(C) PLOS One
This story was originally published by PLOS One and is unaltered.
. . . . . . . . . .



B-cell epitope discovery: The first protein flexibility-based algorithm–Zika virus conserved epitope demonstration [1]

['Daniel W. Biner', 'Department Of Chemistry', 'Indiana University', 'Bloomington', 'Indiana', 'United States Of America', 'Jason S. Grosch', 'Peter J. Ortoleva']

Date: 2023-04

Antibody-antigen interaction–at antigenic local environments called B-cell epitopes–is a prominent mechanism for neutralization of infection. Effective mimicry, and display, of B-cell epitopes is key to vaccine design. Here, a physical approach is evaluated for the discovery of epitopes which evolve slowly over closely related pathogens (conserved epitopes). The approach is 1) protein flexibility-based and 2) demonstrated with clinically relevant enveloped viruses, simulated via molecular dynamics. The approach is validated against 1) seven structurally characterized enveloped virus epitopes which evolved the least (out of thirty-nine enveloped virus-antibody structures), 2) two structurally characterized non-enveloped virus epitopes which evolved slowly (out of eight non-enveloped virus-antibody structures), and 3) eight preexisting epitope and peptide discovery algorithms. Rationale for a new benchmarking scheme is presented. A data-driven epitope clustering algorithm is introduced. The prediction of five Zika virus epitopes (for future exploration on recombinant vaccine technologies) is demonstrated. For the first time, protein flexibility is shown to outperform solvent accessible surface area as an epitope discovery metric.

Funding: PJO Grant #: UL1 TR001108 the National Institutes of Health, National Center for Advancing Translational Sciences, Clinical and Translational Sciences Award https://ncats.nih.gov/ctsa NO Indiana University Grant #: CNS-0521433 National Science Foundation https://www.nsf.gov/ NO This research was supported in part by Lilly Endowment, Inc., through its support for the Indiana University Pervasive Technology Institute. NO This work was supported in part by Shared University Research grants from IBM, Inc., to Indiana University. NO.

This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Here, previous studies of in silico immunology [ 16 , 20 ] are extended by evaluating an algorithm for conserved epitope discovery, based on protein flexibility–as measured via root-mean-square fluctuation (RMSF) of isolated protein and virus-like particle (VLP) protein residues. The method is developed with flaviviruses simulated via MD. The approach is validated against 1) seven structurally characterized flavivirus epitopes (from thirty-nine flavivirus-antibody structures) with the lowest phylogeny-based evolutionary rates (described by Ashkenazy, H., et al. (2016) [ 25 ] as the rate at which a structurally aligned residue changes over a phylogenic tree of proteins with shared ancestry), 2) two structurally characterized human papillomavirus (HPV) epitopes (from eight HPV-antibody structures) with low phylogeny-based evolutionary rates, and 3) eight preexisting epitope and peptide discovery algorithms [ 5 ]. To enhance the epitope dataset (for the prediction of currently uncharacterized ZIKV epitopes), epitopes from seven flaviviruses are structurally aligned. Using 1) a new (data-driven) clustering algorithm, 2) a new epitope organizational model, 3) a new epitope discovery performance benchmarking scheme (which addresses bias in previous methods), and 4) a new epitope discovery benchmark dataset–all presented here for the first time–the prediction of five ZIKV epitopes (which provide starting points for future presentation on recombinant vaccine technologies) is demonstrated. Physical insights identified here 1) supply context for understanding (seemingly contradictory) previous reports on protein flexibility’s role in the humoral immune response [ 15 , 16 , 20 , 26 ] and 2) shed new light on immunologically relevant distinctions between clinically relevant epitope subsets. Notably, for the first time [ 26 , 27 ], protein flexibility is shown to outperform solvent accessible surface area as an epitope discovery metric.

In addition to the limitations (within the field) which have already been noted (e.g. a scarcity of flexibility-based epitope discovery metrics), structure-based methods for the discovery of conserved epitopes (epitopes which evolve the least across closely related pathogens) have yet to be developed. Because highly conserved epitopes (by definition) generalize across many pathogens, highly conserved epitopes are of especially high value as antigenic targets. Ineffectiveness of current vaccine technologies in eliciting antibodies able to bind a diverse set of closely related pathogens has been a challenge in vaccine design [ 21 , 22 ]. Multivalent, live-attenuated vaccines have been introduced to solve the complications mentioned above; however, simultaneous vaccine-based display of related pathogen epitopes has resulted in unbalanced prophylactic protection–suggesting new approaches are needed [ 23 ]. One promising, new approach is the presentation (or display) of conserved epitopes on recombinant vaccines [ 24 ].

Although challenges still exist, recent advancements within the field of all-atom molecular dynamics simulation (MD) have opened up new opportunities to enhance our atomic level understanding of protein flexibility (within the context of the immune response) [ 17 ]. Recent MD investigations into multi-million atom VLP systems (like HIV-1 [ 18 ], satellite tobacco mosaic virus (STMV) [ 19 ], and human papillomavirus (HPV) [ 16 , 20 ]) show quantification of full pathogen structural dynamics 1) is possible and 2) can provide new insights into antibody-antigen interaction physics.

B-cell epitopes are localities of antigens targeted by the humoral immune response, via antibodies and B-cell receptors, to protect the extracellular space (e.g. the blood plasma) [ 1 ]. Molecules which effectively mimic B-cell epitopes are vaccines [ 2 – 4 ]. Consequently, structure-based B-cell epitope discovery has emerged as a promising foundational step in rational vaccine design [ 5 , 6 ]. Despite promise, 1) ambiguity surrounding the definition of an epitope, 2) limitations of current performance benchmarking approaches, 3) a scarcity of benchmark datasets, and 4) an overabundance of solvent accessible surface area-based metrics suggest there is ample room for improvement within the field. For example, while some enveloped virus [ 7 ] epitopes (like those of the Zika virus [ 8 ] (ZIKV)) [ 9 – 11 ] have been studied, a comprehensive, quantitative, uniform, and structure-based epitope analysis of a clinically relevant enveloped virus (like ZIKV) has yet to be explored. Likewise, 1) “cryptic” epitopes hidden within virus structures, [ 12 ] 2) pathogen morphological diversity, [ 13 ] 3) full pathogen structural dynamics, [ 14 ] and 4) possible links between protein flexibility and immunogenicity [ 15 , 16 ] suggest an overreliance on solvent accessible surface area-based epitope discovery metrics [ 5 ] may be a major oversight within the field, especially when it comes to highly flexible, clinically relevant antigens (like ZIKV).

Results/Discussion

[END]
---
[1] Url: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0262321

Published and (C) by PLOS One
Content appears here under this condition or license: Creative Commons - Attribution BY 4.0.

via Magical.Fish Gopher News Feeds:
gopher://magical.fish/1/feeds/news/plosone/

You are viewing proxied material from magical.fish. The copyright of proxied material belongs to its original authors. Any comments or complaints in relation to proxied material should be directed to the original authors of the content concerned. Please see the disclaimer for more details.