Salvador Eugenio C. Caoili

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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(More)
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(More)
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. Yet, this is but a relatively narrow view of the full(More)
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(More)
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(More)
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. Hence, the Immune Epitope Database (IEDB) was searched to obtain published thermodynamic and(More)
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(More)
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(More)
A mechanistically framed consensus on benchmark data and benchmarking procedures for B-cell epitope prediction methods has yet to emerge, thus presenting a critical window of 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(More)
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(More)