B-Cell Epitope Prediction for Antipeptide Paratopes with the HAPTIC2/HEPTAD User Toolkit (HUT).

B-cell epitope prediction is key to developing peptide-based vaccines and immunodiagnostics along with antibodies for prophylactic, therapeutic and/or diagnostic use. This entails estimating paratope binding affinity for variable-length peptidic sequences subject to constraints on both paratope accessibility and antigen conformational flexibility, as described herein for the HAPTIC2/HEPTAD User Toolkit (HUT). HUT comprises the Heuristic Affinity Prediction Tool for Immune Complexes 2 (HAPTIC2), the HAPTIC2-like Epitope Prediction Tool for Antigen with Disulfide (HEPTAD) and the HAPTIC2/HEPTAD Input Preprocessor (HIP).

Immunologic, genetic, and ecological interplay of factors involved in allergic diseases.

An allergic or type I hypersensitivity reaction involves a misdirected immune overreaction to innocuous environmental and dietary antigens called allergens. The genetic predisposition to allergic disease, referred to as atopy, can be expressed as a variety of manifestations-e.g.

Beyond B-Cell Epitopes: Curating Positive Data on Antipeptide Paratope Binding to Support Peptide-Based Vaccine Design.

Background: B-cell epitope prediction is a computational approach originally developed to support the design of peptide-based vaccines for inducing protective antibody-mediated immunity, as exemplified by neutralization of biological activity (e.g., pathogen infectivity).

A Human Erythrocyte-based Haemolysis Assay for the Evaluation of Human Complement Activity.

The complement system consists of at least 50 proteins that serve as one of the first lines of defence against foreign, or damaged, cells and invading microorganisms. Its dysregulation underlies the pathophysiology of many different diseases, which makes functional assays of complement activity crucial; they are, however, underutilised. Standard haemolysis assays for the analysis of complement function employ sensitised non-human erythrocytes (e.

Development and Characterization of Polymeric Peptides for Antibody Tagging of Bacterial Targets.

Background: Microbe-Binding Peptides (MBPs) are currently being investigated to address the problem of antimicrobial resistance. Strategies enhancing their antimicrobial activity have been developed, including peptide dimerization. Here, we present an alternative approach based on peptide polymerization, yielding hapten-labelled polymeric MBPs that mediate tagging of bacteria with anti-hapten antibodies, for enhanced immune recognition by host phagocytes.

Functional analysis of variants found in classic galactosemia patients using a novel cell-free translation method.

Classic galactosemia is an autosomal recessive disorder caused by deleterious variants in the galactose-1-phosphate uridylyltransferase () gene. GALT enzyme deficiency leads to an increase in the levels of galactose and its metabolites in the blood causing neurodevelopmental and other clinical complications in affected individuals. Two variants NM_000155.

Delineating Surface Epitopes of Lyme Disease Pathogen Targeted by Highly Protective Antibodies of New Zealand White Rabbits.

Lyme disease (LD), the most prevalent vector-borne illness in the United States and Europe, is caused by No vaccine is available for humans. Dogmatically, can establish a persistent infection in the mammalian host (e.g.

Identification of Surface Epitopes Associated with Protection against Highly Immune-Evasive VlsE-Expressing Lyme Disease Spirochetes.

The tick-borne pathogen is responsible for approximately 300,000 Lyme disease (LD) cases per year in the United States. Recent increases in the number of LD cases, in addition to the spread of the tick vector and a lack of a vaccine, highlight an urgent need for designing and developing an efficacious LD vaccine. Identification of protective epitopes that could be used to develop a second-generation (subunit) vaccine is therefore imperative.

Expressing Redundancy among Linear-Epitope Sequence Data Based on Residue-Level Physicochemical Similarity in the Context of Antigenic Cross-Reaction.

Epitope-based design of vaccines, immunotherapeutics, and immunodiagnostics is complicated by structural changes that radically alter immunological outcomes. This is obscured by expressing redundancy among linear-epitope data as fractional sequence-alignment identity, which fails to account for potentially drastic loss of binding affinity due to single-residue substitutions even where these might be considered conservative in the context of classical sequence analysis. From the perspective of immune function based on molecular recognition of epitopes, functional redundancy of epitope data (FRED) thus may be defined in a biologically more meaningful way based on residue-level physicochemical similarity in the context of antigenic cross-reaction, with functional similarity between epitopes expressed as the Shannon information entropy for differential epitope binding.

An integrative structure-based framework for predicting biological effects mediated by antipeptide antibodies.

A general framework is presented for predicting quantitative biological effects mediated by antipeptide antibodies, primarily on the basis of antigen structure (possibly featuring intrinsic disorder) analyzed to estimate epitope-paratope binding affinities, which in turn is considered within the context of dose-response relationships as regards antibody concentration. This is illustrated mainly using an approach based on protein structural energetics, whereby expected amounts of solvent-accessible surface area buried upon epitope-paratope binding are related to the corresponding binding affinity, which is estimated from putative B-cell epitope structure with implicit treatment of paratope structure, for antipeptide antibodies either reacting with peptides or cross-reacting with cognate protein antigens. Key methods described are implemented in SAPPHIRE/SUITE (Structural-energetic Analysis Program for Predicting Humoral Immune Response Epitopes/SAPPHIRE User Interface Tool Ensemble; publicly accessible via http://freeshell.

Hybrid methods for B-cell epitope prediction.

Many computational approaches to B-cell epitope prediction have been published, including combinations of previously proposed methods, which complicates the tasks of further developing such computational approaches and of selecting those most appropriate for practical applications (e.g., the design of novel immunodiagnostics and vaccines).

Benchmarking B-cell epitope prediction with quantitative dose-response data on antipeptide antibodies: towards novel pharmaceutical product development.

B-cell epitope prediction can enable novel pharmaceutical product development. However, a mechanistically framed consensus has yet to emerge on benchmarking such prediction, thus presenting an opportunity to establish standards of practice that circumvent epistemic inconsistencies of casting the epitope prediction task as a binary-classification problem. As an alternative to conventional dichotomous qualitative benchmark data, quantitative dose-response data on antibody-mediated biological effects are more meaningful from an information-theoretic perspective in the sense that such effects may be expressed as probabilities (e.

Beyond new chemical entities: advancing drug development based on functional versatility of antibodies.

Antibody-type agents (i.e., antibodies and derivatives thereof) may be produced as clinically valuable antidotes, which conceivably could be developed in tandem with prospective new pharmaceutical products so as to render the risks of clinical trials more acceptable from a regulatory standpoint.

Antidotes, antibody-mediated immunity and the future of pharmaceutical product development.

If new scientific knowledge is to be more efficiently generated and applied toward the advancement of health, human safety must be more effectively addressed in the conduct of research. Given the present difficulties of accurately predicting biological outcomes of novel interventions in vivo, the imperative of human safety suggests the development of novel pharmaceutical products in tandem with their prospective antidotes in anticipation of possible adverse events, to render the risks of initial clinical trials more acceptable from a regulatory standpoint. Antibody-mediated immunity provides a generally applicable mechanistic basis for developing antidotes to both biologicals and small-molecule drugs (such that antibodies may serve as antidotes to pharmaceutical agents as a class including other antibodies) and also for the control and prevention of both infectious and noninfectious diseases via passive or active immunization.

On the meaning of affinity limits in B-cell epitope prediction for antipeptide antibody-mediated immunity.

B-cell epitope prediction aims to aid the design of peptide-based immunogens (e.g., vaccines) for eliciting antipeptide antibodies that protect against disease, but such antibodies fail to confer protection and even promote disease if they bind with low affinity.

Benchmarking B-cell epitope prediction for the design of peptide-based vaccines: problems and prospects.

To better support the design of peptide-based vaccines, refinement of methods to predict B-cell epitopes necessitates meaningful benchmarking against empirical data on the cross-reactivity of polyclonal antipeptide antibodies with proteins, such that the positive data reflect functionally relevant cross-reactivity (which is consistent with antibody-mediated change in protein function) and the negative data reflect genuine absence of cross-reactivity (rather than apparent absence of cross-reactivity due to artifactual masking of B-cell epitopes in immunoassays). These data are heterogeneous in view of multiple factors that complicate B-cell epitope prediction, notably physicochemical factors that define key structural differences between immunizing peptides and their cognate proteins (e.g.

Immunization with peptide-protein conjugates: impact on benchmarking B-cell epitope prediction for vaccine design.

Benchmarking B-cell epitope prediction for vaccine design is meaningful if based on empirical reference data pertaining to cross-reactivities of antipeptide antibodies with native protein antigens; yet it is complicated by such data acquired using antibodies raised against peptide-protein conjugates, as peptide-protein conjugation can differentially suppress antibody responses to peptide epitopes.

A structural-energetic basis for B-cell epitope prediction.

Structural-energetic analysis of peptide and protein antigens in the context of binding to antibody reveals fundamental differences between the cross-reactions of antipeptide antibody with protein and antiprotein antibody with peptide, providing a physicochemical basis for B-cell epitope prediction as applied to the development of peptide-based vaccines and immunodiagnostics.