Engineering the Fab fragment of the anti-IgE omalizumab to prevent Fab crystallization and permit IgE-Fc complex crystallization

Isolation and functional analysis of phage-displayed antibody fragments targeting the staphylococcal superantigen-like proteins

Staphylococcus aureus produces numerous virulence factors that manipulate the immune system, helping the bacteria avoid phagocytosis. In this study, we are investigating three immune evasion molecules called the staphylococcal superantigen-like proteins 1, 5, and 10 (SSL1, SSL5, and SSL10). All three SSLs inhibit vital host immune processes and contribute to S. aureus immune evasion. This study aimed to identify single-chain variable fragment (scFvs) antibodies from synthetic antibody phage libraries, which can recognize either of the three SSLs and could block the interaction between the SSLs and their respective human targets. The antibodies were isolated after three rounds of panning against SSL1, SSL5, and SSL10, and their ability to bind to the SSLs was studied using a time-resolved fluorescence-based immunoassay. We successfully obtained altogether 44 unique clones displaying binding activity to either SSL1, SSL5, or SSL10. The capability of the SSL-recognizing scFvs to inhibit the SSLs' function was tested in an MMP9 enzymatic activity assay, a P-selectin glycoprotein ligand 1 competitive binding assay, and an IgG1-mediated phagocytosis assay. We could show that one scFv was able to inhibit SSL1 and maintain MMP9 activity in a concentration-dependent manner. Finally, the structure of this inhibiting scFv was modeled and used to create putative scFv-SSL1-complex models by protein-protein docking. The complex models were subjected to a 100-ns molecular dynamics simulation to assess the possible binding mode of the antibody.

Hallucinating structure-conditioned antibody libraries for target-specific binders

Antibodies are widely developed and used as therapeutics to treat cancer, infectious disease, and inflammation. During development, initial leads routinely undergo additional engineering to increase their target affinity. Experimental methods for affinity maturation are expensive, laborious, and time-consuming and rarely allow the efficient exploration of the relevant design space. Deep learning (DL) models are transforming the field of protein engineering and design. While several DL-based protein design methods have shown promise, the antibody design problem is distinct, and specialized models for antibody design are desirable. Inspired by hallucination frameworks that leverage accurate structure prediction DL models, we propose the F_vHallucinator for designing antibody sequences, especially the CDR loops, conditioned on an antibody structure. Such a strategy generates targeted CDR libraries that retain the conformation of the binder and thereby the mode of binding to the epitope on the antigen. On a benchmark set of 60 antibodies, F_vHallucinator generates sequences resembling natural CDRs and recapitulates perplexity of canonical CDR clusters. Furthermore, the F_vHallucinator designs amino acid substitutions at the V_H-V_L interface that are enriched in human antibody repertoires and therapeutic antibodies. We propose a pipeline that screens F_vHallucinator designs to obtain a library enriched in binders for an antigen of interest. We apply this pipeline to the CDR H3 of the Trastuzumab-HER2 complex to generate in silico designs predicted to improve upon the binding affinity and interfacial properties of the original antibody. Thus, the F_vHallucinator pipeline enables generation of inexpensive, diverse, and targeted antibody libraries enriched in binders for antibody affinity maturation.

Directed evolution of and structural insights into antibody-mediated disruption of a stable receptor-ligand complex

Antibody drugs exert therapeutic effects via a range of mechanisms, including competitive inhibition, allosteric modulation, and immune effector mechanisms. Facilitated dissociation is an additional mechanism where antibody-mediated “disruption” of stable high-affinity macromolecular complexes can potentially enhance therapeutic efficacy. However, this mechanism is not well understood or utilized therapeutically. Here, we investigate and engineer the weak disruptive activity of an existing therapeutic antibody, omalizumab, which targets IgE antibodies to block the allergic response. We develop a yeast display approach to select for and engineer antibody disruptive efficiency and generate potent omalizumab variants that dissociate receptor-bound IgE. We determine a low resolution cryo-EM structure of a transient disruption intermediate containing the IgE-Fc, its partially dissociated receptor and an antibody inhibitor. Our results provide a conceptual framework for engineering disruptive inhibitors for other targets, insights into the failure in clinical trials of the previous high affinity omalizumab HAE variant and anti-IgE antibodies that safely and rapidly disarm allergic effector cells.

Facilitated dissociation is a mechanism where antibody-mediated disruption of high-affinity complexes can enhance the therapeutic effects of a drug. Here the authors present a yeast display approach to select and engineer omalizumab variants that dissociate receptor-bound IgE to accelerate its inhibition of the allergic response.