flexiMAP: a regression-based method for discovering differential alternative polyadenylation events in standard RNA-seq data.

MOTIVATION: We present flexible Modeling of Alternative PolyAdenylation (flexiMAP), a new beta-regression-based method implemented in R, for discovering differential alternative polyadenylation events in standard RNA-seq data. RESULTS: We show, using both simulated and real data, that flexiMAP exhibits a good balance between specificity and sensitivity and compares favourably to existing methods, especially at low fold changes. In addition, the tests on simulated data reveal some hitherto unrecognized caveats of existing methods. Importantly, flexiMAP allows modeling of multiple known covariates that often confound the results of RNA-seq data analysis. AVAILABILITY AND IMPLEMENTATION: The flexiMAP R package is available at: https://github.com/kszkop/flexiMAP. Scripts and data to reproduce the analysis in this paper are available at: https://doi.org/10.5281/zenodo.3689788. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Flexibility and intrinsic disorder are conserved features of hepatitis C virus E2 glycoprotein.

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. Despite high sequence divergence, and subtle differences in the models, E2 from different strains behave similarly, possessing a stable core flanked by highly flexible regions, some of which perform essential functions such as receptor binding. Comparison with sequence data suggest that this consistent behaviour is conferred by a network of conserved residues that act as hinge and anchor points throughout E2. The variable regions (HVR-1, HVR-2 and VR-3) exhibit particularly high flexibility, and bioinformatic analysis suggests that HVR-1 is a putative intrinsically disordered protein region. Dynamic cross-correlation analyses demonstrate intramolecular communication and suggest that specific regions, such as HVR-1, can exert influence throughout E2. To support our computational approach we performed small-angle X-ray scattering with purified E2 ectodomain; this data was consistent with our MD experiments, suggesting a compact globular core with peripheral flexible regions. This work captures the dynamic behaviour of E2 and has direct relevance to the interaction of HCV with cell-surface receptors and neutralising antibodies.

Factor VIII cross-matches to the human proteome reduce the predicted inhibitor risk in missense mutation hemophilia A.

Single missense mutations in the F8 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. The aim of this study was to understand whether fortuitous, primary sequence cross-matches between therapeutic factor VIII and proteins in the human proteome are the reason why certain F8 mutations are not associated with inhibitor formation. We predicted which therapeutic factor VIII differences are potentially perceived as foreign by helper T cells - a necessary precursor to inhibitor development - and then scanned potentially immunogenic peptides against more than 100,000 proteins in the proteome. As there are hundreds of disease-causing F8 missense mutations and the human leukocyte antigen gene complex governing peptide presentation to helper T cells is highly polymorphic, these calculations pose a huge combinatorial challenge that we addressed computationally. We found that cross-matches between therapeutic factor VIII and the human proteome are commonplace and have a profound impact on the predicted risk of inhibitor development. Our results emphasize the importance of knowing both the F8 missense mutation and the human leukocyte antigen alleles of a patient with missense mutation hemophilia A if his underlying risk of inhibitor development is to be estimated.

N-linked glycans on influenza A H3N2 hemagglutinin constrain binding of host antibodies, but shielding is limited.

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. The aim of this paper is to present a computational analysis of mutations in the vicinity of N-glycans that will facilitate a better understanding of their protective role. We identify, from an analysis of over 6000 influenza A H3N2 sequences, a set of residues adjacent to N-glycosylation sites that are highly likely to be involved in antigenic escape from host antibodies. Fifteen of these residues occur within 10 Å of an N-glycosylation site. Hence, we conclude that it is relatively common for antibodies to bind in close proximity to N-glycans on the surface ofHA, with any shielding effect largely attributable to the inability of host antibodies to bind across an N-glycan attachment site, rather than to the physical masking of neighboring residues.

A large-scale computational study of inhibitor risk in non-severe haemophilia A.

Over 500 missense F8 mutations have been reported to cause non-severe haemophilia A. Some F8 genotypes appear to confer a higher risk of inhibitor formation than others and individuals with the same F8 genotype may have differing risks of inhibitor formation. We present an in silico strategy demonstrating the heterogeneity of factor VIII (FVIII)-derived antigen presentation whilst identifying patterns of human leucocyte antigen (HLA) peptide binding that might predict future inhibitor risk. A well-validated computational tool, NetMHCII, enabled large-scale comparison of predicted antigen presentation between endogenous, mutated FVIII-derived peptides and wild-type, therapeutic FVIII-derived peptides spanning all F8 missense mutation positions reported to The Haemophilia A Mutation, Structure and Resource Site (HADB). We identify 40 F8 genotypes to be 'low risk' at a 50% inhibitory concentration (IC50 )-binding threshold of 300 nmol/l (P = 0·00005), defined as absence of novel peptide-major histocompatibility complex (MHC) surfaces for all 14 common HLA-DR alleles assessed. Analysing each of the possible 7280 F8 genotype/HLA-DR permutations individually at an IC50 threshold of 300 nmol/l, 65% are predicted to not generate a novel peptide-MHC surface that would be necessary to engage T cell help for subsequent anti-FVIII antibody generation. This study demonstrates the future importance of interpreting F8 genotype in the context of an individual's HLA profile to personalize inhibitor risk prediction.

Molecular architecture and functional analysis of NetB, a pore-forming toxin from Clostridium perfringens.

NetB is a pore-forming toxin produced by Clostridium perfringens and has been reported to play a major role in the pathogenesis of avian necrotic enteritis, a disease that has emerged due to the removal of antibiotics in animal feedstuffs. Here we present the crystal structure of the pore form of NetB solved to 3.9 Å. The heptameric assembly shares structural homology to the staphylococcal α-hemolysin. However, the rim domain, a region that is thought to interact with the target cell membrane, shows sequence and structural divergence leading to the alteration of a phosphocholine binding pocket found in the staphylococcal toxins. Consistent with the structure we show that NetB does not bind phosphocholine efficiently but instead interacts directly with cholesterol leading to enhanced oligomerization and pore formation. Finally we have identified conserved and non-conserved amino acid positions within the rim loops that significantly affect binding and toxicity of NetB. These findings present new insights into the mode of action of these pore-forming toxins, enabling the design of more effective control measures against necrotic enteritis and providing potential new tools to the field of bionanotechnology.

Evolution in the influenza A H3 stalk - a challenge for broad-spectrum vaccines?

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. We concluded that there have been periods of activity in the stalk that are consistent with the evolution of antigenic escape. This work casts light on the presence of stalk-binding antibodies in the population as a whole and, through the analysis of antigenically active regions in the stalk, may contribute to the identification of epitopes that are refractive to change and hence useful for vaccine development.

Visualisation of variable binding pockets on protein surfaces by probabilistic analysis of related structure sets.

BACKGROUND: Protein structures provide a valuable resource for rational drug design. For a protein with no known ligand, computational tools can predict surface pockets that are of suitable size and shape to accommodate a complementary small-molecule drug. However, pocket prediction against single static structures may miss features of pockets that arise from proteins' dynamic behaviour. In particular, ligand-binding conformations can be observed as transiently populated states of the apo protein, so it is possible to gain insight into ligand-bound forms by considering conformational variation in apo proteins. This variation can be explored by considering sets of related structures: computationally generated conformers, solution NMR ensembles, multiple crystal structures, homologues or homology models. It is non-trivial to compare pockets, either from different programs or across sets of structures. For a single structure, difficulties arise in defining particular pocket's boundaries. For a set of conformationally distinct structures the challenge is how to make reasonable comparisons between them given that a perfect structural alignment is not possible. RESULTS: We have developed a computational method, Provar, that provides a consistent representation of predicted binding pockets across sets of related protein structures. The outputs are probabilities that each atom or residue of the protein borders a predicted pocket. These probabilities can be readily visualised on a protein using existing molecular graphics software. We show how Provar simplifies comparison of the outputs of different pocket prediction algorithms, of pockets across multiple simulated conformations and between homologous structures. We demonstrate the benefits of use of multiple structures for protein-ligand and protein-protein interface analysis on a set of complexes and consider three case studies in detail: i) analysis of a kinase superfamily highlights the conserved occurrence of surface pockets at the active and regulatory sites; ii) a simulated ensemble of unliganded Bcl2 structures reveals extensions of a known ligand-binding pocket not apparent in the apo crystal structure; iii) visualisations of interleukin-2 and its homologues highlight conserved pockets at the known receptor interfaces and regions whose conformation is known to change on inhibitor binding. CONCLUSIONS: Through post-processing of the output of a variety of pocket prediction software, Provar provides a flexible approach to the analysis and visualization of the persistence or variability of pockets in sets of related protein structures.

Analysis of antigenically important residues in human influenza A virus in terms of B-cell epitopes.

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. Our results support recent indications that antibodies binding to the "stalk" region of hemagglutinin are found in the human population and exert evolutionary pressure on the virus. Our computational approach provides a possible method for identifying antigenic escape through evolution in this region, which in some cases will not be identified by the hemagglutinin inhibition assay.

An entropic safety catch controls hepatitis C virus entry and antibody resistance.

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. Thus, HVR-1 is akin to a safety catch that prevents premature triggering of E1E2 activity. Crucially, this mechanism is turned off by host receptor interactions at the cell surface to allow entry. Mutations that reduce conformational entropy in HVR-1, or genetic deletion of HVR-1, turn off the safety catch to generate hyper-reactive HCV that exhibits enhanced virus entry but is thermally unstable and acutely sensitive to neutralising antibodies. Therefore, the HVR-1 safety catch controls the efficiency of virus entry and maintains resistance to neutralising antibodies. This discovery provides an explanation for the ability of HCV to persist in the face of continual immune assault and represents a novel regulatory mechanism that is likely to be found in other viral fusion machinery.

ImmunoGrid, an integrative environment for large-scale simulation of the immune system for vaccine discovery, design and optimization.

Vaccine research is a combinatorial science requiring computational analysis of vaccine components, formulations and optimization. We have developed a framework that combines computational tools for the study of immune function and vaccine development. This framework, named ImmunoGrid combines conceptual models of the immune system, models of antigen processing and presentation, system-level models of the immune system, Grid computing, and database technology to facilitate discovery, formulation and optimization of vaccines. ImmunoGrid modules share common conceptual models and ontologies. The ImmunoGrid portal offers access to educational simulators where previously defined cases can be displayed, and to research simulators that allow the development of new, or tuning of existing, computational models. The portal is accessible at .

A computational analysis of the antigenic properties of haemagglutinin in influenza A H3N2.

MOTIVATION: Modelling antigenic shift in influenza A H3N2 can help to predict the efficiency of vaccines. The virus is known to exhibit sudden jumps in antigenic distance, and prediction of such novel strains from amino acid sequence differences remains a challenge. RESULTS: From analysis of 6624 amino acid sequences of wild-type H3, we propose updates to the frequently referenced list of 131 amino acids located at or near the five identified antibody binding regions in haemagglutinin (HA). We introduce a class of predictive models based on the analysis of amino acid changes in these binding regions, and extend the principle to changes in HA1 as a whole by dividing the molecule into regional bands. Our results show that a range of simple models based on banded changes give better predictive performance than models based on the established five canonical regions and can identify a higher proportion of vaccine escape candidates among novel strains than a current state-of-the-art model.

Clostridium perfringens epsilon-toxin shows structural similarity to the pore-forming toxin aerolysin.

Epsilon-toxin from Clostridium perfringens is a lethal toxin. Recent studies suggest that the toxin acts via an unusually potent pore-forming mechanism. Here we report the crystal structure of epsilon-toxin, which reveals structural similarity to aerolysin from Aeromonas hydrophila. Pore-forming toxins can change conformation between soluble and transmembrane states. By comparing the two toxins, we have identified regions important for this transformation.

Identification of the HLA-DM/HLA-DR interface.

Human leukocyte antigen (HLA)-DM is a critical participant in antigen presentation that catalyzes the dissociation of the Class II-associated Invariant chain-derived Peptide (CLIP) from the major histocompatibility complex (MHC) Class II molecules. There is competition amongst peptides for access to an MHC Class II groove and it has been hypothesised that DM functions as a 'peptide editor' that catalyzes the replacement of one peptide for another within the groove. It is established that the DM catalyst interacts directly with the MHC Class II but the precise location of the interface is unknown. Here, we combine previously described mutational data with molecular docking and energy minimisation simulations to identify a putative interaction site of >4000A2 which agrees with known point mutational data for both the DR and DM molecule. The docked structure is validated by comparison with experimental data and previously determined properties of protein-protein interfaces. A possible dissociation mechanism is suggested by the presence of an acidic cluster near the N terminus of the bound peptide.

The pore structure of Clostridium perfringens epsilon toxin.

Epsilon toxin (Etx), a potent pore forming toxin (PFT) produced by Clostridium perfringens, is responsible for the pathogenesis of enterotoxaemia of ruminants and has been suggested to play a role in multiple sclerosis in humans. Etx is a member of the aerolysin family of ß-PFTs (aß-PFTs). While the Etx soluble monomer structure was solved in 2004, Etx pore structure has remained elusive due to the difficulty of isolating the pore complex. Here we show the cryo-electron microscopy structure of Etx pore assembled on the membrane of susceptible cells. The pore structure explains important mutant phenotypes and suggests that the double ß-barrel, a common feature of the aß-PFTs, may be an important structural element in driving efficient pore formation. These insights provide the framework for the development of novel therapeutics to prevent human and animal infections, and are relevant for nano-biotechnology applications.

Towards a lightweight generic computational grid framework for biological research.

BACKGROUND: An increasing number of scientific research projects require access to large-scale computational resources. This is particularly true in the biological field, whether to facilitate the analysis of large high-throughput data sets, or to perform large numbers of complex simulations - a characteristic of the emerging field of systems biology. RESULTS: In this paper we present a lightweight generic framework for combining disparate computational resources at multiple sites (ranging from local computers and clusters to established national Grid services). A detailed guide describing how to set up the framework is available from the following URL: http://igrid-ext.cryst.bbk.ac.uk/portal_guide/. CONCLUSION: This approach is particularly (but not exclusively) appropriate for large-scale biology projects with multiple collaborators working at different national or international sites. The framework is relatively easy to set up, hides the complexity of Grid middleware from the user, and provides access to resources through a single, uniform interface. It has been developed as part of the European ImmunoGrid project.

Toward the atomistic simulation of T cell epitopes automated construction of MHC: peptide structures for free energy calculations.

Epitopes mediated by T cells lie at the heart of the adaptive immune response and form the essential nucleus of anti-tumour peptide or epitope-based vaccines. Antigenic T cell epitopes are mediated by major histocompatibility complex (MHC) molecules, which present them to T cell receptors. Calculating the affinity between a given MHC molecule and an antigenic peptide using experimental approaches is both difficult and time consuming, thus various computational methods have been developed for this purpose. A server has been developed to allow a structural approach to the problem by generating specific MHC:peptide complex structures and providing configuration files to run molecular modelling simulations upon them. A system has been produced which allows the automated construction of MHC:peptide structure files and the corresponding configuration files required to execute a molecular dynamics simulation using NAMD. The system has been made available through a web-based front end and stand-alone scripts. Previous attempts at structural prediction of MHC:peptide affinity have been limited due to the paucity of structures and the computational expense in running large scale molecular dynamics simulations. The MHCsim server (http://igrid-ext.cryst.bbk.ac.uk/MHCsim) allows the user to rapidly generate any desired MHC:peptide complex and will facilitate molecular modelling simulation of MHC complexes on an unprecedented scale.

Investigating Substitutions in Antibody-Antigen Complexes Using Molecular Dynamics: A Case Study with Broad-spectrum, Influenza A Antibodies.

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. For example, are there antibody substitutions capable of improving binding without a loss of breadth, or antigen substitutions that lead to antigenic escape? The questions cannot be answered reliably from sequence variation alone, exhaustive substitution assays are usually impractical, and alanine scans provide at best an incomplete identification of the critical residue-residue interactions. Here, we show that, given an initial structure of an antibody bound to an antigen, molecular dynamics simulations using the energy method molecular mechanics with Generalized Born surface area (MM/GBSA) can model the impact of single amino acid substitutions on antibody-antigen binding energy. We apply the technique to three broad-spectrum antibodies to influenza A hemagglutinin and examine both previously characterized and novel variant strains observed in the human population that may give rise to antigenic escape. We find that in some cases the impact of a substitution is local, while in others it causes a reorientation of the antibody with wide-ranging impact on residue-residue interactions: this explains, in part, why the change in chemical properties of a residue can be, on its own, a poor predictor of overall change in binding energy. Our estimates are in good agreement with experimental results-indeed, they approximate the degree of agreement between different experimental techniques. Simulations were performed on commodity computer hardware; hence, this approach has the potential to be widely adopted by those undertaking infectious disease research. Novel aspects of this research include the application of MM/GBSA to investigate binding between broadly binding antibodies and a viral glycoprotein; the development of an approach for visualizing substrate-ligand interactions; and the use of experimental assay data to rescale our predictions, allowing us to make inferences about absolute, as well as relative, changes in binding energy.

Dysregulation of Alternative Poly-adenylation as a Potential Player in Autism Spectrum Disorder.

We present here the hypothesis that alternative poly-adenylation (APA) is dysregulated in the brains of individuals affected by Autism Spectrum Disorder (ASD), due to disruptions in the calcium signaling networks. APA, the process of selecting different poly-adenylation sites on the same gene, yielding transcripts with different-length 3' untranslated regions (UTRs), has been documented in different tissues, stages of development and pathologic conditions. Differential use of poly-adenylation sites has been shown to regulate the function, stability, localization and translation efficiency of target RNAs. However, the role of APA remains rather unexplored in neurodevelopmental conditions. In the human brain, where transcripts have the longest 3' UTRs and are thus likely to be under more complex post-transcriptional regulation, erratic APA could be particularly detrimental. In the context of ASD, a condition that affects individuals in markedly different ways and whose symptoms exhibit a spectrum of severity, APA dysregulation could be amplified or dampened depending on the individual and the extent of the effect on specific genes would likely vary with genetic and environmental factors. If this hypothesis is correct, dysregulated APA events might be responsible for certain aspects of the phenotypes associated with ASD. Evidence supporting our hypothesis is derived from standard RNA-seq transcriptomic data but we suggest that future experiments should focus on techniques that probe the actual poly-adenylation site (3' sequencing). To address issues arising from the use of post-mortem tissue and low numbers of heterogeneous samples affected by confounding factors (such as the age, gender and health of the individuals), carefully controlled in vitro systems will be required to model the effect of calcium signaling dysregulation in the ASD brain.

Statistical deconvolution of enthalpic energetic contributions to MHC-peptide binding affinity.

BACKGROUND: MHC Class I molecules present antigenic peptides to cytotoxic T cells, which forms an integral part of the adaptive immune response. Peptides are bound within a groove formed by the MHC heavy chain. Previous approaches to MHC Class I-peptide binding prediction have largely concentrated on the peptide anchor residues located at the P2 and C-terminus positions. RESULTS: A large dataset comprising MHC-peptide structural complexes was created by re-modelling pre-determined x-ray crystallographic structures. Static energetic analysis, following energy minimisation, was performed on the dataset in order to characterise interactions between bound peptides and the MHC Class I molecule, partitioning the interactions within the groove into van der Waals, electrostatic and total non-bonded energy contributions. CONCLUSION: The QSAR techniques of Genetic Function Approximation (GFA) and Genetic Partial Least Squares (G/PLS) algorithms were used to identify key interactions between the two molecules by comparing the calculated energy values with experimentally-determined BL50 data. Although the peptide termini binding interactions help ensure the stability of the MHC Class I-peptide complex, the central region of the peptide is also important in defining the specificity of the interaction. As thermodynamic studies indicate that peptide association and dissociation may be driven entropically, it may be necessary to incorporate entropic contributions into future calculations.