Monoclonal antibodies are being developed as therapeutics to complement drugs and vaccines or to fill the gap where no drugs or vaccines exist. These therapeutic antibodies (ThAb) may be especially important for infectious diseases in which there is antibiotic resistance, toxin-mediated pathogenesis, or for emerging pathogens. The unique structure of antibodies determines the specific nature of the effector function, so when developing ThAb, the desired effector functions need to be considered and integrated into the design and development processes to ensure maximum efficacy and safety. Antibody subclass is a critical consideration, but it is noteworthy that almost all ThAb that are licenced or currently in development utilise an IgG1 backbone. This review outlines the major structural properties that vary across subclasses, how these properties affect functional immunity, and discusses the various approaches used to study subclass responses to infectious diseases. We also review the factors associated with the selection of antibody subclasses when designing ThAb and highlight circumstances where different subclass properties might be beneficial when applied to particular infectious diseases. These approaches are critical to the future design of ThAb and to the study of naturally-acquired and vaccine-induced immunity.

Malaria remains a significant global health burden. The development of an effective malaria vaccine remains as a major challenge with the potential to significantly reduce morbidity and mortality. While Plasmodium spp. have been shown to contain a large number of intrinsically disordered proteins (IDPs) or disordered protein regions, the relationship of protein structure to subcellular localisation and adaptive immune responses remains unclear. In this study, we employed several computational prediction algorithms to identify IDPs at the proteome level of six Plasmodium spp. and to investigate the potential impact of protein disorder on adaptive immunity against P. falciparum parasites. IDPs were shown to be particularly enriched within nuclear proteins, apical proteins, exported proteins and proteins localised to the parasitophorous vacuole. Furthermore, several leading vaccine candidates, and proteins with known roles in host-cell invasion, have extensive regions of disorder. Presentation of peptides by MHC molecules plays an important role in adaptive immune responses, and we show that IDP regions are predicted to contain relatively few MHC class I and II binding peptides owing to inherent differences in amino acid composition compared to structured domains. In contrast, linear B-cell epitopes were predicted to be enriched in IDPs. Tandem repeat regions and non-synonymous single nucleotide polymorphisms were found to be strongly associated with regions of disorder. In summary, immune responses against IDPs appear to have characteristics distinct from those against structured protein domains, with increased antibody recognition of linear epitopes but some constraints for MHC presentation and issues of polymorphisms. These findings have major implications for vaccine design, and understanding immunity to malaria.

Humoral immune responses against the malaria parasite are an important component of a protective immune response. Antibodies are often directed towards conformational epitopes, and the native structure of the antigenic region is usually critical for antibody recognition. We examined the structural features of various Plasmodium antigens that may impact on epitope location, by performing a comprehensive analysis of known and modelled structures from P. falciparum. Examining the location of known polymorphisms over all available structures, we observed a strong propensity for polymorphic residues to be exposed on the surface and to occur in particular secondary structure segments such as hydrogen-bonded turns. We also utilised established prediction algorithms for B-cell epitopes and MHC class II binding peptides, examining predicted epitopes in relation to known polymorphic sites within structured regions. Finally, we used the available structures to examine polymorphic hotspots and Tajima’s D values using a spatial averaging approach. We identified a region of PfAMA1 involving both domains II and III under a high degree of balancing selection relative to the rest of the protein. In summary, we developed general methods for examining how sequence-based features relate to one another in three-dimensional space and applied these methods to key P. falciparum antigens.

BackgroundPlasmodium vivax is a significant contributor to the global malaria burden, and a vaccine targeting vivax malaria is urgently needed. An understanding of the targets of functional immune responses during the course of natural infection will aid in the development of a vaccine. Antibodies play a key role in this process, with responses against particular epitopes leading to immune selection pressure on these epitopes. A number of techniques exist to estimate levels of immune selection pressure on particular epitopes, with a sliding window analysis often used to determine particular regions likely to be under immune pressure. However, such analysis neglects protein three-dimensional structural information. With this in mind, a newly developed tool, BioStructMap, was applied to two key antigens from Plasmodium vivax: PvAMA1 and PvDBP Region II. This tool incorporates structural information into tests of selection pressure.ResultsSequences from a number of populations were analysed, examining spatially-derived nucleotide diversity and Tajima’s D over protein structures for PvAMA1 and PvDBP. Structural patterns of nucleotide diversity were similar across all populations examined, with Domain I of PvAMA1 having the highest nucleotide diversity and displaying significant signatures of immune selection pressure (Tajima’s D > 0). Nucleotide diversity for PvDBP was highest bordering the dimerization and DARC-binding interface, although there was less evidence of immune selection pressure on PvDBP compared with PvAMA1. This study supports previous work that has identified Domain I as the main target of immune-mediated selection pressure for PvAMA1, and also supports studies that have identified functional epitopes within PvDBP Region II.ConclusionsThe BioStructMap tool was applied to leading vaccine candidates from P. vivax, to examine structural patterns of selection and diversity across a number of geographic populations. There were striking similarities in structural patterns of diversity across multiple populations. Furthermore, whilst regions of high diversity tended to surround conserved binding interfaces, a number of protein regions with very low diversity were also identified, and these may be useful targets for further vaccine development, given previous evidence of functional antibody responses against these regions.Electronic supplementary materialThe online version of this article (10.1186/s12936-018-2324-3) contains supplementary material, which is available to authorized users.

Findings suggest that naturally acquired binding-inhibitory antibodies are an important functional mechanism that contributes to protection against malaria and further supports the potential of EBA-175 as a vaccine candidate. Identifying vaccines and approaches that induce potent binding-inhibitory antibodies may be a valuable strategy in the development of highly efficacious malaria vaccines.

SummaryA sliding window analysis over a protein or genomic sequence is commonly performed, and we present a Python tool, BioStructMap, that extends this concept to three-dimensional (3D) space, allowing the application of a 3D sliding window analysis over a protein structure. BioStructMap is easily extensible, allowing the user to apply custom functions to spatially aggregated data. BioStructMap also allows mapping of underlying genomic sequences to protein structures, allowing the user to perform genetic-based analysis over spatially linked codons—this has applications when selection pressures arise at the level of protein structure.Availability and implementationThe Python BioStructMap package is available at https://github.com/andrewguy/biostructmap and released under the MIT License. An online server implementing standard functionality is available at https://biostructmap.burnet.edu.au.Supplementary information Supplementary data are available at Bioinformatics online.

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