databases and databases are forced to predict all but the most immediately useful pathways.Text-mining has the potential to solve this problem, but while sophisticated text-mining methods have been developed to assist the curation of many types of biomedical networks, such as protein-protein interaction networks, the mining of metabolic pathways from the literature has been largely neglected by the text-mining community.

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The Forkhead box transcription factor FoxP3 is pivotal to the development and function of regulatory T cells (Tregs), which make a major contribution to peripheral tolerance. FoxP3 is believed to perform a regulatory role in all the vertebrate species in which it has been detected. The prevailing view is that FoxP3 is absent in birds and that avian Tregs rely on alternative developmental and suppressive pathways.

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There are at present few tools available to assist with the determination and analysis of B-cell lineage trees from next-generation sequencing data. Here we present two utilities that support automated large-scale analysis and the creation of publication-quality results. The tools are available on the web and are also available for download so that they can be integrated into an automated pipeline.

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Article Synopsis
  • Over 500 mutations in the F8 gene are linked to non-severe haemophilia A, with some genotypes posing a higher risk of inhibitor formation.
  • The study uses a computational tool, NetMHCII, to analyze how mutations affect antigen presentation and to identify HLA peptide binding patterns that could indicate future inhibitor risk.
  • Researchers found that many F8 genotypes (65%) are likely to have a low risk of generating the immune response needed for inhibitor production, highlighting the need to consider both F8 genotypes and individual HLA profiles for more accurate risk predictions.
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The extent of the role of N-linked glycans (N-glycans) in shielding influenza A hemagglutinin (HA) against host antibodies has proved controversial, with different authors making widely different assumptions. One common assumption is that N-glycans physically shield surface residues that are near to glycosylation sites, thereby preventing antibodies from binding to them. However, it is unclear, from existing experimental evidence, whether antibodies that bind close to N-glycans are a rare or commonplace feature of human herd immune responses to influenza AHA.

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The study of biological networks is playing an increasingly important role in the life sciences. Many different kinds of biological system can be modelled as networks; perhaps the most important examples are protein-protein interaction (PPI) networks, metabolic pathways, gene regulatory networks, and signalling networks. Although much useful information is easily accessible in publicly databases, a lot of extra relevant data lies scattered in numerous published papers.

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Recently, a number of broad-spectrum human antibodies binding to the stalk region of influenza A haemagglutinin (HA) have been isolated. As this region tends to develop substitutions at a slower rate than other regions of HA, a vaccine eliciting such antibodies could have a longer effective life. But this begs a question: is the stalk resistant to change even in the face of evolutionary pressure? In this paper, we analysed the known epitopes in the H3 stalk and, utilizing a collection of 3440 sequences, present a novel approach for detecting putative B-cell epitopes in regions such as this, in which mutations occur infrequently.

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Background: Increasingly biological text mining research is focusing on the extraction of complex relationships relevant to the construction and curation of biological networks and pathways. However, one important category of pathway - metabolic pathways - has been largely neglected.Here we present a relatively simple method for extracting metabolic reaction information from free text that scores different permutations of assigned entities (enzymes and metabolites) within a given sentence based on the presence and location of stemmed keywords.

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Although it is widely acknowledged that most B-cell epitopes are discontinuous, the degree of discontinuity is poorly understood. For example, given that an antigen having a single epitope that has been chopped into peptides of a specific length, what is the likelihood that one of the peptides will span all the residues belonging to that epitope? Or, alternatively, what is the largest proportion of the epitope's residues that any peptide is likely to contain? These and similar questions are of direct relevance both to computational methods that aim to predict the location of epitopes from sequence (linear B-cell epitope prediction methods) and window-based experimental methods that aim to locate epitopes by assessing the strength of antibody binding to synthetic peptides on a chip. In this paper we present an analysis of the degree of B-cell epitope discontinuity, both in terms of the structural epitopes defined by a set of antigen-antibody complexes in the Protein Data Bank, and with respect to the distribution of key residues that form functional epitopes.

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In this paper we undertake an analysis of the antigenicity of influenza A virus hemagglutinin. We developed a novel computational approach to the identification of antigenically active regions and showed that the amino acid substitutions between successive predominant seasonal strains form clusters that are consistent, in terms of both their location and their size, with the properties of B-cell epitopes in general and with those epitopes that have been identified experimentally in influenza A virus hemagglutinin to date. Such an interpretation provides a biologically plausible framework for an understanding of the location of antigenically important substitutions that is more specific than the canonical "antigenic site" model and provides an effective basis for deriving models that predict antigenic escape in the H3N2 subtype.

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Background: Transcription factors (TFs) control transcription by binding to specific regions of DNA called transcription factor binding sites (TFBSs). The identification of TFBSs is a crucial problem in computational biology and includes the subtask of predicting the location of known TFBS motifs in a given DNA sequence. It has previously been shown that, when scoring matches to known TFBS motifs, interdependencies between positions within a motif should be taken into account.

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