Public Baseline and shared response structures support the theory of antibody repertoire functional commonality

Abstract

The naïve antibody/B-cell receptor (BCR) repertoires of different individuals ought to exhibit significant functional commonality, given that most pathogens trigger an effective antibody response to immunodominant epitopes. Sequence-based repertoire analysis has so far offered little evidence for this phenomenon. For example, a recent study estimated the number of shared (‘public’) antibody clonotypes in circulating baseline repertoires to be around 0.02% across ten unrelated individuals. However, to engage the same epitope, antibodies only require a similar binding site structure and the presence of key paratope interactions, which can occur even when their sequences are dissimilar. Here, we search for evidence of geometric similarity/convergence across human antibody repertoires. We first structurally profile naïve (‘baseline’) antibody diversity using snapshots from 41 unrelated individuals, predicting all modellable distinct structures within each repertoire. This analysis uncovers a high (much greater than random) degree of structural commonality. For instance, around 3% of distinct structures are common to the ten most diverse individual samples (‘Public Baseline’ structures). Our approach is the first computational method to find levels of BCR commonality commensurate with epitope immunodominance and could therefore be harnessed to find more genetically distant antibodies with same-epitope complementarity. We then apply the same structural profiling approach to repertoire snapshots from three individuals before and after flu vaccination, detecting a convergent structural drift indicative of recognising similar epitopes (‘Public Response’ structures). We show that Antibody Model Libraries derived from Public Baseline and Public Response structures represent a powerful geometric basis set of low-immunogenicity candidates exploitable for general or target-focused therapeutic antibody screening.

Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for real-world antibody specificity prediction

“…Absolut! may be used to investigate to what extent structural information may be important to consider for repertoire-based ML (109,110). Furthermore, these specificity-annotated datasets may be used for deeper investigations into modeling the ensemble specificity of antibody repertoires (111).…”

Epitope profiling using computational structural modelling demonstrated on coronavirus-binding antibodies

“…This is supported by statistical arguments showing the implausability of a purely “random repertoire” for an efficient immune response [ 25 , 27 ]. Epitope immunodominance could be rationalised via the existence of a more ‘public’ set of backbone structures in the BCR repertoire and the concept that BCRs with similar topologies and sufficient chemical complementarity engage the same epitope [ 24 , 25 ].…”

Epitope profiling of coronavirus-binding antibodies using computational structural modelling

“…We used ABodyBuilder (59) to homology model the 2,063 antibody entries in CoV-AbDab with full Fv sequences. This resulted in a total of 1,500 models in which every loop was entirely FREAD-modellable without any need for ab initio loop modelling or backbone adjustment (see Methods); we focus on this subset of models as we have the highest confidence in their accuracy (23,24,59). This represents 72.7% modellability across the set of Fv sequences, a remarkably high percentage relative to recent studies on both healthy and disease-related natural antibody datasets (23,24).…”

“…For a full breakdown of each multiple-occupancy structural cluster, labelled SC0-SC199, see SI Dataset 2. When applied to an entire antibody repertoire, the number of antibodies with similar structures but different functionalities is likely to be significant (24). However, on 'cleaner' datasets such as CoV-AbDab, where every antibody has been shown to bind a coronavirus antigen (and often a particular domain) in vitro, antibodies with similar Fv structures should have a high chance of binding to the same surface region and therefore being complementary to the same epitope, as demonstrated in our analysis of solved structures.…”

“…Levels of functional convergence may in fact be higher than implied even by lenient clonotyping, as antibodies that derive from different lineages can engage the same epitope. The evidence for this phenomenon has been growing over recent years (9,10,(23)(24)(25). For example, solved structures of antibody-antigen complexes reveal pairs of antibodies with different genetic origins but sufficiently similar binding site geometry and paratope similarity that they bind to the same antigen with near-identical binding modes (9,10).…”