B-cell epitope prediction for peptide-based vaccine design: towards a paradigm of biological outcomes for global health
Global health must address a rapidly evolving burden of disease, hence the urgent need for versatile generic technologies exemplified by peptide-based vaccines. B-cell epitope prediction is crucial for designing such vaccines; yet this approach has thus far been largely unsuccessful, prompting further inquiry into the underlying reasons for its apparent inadequacy. Two major obstacles to the development of B-cell epitope prediction for peptide-based vaccine design are (1) the prevailing binary
... prevailing binary classification paradigm, which mandates the problematic dichotomization of continuous outcome variables, and (2) failure to explicitly model biological consequences of immunization that are relevant to practical considerations of safety and efficacy. The first obstacle is eliminated by redefining the predictive task as quantitative estimation of empirically observable biological effects of antibody-antigen binding, such that prediction is benchmarked using measures of correlation between continuous rather than dichotomous variables; but this alternative approach by itself fails to address the second obstacle even if benchmark data are selected to exclusively reflect functionally relevant cross-reactivity of antipeptide antibodies with protein antigens (as evidenced by antibody-modulated protein biological activity), particularly where only antibody-antigen binding is actually predicted as a surrogate for its biological effects. To overcome the second obstacle, the prerequisite is deliberate effort to predict, a priori, biological outcomes that are of immediate practical significance from the perspective of vaccination. This demands a much broader and deeper systems view of immunobiology than has hitherto been invoked for B-cell epitope prediction. Such a view would facilitate comprehension of many crucial yet largely neglected aspects of the vaccine-design problem. Of these, immunodominance among B-cell epitopes is a central unifying theme that subsumes immune phenomena of tolerance, imprinting and refocusing; but it is meaningful for vaccine design only in the light of disease-specific pathophysiology, which for infectious processes is complicated by host-pathogen coevolution. To better support peptide-based vaccine design, B-cell epitope prediction would entail individualized quantitative estimation of biological outcomes relevant to safety and efficacy. Passive-immunization experiments could serve as an important initial proving ground for B-cell epitope prediction en route to vaccine-design applications, by restricting biological complexity to render epitopeprediction problems more computationally tractable.