The optimization of therapeutic antibodies through traditional techniques, such as candidate screening via hybridoma or phage display, is resource-intensive and time-consuming. In recent years, computational and artificial intelligence-based methods have been actively developed to accelerate and improve the development of therapeutic antibodies. In this study, we developed an end-to-end sequence-based deep learning model, termed AttABseq, for the predictions of the antigen-antibody binding affinity changes connected with antibody mutations. AttABseq is a highly efficient and generic attention-based model by utilizing diverse antigen-antibody complex sequences as the input to predict the binding affinity changes of residue mutations. The assessment on the three benchmark datasets illustrates that AttABseq is 120% more accurate than other sequence-based models in terms of the Pearson correlation coefficient between the predicted and experimental binding affinity changes. Moreover, AttABseq also either outperforms or competes favorably with the structure-based approaches. Furthermore, AttABseq consistently demonstrates robust predictive capabilities across a diverse array of conditions, underscoring its remarkable capacity for generalization across a wide spectrum of antigen-antibody complexes. It imposes no constraints on the quantity of altered residues, rendering it particularly applicable in scenarios where crystallographic structures remain unavailable. The attention-based interpretability analysis indicates that the causal effects of point mutations on antibody-antigen binding affinity changes can be visualized at the residue level, which might assist automated antibody sequence optimization. We believe that AttABseq provides a fiercely competitive answer to therapeutic antibody optimization.

The underlying contribution of immune complexes in modulating adaptive immunity in mucosal tissues remains poorly understood. In this report, we examined, in mice, the proinflammatory response elicited by intranasal delivery of the biothreat agent ricin toxin (RT) in association with two toxin-neutralizing mAbs, SylH3 and PB10. We previously demonstrated that ricin-immune complexes (RICs) induce the rapid onset of high-titer toxin-neutralizing Abs that persist for months. We now demonstrate that such responses are dependent on CD4+ T cell help, because treatment of mice with an anti-CD4 mAb abrogated the onset of RT-specific Abs following intranasal RICs exposure. To define the inflammatory environment associated with RIC exposure, we collected bronchoalveolar lavage fluid (BALF) and sera from mice 6, 12, and 18 h after they had received RT or RICs by the intranasal route. A 32-plex cytometric bead array revealed an inflammatory profile elicited by RT that was dominated by IL-6 (>1500-fold increase in BALF) and secondarily by KC (CXCL1), G-CSF, GM-CSF, and MCP-1. RICs induced inflammatory profiles in both BALF and serum response that were similar to RT, albeit at markedly reduced levels. These results demonstrate that RICs retain the capacity to induce local and systemic inflammatory cytokines/chemokines that, in turn, may influence Ag sampling and presentation in the lung mucosa and draining lymph nodes. A better understanding of the fate of immune complexes following intranasal delivery has implications for the development of mucosal vaccines for biothreats and emerging infectious diseases.

Although antibody-mediated lung damage is a major factor in transfusion-related acute lung injury (ALI), autoimmune lung disease (for example, coatomer subunit α [COPA] syndrome), and primary graft dysfunction following lung transplantation, the mechanism by which antigen-antibody complexes activate complement to induce lung damage remains unclear. In this issue of the JCI, Cleary and colleagues utilized several approaches to demonstrate that IgG forms hexamers with MHC class I alloantibodies. This hexamerization served as a key pathophysiological mechanism in alloimmune lung injury models and was mediated through the classical pathway of complement activation. Additionally, the authors provided avenues for exploring therapeutics for this currently hard-to-treat clinical entity that has several etiologies but a potentially focused mechanism.

Antibodies play a central role in the adaptive immune response of vertebrates through the specific recognition of exogenous or endogenous antigens. The rational design of antibodies has a wide range of biotechnological and medical applications, such as in disease diagnosis and treatment. However, there are currently no reliable methods for predicting the antibodies that recognize a specific antigen region (or epitope) and, conversely, epitopes that recognize the binding region of a given antibody (or paratope). To fill this gap, we developed ImaPEp, a machine learning-based tool for predicting the binding probability of paratope-epitope pairs, where the epitope and paratope patches were simplified into interacting two-dimensional patches, which were colored according to the values of selected features, and pixelated. The specific recognition of an epitope image by a paratope image was achieved by using a convolutional neural network-based model, which was trained on a set of two-dimensional paratope-epitope images derived from experimental structures of antibody-antigen complexes. Our method achieves good performances in terms of cross-validation with a balanced accuracy of 0.8. Finally, we showcase examples of application of ImaPep, including extensive screening of large libraries to identify paratope candidates that bind to a selected epitope, and rescoring and refining antibody-antigen docking poses.

In patients with immune thrombotic thrombocytopenic purpura (iTTP), autoantibodies against the metalloprotease ADAMTS13 lead to catastrophic microvascular thrombosis. However, the potential benefits of recombinant human ADAMTS13 (rADAMTS13) in patients with iTTP remain unknown. Here, we report the clinical use of rADAMTS13, which resulted in the rapid suppression of disease activity and complete recovery in a critically ill patient whose condition had proved to be refractory to all available treatments. We also show that rADAMTS13 causes immune complex formation, which saturates the autoantibody and may promote its clearance. Our data support the role of rADAMTS13 as a novel adjunctive therapy in patients with iTTP.

The classical complement pathway is activated by antigen-bound IgG antibodies. Monomeric IgG must oligomerize to activate complement via the hexameric C1q complex, and hexamerizing mutants of IgG appear as promising therapeutic candidates. However, structural data have shown that it is not necessary to bind all six C1q arms to initiate complement, revealing a symmetry mismatch between C1 and the hexameric IgG complex that has not been adequately explained. Here, we use DNA nanotechnology to produce specific nanostructures to template antigens and thereby spatially control IgG valency. These DNA-nanotemplated IgG complexes can activate complement on cell-mimetic lipid membranes, which enabled us to determine the effect of IgG valency on complement activation without the requirement to mutate antibodies. We investigated this using biophysical assays together with 3D cryo-electron tomography. Our data revealed the importance of interantigen distance on antibody-mediated complement activation, and that the cleavage of complement component C4 by the C1 complex is proportional to the number of ideally spaced antigens. Increased IgG valency also translated to better terminal pathway activation and membrane attack complex formation. Together, these data provide insights into how nanopatterning antigen-antibody complexes influence the activation of the C1 complex and suggest routes to modulate complement activation by antibody engineering. Furthermore, to our knowledge, this is the first time DNA nanotechnology has been used to study the activation of the complement system.

Covalent labeling in combination with mass spectrometry is a powerful approach used in structural biology to study protein structures, interactions, and dynamics. Recently, the toolbox of covalent labeling techniques has been expanded with fast fluoroalkylation of proteins (FFAP). FFAP is a novel radical labeling method that utilizes fluoroalkyl radicals generated from hypervalent Togni reagents for targeting aromatic residues. This report further demonstrates the benefits of FFAP as a new method for structural characterization of therapeutic antibodies and interaction interfaces of antigen-antibody complexes. The results obtained from human trastuzumab and its complex with human epidermal growth factor receptor 2 (HER2) correlate well with previously published structural data and demonstrate the potential of FFAP in structural biology.

Visceral leishmaniasis (VL) is an infectious disease caused by Leishmania infantum. Clinically, VL evolves with systemic impairment, immunosuppression and hyperactivation with hypergammaglobulinemia. Although renal involvement has been recognized, a dearth of understanding about the underlying mechanisms driving acute kidney injury (AKI) in VL remains. We aimed to evaluate the involvement of immunoglobulins (Igs) and immune complexes (CIC) in the occurrence of AKI in VL patients. Fourteen VL patients were evaluated between early treatment and 12 months post-treatment (mpt). Anti-Leishmania Igs, CIC, cystatin C, C3a and C5a were assessed and correlated with AKI markers. Interestingly, high levels of CIC were observed in VL patients up to 6 mpt. Concomitantly, twelve patients met the criteria for AKI, while high levels of cystatin C were observed up to 6 mpt. Plasmatic cystatin C was positively correlated with CIC and Igs. Moreover, C5a was correlated with cystatin C, CIC and Igs. We did not identify any correlation between amphotericin B use and kidney function markers in VL patients, although this association needs to be further explored in subsequent studies. Our data reinforce the presence of an important renal function impairment during VL, suggesting the involvement of Igs, CIC, and C5a in this clinical condition.

Most host-microbiota interactions occur within the intestinal barrier, which is essential for separating the intestinal epithelium from toxins, microorganisms, and antigens in the gut lumen. Gut inflammation allows pathogenic bacteria to enter the blood stream, forming immune complexes which may deposit on organs. Despite increased circulating immune complexes (CICs) in patients with inflammatory bowel disease (IBD) and discussions among IBD experts regarding their potential pathogenic role in extra-intestinal manifestations, this phenomenon is overlooked because definitive evidence demonstrating CIC-induced extra-intestinal manifestations in IBD animal models is lacking. However, clinical observations of elevated CICs in newly diagnosed, untreated patients with IBD have reignited research into their potential pathogenic implications. Musculoskeletal symptoms are the most prevalent extra-intestinal IBD manifestations. CICs are pivotal in various arthritis forms, including reactive, rheumatoid, and Lyme arthritis and systemic lupus erythematosus. Research indicates that intestinal barrier restoration during the pre-phase of arthritis could inhibit arthritis development. In the absence of animal models supporting extra-intestinal IBD manifestations, this paper aims to comprehensively explore the relationship between CICs and arthritis onset via a multifaceted analysis to offer a fresh perspective for further investigation and provide novel insights into the interplay between CICs and arthritis development in IBD.

The function of immune complexes in rheumatoid arthritis (RA) is related to their composition and size. Using dynamic light scattering (DLS), we investigated the link between the RA circulating immune complex (CIC) particles\' size and the CIC immunoglobulin level. In this study, 30 RA patients and 30 healthy individuals were included. IgA, IgG, and IgM were found in all analyzed CICs, but more IgA and IgG were found in RA than in control CICs. In both control and RA CICs, DLS detected 50 particles that differed in size and clustered around two size groups: with a 7.5-164 nm radius and with a 342-1718 nm radius. An increased level of IgA in RA CICs, compared to control ones, was associated with more than 50% of CIC particles. In RA, compared to the control, a higher number of CICs with 28.2 nm, 531 nm, 712 nm, and 1718 nm particles and a lower number of CICs with 78.8 nm particles were detected. This particle distribution pattern did not reflect the changes in the CIC immunoglobulin level. Thus, RA elevated CIC IgA was linked with all these particles (except the 1718 nm particle), the IgM increase was linked with 43.8 nm and 712 nm particles, and the IgG increase was linked with the 712 nm particle only. This study provides the very first data on the association between CIC particles\' size, CIC immunoglobulin level, and RA. It opens the possibility that the size of CICs determined by DLS can be used as a criterion in RA diagnosis or monitoring after a large-scale study confirmation.