A structure-based engineering approach to abrogate pre-existing antibody binding to biotherapeutics

Immunogenicity risk assessment and mitigation for engineered antibody and protein therapeutics

Remarkable progress has been made in recent decades in engineering antibodies and other protein therapeutics, including enhancements to existing functions as well as the advent of novel molecules that confer biological activities previously unknown in nature. These protein therapeutics have brought major benefits to patients across multiple areas of medicine. One major ongoing challenge is that protein therapeutics can elicit unwanted immune responses (immunogenicity) in treated patients, including the generation of anti-drug antibodies. In rare and unpredictable cases, anti-drug antibodies can seriously compromise therapeutic safety and/or efficacy. Systematic deconvolution of this immunogenicity problem is confounded by the complexity of its many contributing factors and the inherent limitations of available experimental and computational methods. Nevertheless, continued progress with the assessment and mitigation of immunogenicity risk at the preclinical stage has the potential to reduce the incidence and severity of clinical immunogenicity events. This Review focuses on identifying key unsolved anti-drug antibody-related challenges and offers some pragmatic approaches towards addressing them. Examples are drawn mainly from antibodies, given that the majority of available clinical data are from this class of protein therapeutics. Plausible and seemingly tractable solutions are in sight for some immunogenicity problems, whereas other challenges will likely require completely new approaches.

On the humanization of VHHs: Prospective case studies, experimental and computational characterization of structural determinants for functionality

The humanization of camelid-derived variable domain heavy chain antibodies (VHHs) poses challenges including immunogenicity, stability, and potential reduction of affinity. Critical to this process are complementarity-determining regions (CDRs), Vernier and Hallmark residues, shaping the three-dimensional fold and influencing VHH structure and function. Additionally, the presence of non-canonical disulfide bonds further contributes to conformational stability and antigen binding. In this study, we systematically humanized two camelid-derived VHHs targeting the natural cytotoxicity receptor NKp30. Key structural positions in Vernier and Hallmark regions were exchanged with residues from the most similar human germline sequences. The resulting variants were characterized for binding affinities, yield, and purity. Structural binding modes were elucidated through crystal structure determination and AlphaFold2 predictions, providing insights into differences in binding affinity. Comparative structural and molecular dynamics characterizations of selected variants were performed to rationalize their functional properties and elucidate the role of specific sequence motifs in antigen binding. Furthermore, systematic analyses of next-generation sequencing (NGS) and Protein Data Bank (PDB) data was conducted, shedding light on the functional significance of Hallmark motifs and non-canonical disulfide bonds in VHHs in general. Overall, this study provides valuable insights into the structural determinants governing the functional properties of VHHs, offering a roadmap for their rational design, humanization, and optimization for therapeutic applications.

Discovery of nanobodies: a comprehensive review of their applications and potential over the past five years

Nanobodies (Nbs) are antibody fragments derived from heavy-chain-only IgG antibodies found in the Camelidae family as well as cartilaginous fish. Their unique structural and functional properties, such as their small size, the ability to be engineered for high antigen-binding affinity, stability under extreme conditions, and ease of production, have made them promising tools for diagnostics and therapeutics. This potential was realized in 2018 with the approval of caplacizumab, the world's first Nb-based drug. Currently, Nbs are being investigated in clinical trials for a broad range of treatments, including targeted therapies against PDL1 and Epidermal Growth Factor Receptor (EGFR), cardiovascular diseases, inflammatory conditions, and neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. They are also being studied for their potential for detecting and imaging autoimmune conditions and infectious diseases such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A variety of methods are now available to generate target-specific Nbs quickly and efficiently at low costs, increasing their accessibility. This article examines these diverse applications of Nbs and their promising roles. Only the most recent articles published in the last five years have been used to summarize the most advanced developments in the field.

Nonclinical immunogenicity risk assessment for knobs-into-holes bispecific IgG1 antibodies

Bispecific antibodies, including bispecific IgG, are emerging as an important new class of antibody therapeutics. As a result, we, as well as others, have developed engineering strategies designed to facilitate the efficient production of bispecific IgG for clinical development. For example, we have extensively used knobs-into-holes (KIH) mutations to facilitate the heterodimerization of antibody heavy chains and more recently Fab mutations to promote cognate heavy/light chain pairing for efficient in vivo assembly of bispecific IgG in single host cells. A panel of related monospecific and bispecific IgG1 antibodies was constructed and assessed for immunogenicity risk by comparison with benchmark antibodies with known low (Avastin and Herceptin) or high (bococizumab and ATR-107) clinical incidence of anti-drug antibodies. Assay methods used include dendritic cell internalization, T cell proliferation, and T cell epitope identification by in silico prediction and MHC-associated peptide proteomics. Data from each method were considered independently and then together for an overall integrated immunogenicity risk assessment. In toto, these data suggest that the KIH mutations and in vitro assembly of half antibodies do not represent a major risk for immunogenicity of bispecific IgG1, nor do the Fab mutations used for efficient in vivo assembly of bispecifics in single host cells. Comparable or slightly higher immunogenicity risk assessment data were obtained for research-grade preparations of trastuzumab and bevacizumab versus Herceptin and Avastin, respectively. These data provide experimental support for the common practice of using research-grade preparations of IgG1 as surrogates for immunogenicity risk assessment of their corresponding pharmaceutical counterparts.

T and B cell epitope analysis for the immunogenicity evaluation and mitigation of antibody-based therapeutics

The surge in the clinical use of therapeutic antibodies has reshaped the landscape of pharmaceutical therapy for many diseases, including rare and challenging conditions. However, the administration of exogenous biologics could potentially trigger unwanted immune responses such as generation of anti-drug antibodies (ADAs). Real-world experiences have illuminated the clear correlation between the ADA occurrence and unsatisfactory therapeutic outcomes as well as immune-related adverse events. By retrospectively examining research involving immunogenicity analysis, we noticed the growing emphasis on elucidating the immunogenic epitope profiles of antibody-based therapeutics aiming for mechanistic understanding the immunogenicity generation and, ideally, mitigating the risks. As such, we have comprehensively summarized here the progress in both experimental and computational methodologies for the characterization of T and B cell epitopes of therapeutics. Furthermore, the successful practice of epitope-driven deimmunization of biotherapeutics is exceptionally highlighted in this article.

Applications and challenges in designing VHH-based bispecific antibodies: leveraging machine learning solutions

The development of bispecific antibodies that bind at least two different targets relies on bringing together multiple binding domains with different binding properties and biophysical characteristics to produce a drug-like therapeutic. These building blocks play an important role in the overall quality of the molecule and can influence many important aspects from potency and specificity to stability and half-life. Single-domain antibodies, particularly camelid-derived variable heavy domain of heavy chain (VHH) antibodies, are becoming an increasingly popular choice for bispecific construction due to their single-domain modularity, favorable biophysical properties, and potential to work in multiple antibody formats. Here, we review the use of VHH domains as building blocks in the construction of multispecific antibodies and the challenges in creating optimized molecules. In addition to exploring traditional approaches to VHH development, we review the integration of machine learning techniques at various stages of the process. Specifically, the utilization of machine learning for structural prediction, lead identification, lead optimization, and humanization of VHH antibodies.

A library approach for the de novo high-throughput isolation of humanized VHH domains with favorable developability properties following camelid immunization

In this study, we generated a novel library approach for high throughput de novo identification of humanized single-domain antibodies following camelid immunization. To achieve this, VHH-derived complementarity-determining regions-3 (CDR3s) obtained from an immunized llama (Lama glama) were grafted onto humanized VHH backbones comprising moderately sequence-diversified CDR1 and CDR2 regions similar to natural immunized and naïve antibody repertoires. Importantly, these CDRs were tailored toward favorable in silico developability properties, by considering human-likeness as well as excluding potential sequence liabilities and predicted immunogenic motifs. Target-specific humanized single-domain antibodies (sdAbs) were readily obtained by yeast surface display. We demonstrate that, by exploiting this approach, high affinity sdAbs with an optimized in silico developability profile can be generated. These sdAbs display favorable biophysical, biochemical, and functional attributes and do not require any further sequence optimization. This approach is generally applicable to any antigen upon camelid immunization and has the potential to significantly accelerate candidate selection and reduce risks and attrition rates in sdAb development.

Immunogenicity assessment of bispecific antibody-based immunotherapy in oncology

With increasing numbers of bispecific antibodies (BsAbs) and multispecific products entering the clinic, recent data highlight immunogenicity as an emerging challenge in the development of such novel biologics. This review focuses on the immunogenicity risk assessment (IgRA) of BsAb-based immunotherapies for cancer, highlighting several risk factors that need to be considered. These include the novel scaffolds consisting of bioengineered sequences, the potentially synergistic immunomodulating mechanisms of action (MOAs) from different domains of the BsAb, as well as several other product-related and patient-related factors. In addition, the clinical relevance of anti-drug antibodies (ADAs) against selected BsAbs developed as anticancer agents is reviewed and the advances in our knowledge of tools and strategies for immunogenicity prediction, monitoring, and mitigation are discussed. It is critical to implement a drug-specific IgRA during the early development stage to guide ADA monitoring and risk management strategies. This IgRA may include a combination of several assessment tools to identify drug-specific risks as well as a proactive risk mitigation approach for candidate or format selection during the preclinical stage. The IgRA is an on-going process throughout clinical development. IgRA during the clinical stage may bridge the gap between preclinical immunogenicity prediction and clinical immunogenicity, and retrospectively guide optimization efforts for next-generation BsAbs. This iterative process throughout development may improve the reliability of the IgRA and enable the implementation of effective risk mitigation strategies, laying the foundation for improved clinical success.

VHH Structural Modelling Approaches: A Critical Review

VHH, i.e., VH domains of camelid single-chain antibodies, are very promising therapeutic agents due to their significant physicochemical advantages compared to classical mammalian antibodies. The number of experimentally solved VHH structures has significantly improved recently, which is of great help, because it offers the ability to directly work on 3D structures to humanise or improve them. Unfortunately, most VHHs do not have 3D structures. Thus, it is essential to find alternative ways to get structural information. The methods of structure prediction from the primary amino acid sequence appear essential to bypass this limitation. This review presents the most extensive overview of structure prediction methods applied for the 3D modelling of a given VHH sequence (a total of 21). Besides the historical overview, it aims at showing how model software programs have been shaping the structural predictions of VHHs. A brief explanation of each methodology is supplied, and pertinent examples of their usage are provided. Finally, we present a structure prediction case study of a recently solved VHH structure. According to some recent studies and the present analysis, AlphaFold 2 and NanoNet appear to be the best tools to predict a structural model of VHH from its sequence.