NanoBERTa-ASP: predicting nanobody paratope based on a pretrained RoBERTa model.

BACKGROUND: Nanobodies, also known as VHH or single-domain antibodies, are unique antibody fragments derived solely from heavy chains. They offer advantages of small molecules and conventional antibodies, making them promising therapeutics. The paratope is the specific region on an antibody that binds to an antigen. Paratope prediction involves the identification and characterization of the antigen-binding site on an antibody. This process is crucial for understanding the specificity and affinity of antibody-antigen interactions. Various computational methods and experimental approaches have been developed to predict and analyze paratopes, contributing to advancements in antibody engineering, drug development, and immunotherapy. However, existing predictive models trained on traditional antibodies may not be suitable for nanobodies. Additionally, the limited availability of nanobody datasets poses challenges in constructing accurate models. METHODS: To address these challenges, we have developed a novel nanobody prediction model, named NanoBERTa-ASP (Antibody Specificity Prediction), which is specifically designed for predicting nanobody-antigen binding sites. The model adopts a training strategy more suitable for nanobodies, based on an advanced natural language processing (NLP) model called BERT (Bidirectional Encoder Representations from Transformers). To be more specific, the model utilizes a masked language modeling approach named RoBERTa (Robustly Optimized BERT Pretraining Approach) to learn the contextual information of the nanobody sequence and predict its binding site. RESULTS: NanoBERTa-ASP achieved exceptional performance in predicting nanobody binding sites, outperforming existing methods, indicating its proficiency in capturing sequence information specific to nanobodies and accurately identifying their binding sites. Furthermore, NanoBERTa-ASP provides insights into the interaction mechanisms between nanobodies and antigens, contributing to a better understanding of nanobodies and facilitating the design and development of nanobodies with therapeutic potential. CONCLUSION: NanoBERTa-ASP represents a significant advancement in nanobody paratope prediction. Its superior performance highlights the potential of deep learning approaches in nanobody research. By leveraging the increasing volume of nanobody data, NanoBERTa-ASP can further refine its predictions, enhance its performance, and contribute to the development of novel nanobody-based therapeutics. Github repository: https://github.com/WangLabforComputationalBiology/NanoBERTa-ASP.

The rise of big data: deep sequencing-driven computational methods are transforming the landscape of synthetic antibody design.

Synthetic antibodies (Abs) represent a category of artificial proteins capable of closely emulating the functions of natural Abs. Their in vitro production eliminates the need for an immunological response, streamlining the process of Ab discovery, engineering, and development. These artificially engineered Abs offer novel approaches to antigen recognition, paratope site manipulation, and biochemical/biophysical enhancements. As a result, synthetic Abs are fundamentally reshaping conventional methods of Ab production. This mirrors the revolution observed in molecular biology and genomics as a result of deep sequencing, which allows for the swift and cost-effective sequencing of DNA and RNA molecules at scale. Within this framework, deep sequencing has enabled the exploration of whole genomes and transcriptomes, including particular gene segments of interest. Notably, the fusion of synthetic Ab discovery with advanced deep sequencing technologies is redefining the current approaches to Ab design and development. Such combination offers opportunity to exhaustively explore Ab repertoires, fast-tracking the Ab discovery process, and enhancing synthetic Ab engineering. Moreover, advanced computational algorithms have the capacity to effectively mine big data, helping to identify Ab sequence patterns/features hidden within deep sequencing Ab datasets. In this context, these methods can be utilized to predict novel sequence features thereby enabling the successful generation of de novo Ab molecules. Hence, the merging of synthetic Ab design, deep sequencing technologies, and advanced computational models heralds a new chapter in Ab discovery, broadening our comprehension of immunology and streamlining the advancement of biological therapeutics.

Do antibody CDR loops change conformation upon binding?

Antibodies have increasingly been developed as drugs with over 100 now licensed in the US or EU. During development, it is often necessary to increase or reduce the affinity of an antibody and rational attempts to do so rely on having a structure of the antibody-antigen complex often obtained by modeling. The antigen-binding site consists primarily of six loops known as complementarity-determining regions (CDRs), and an open question has been whether these loops change their conformation when they bind to an antigen. Existing surveys of antibody-antigen complex structures have only examined CDR conformational change in case studies or small-scale surveys. With an increasing number of antibodies where both free and complexed structures have been deposited in the Protein Data Bank, a large-scale survey of CDR conformational change during binding is now possible. To this end, we built a dataset, AbAgDb, that currently includes 177 antibodies with high-quality CDRs, each of which has at least one bound and one unbound structure. We analyzed the conformational change of the Cα backbone of each CDR upon binding and found that, in most cases, the CDRs (other than CDR-H3) show minimal movement, while 70.6% and 87% of CDR-H3s showed global Cα RMSD ≤ 1.0Å and ≤ 2.0Å, respectively. We also compared bound CDR conformations with the conformational space of unbound CDRs and found most of the bound conformations are included in the unbound conformational space. In future, our results will contribute to developing insights into antibodies and new methods for modeling and docking.

ThermoPCD: a database of molecular dynamics trajectories of antibody-antigen complexes at physiologic and fever-range temperatures.

Progression of various cancers and autoimmune diseases is associated with changes in systemic or local tissue temperatures, which may impact current therapies. The role of fever and acute inflammation-range temperatures on the stability and activity of antibodies relevant for cancers and autoimmunity is unknown. To produce molecular dynamics (MD) trajectories of immune complexes at relevant temperatures, we used the Research Collaboratory for Structural Bioinformatics (RCSB) database to identify 50 antibody:antigen complexes of interest, in addition to single antibodies and antigens, and deployed Groningen Machine for Chemical Simulations (GROMACS) to prepare and run the structures at different temperatures for 100-500 ns, in single or multiple random seeds. MD trajectories are freely available. Processed data include Protein Data Bank outputs for all files obtained every 50 ns, and free binding energy calculations for some of the immune complexes. Protocols for using the data are also available. Individual datasets contain unique DOIs. We created a web interface, ThermoPCD, as a platform to explore the data. The outputs of ThermoPCD allow the users to relate thermally-dependent changes in epitopes:paratopes interfaces to their free binding energies, or against own experimentally derived binding affinities. ThermoPCD is a free to use database of immune complexes' trajectories at different temperatures that does not require registration and allows for all the data to be available for download. Database URL: https://sites.google.com/view/thermopcd/home.

Impact of antibody architecture and paratope valency on effector functions of bispecific NKp30 x EGFR natural killer cell engagers.

Natural killer (NK) cells emerged as a promising effector population that can be harnessed for anti-tumor therapy. In this work, we constructed NK cell engagers (NKCEs) based on NKp30-targeting single domain antibodies (sdAbs) that redirect the cytotoxic potential of NK cells toward epidermal growth factor receptor (EGFR)-expressing tumor cells. We investigated the impact of crucial parameters such as sdAb location, binding valencies, the targeted epitope on NKp30, and the overall antibody architecture on the redirection capacity. Our study exploited two NKp30-specific sdAbs, one of which binds a similar epitope on NKp30 as its natural ligand B7-H6, while the other sdAb addresses a non-competing epitope. For EGFR-positive tumor targeting, humanized antigen-binding domains of therapeutic antibody cetuximab were used. We demonstrate that NKCEs bivalently targeting EGFR and bivalently engaging NKp30 are superior to monovalent NKCEs in promoting NK cell-mediated tumor cell lysis and that the architecture of the NKCE can substantially influence killing capacities depending on the NKp30-targeting sdAb utilized. While having a pronounced impact on NK cell killing efficacy, the capabilities of triggering antibody-dependent cellular phagocytosis or complement-dependent cytotoxicity were not significantly affected comparing the bivalent IgG-like NKCEs with cetuximab. However, the fusion of sdAbs can have a slight impact on the NK cell release of immunomodulatory cytokines, as well as on the pharmacokinetic profile of the NKCE due to unfavorable spatial orientation within the molecule architecture. Ultimately, our findings reveal novel insights for the engineering of potent NKCEs triggering the NKp30 axis.

Inadequate structural constraint on Fab approach rather than paratope elicitation limits HIV-1 MPER vaccine utility.

Broadly neutralizing antibodies (bnAbs) against HIV-1 target conserved envelope (Env) epitopes to block viral replication. Here, using structural analyses, we provide evidence to explain why a vaccine targeting the membrane-proximal external region (MPER) of HIV-1 elicits antibodies with human bnAb-like paratopes paradoxically unable to bind HIV-1. Unlike in natural infection, vaccination with MPER/liposomes lacks a necessary structure-based constraint to select for antibodies with an adequate approach angle. Consequently, the resulting Abs cannot physically access the MPER crawlspace on the virion surface. By studying naturally arising Abs, we further reveal that flexibility of the human IgG3 hinge mitigates the epitope inaccessibility and additionally facilitates Env spike protein crosslinking. Our results suggest that generation of IgG3 subtype class-switched B cells is a strategy for anti-MPER bnAb induction. Moreover, the findings illustrate the need to incorporate topological features of the target epitope in immunogen design.

Cattle-derived knob paratopes grafted onto peripheral loops of the IgG1 Fc region enable the generation of a novel symmetric bispecific antibody format.

In this work we present a novel symmetric bispecific antibody format based on engraftments of cattle-derived knob paratopes onto peripheral loops of the IgG1 Fc region. For this, knob architectures obtained from bovine ultralong CDR-H3 antibodies were inserted into the AB loop or EF loop of the CH3 domain, enabling the introduction of an artificial binding specificity into an IgG molecule. We demonstrate that inserted knob domains largely retain their binding affinities, resulting into bispecific antibody derivatives versatile for effector cell redirection. Essentially, generated bispecifics demonstrated adequate biophysical properties and were not compromised in their Fc mediated functionalities such as FcRn or FcγRIIIa binding.

Widespread impact of immunoglobulin V-gene allelic polymorphisms on antibody reactivity.

The ability of the human immune system to generate antibodies to any given antigen can be strongly influenced by immunoglobulin V-gene allelic polymorphisms. However, previous studies have provided only limited examples. Therefore, the prevalence of this phenomenon has been unclear. By analyzing >1,000 publicly available antibody-antigen structures, we show that many V-gene allelic polymorphisms in antibody paratopes are determinants for antibody binding activity. Biolayer interferometry experiments further demonstrate that paratope allelic polymorphisms on both heavy and light chains often abolish antibody binding. We also illustrate the importance of minor V-gene allelic polymorphisms with low frequency in several broadly neutralizing antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza virus. Overall, this study not only highlights the pervasive impact of V-gene allelic polymorphisms on antibody binding but also provides mechanistic insights into the variability of antibody repertoires across individuals, which in turn have important implications for vaccine development and antibody discovery.

Antibodies to coagulase of Staphylococcus aureus crossreact to Efb and reveal different binding of shared fibrinogen binding repeats.

Staphylococcus aureus pathology is caused by a plethora of virulence factors able to combat multiple host defence mechanisms. Fibrinogen (Fg), a critical component in the host coagulation cascade, plays an important role in the pathogenesis of this bacterium, as it is the target of numerous staphylococcal virulence proteins. Amongst its secreted virulence factors, coagulase (Coa) and Extracellular fibrinogen-binding protein (Efb) share common Fg binding motives and have been described to form a Fg shield around staphylococcal cells, thereby allowing efficient bacterial spreading, phagocytosis escape and evasion of host immune system responses. Targeting these proteins with monoclonal antibodies thus represents a new therapeutic option against S. aureus. To this end, here we report the selection and characterization of fully human, sequence-defined, monoclonal antibodies selected against the C-terminal of coagulase. Given the functional homology between Coa and Efb, we also investigated if the generated antibodies bound the two virulence factors. Thirteen unique antibodies were isolated from naïve antibodies gene libraries by antibody phage display. As anticipated, most of the selected antibodies showed cross-recognition of these two proteins and among them, four were able to block the interaction between Coa/Efb and Fg. Furthermore, our monoclonal antibodies could interact with the two main Fg binding repeats present at the C-terminal of Coa and distinguish them, suggesting the presence of two functionally different Fg-binding epitopes.

Epivolve: A Protocol for Site-Directed Antibodies.

Researchers can often successfully generate antibodies to predicted epitopes. Especially when the epitopes are on the surface of a protein or in a hydrophilic loop. But it is difficult to direct recombinant antibodies to bind either to- or near a specific amino acid on a protein or peptide. We have developed a unique immune-targeting strategy, that we call "Epivolve," that enables us to make site-specific antibodies (Abs). Epivolve technology leverages a highly immunogenic modified amino acid that acts as a "pseudo-hapten" immuno-target and takes advantage of Ab affinity maturation technologies to make high-affinity site-specific antibodies. Epivolve functions by the evolution of an Ab paratope to either synonymous or especially non-synonymous amino acid (aa) binding. Here we describe the use of Epivolve technology in phage display and the protocols for developing site-specific antibodies.

"Redirecting an anti-IL-1ß antibody to bind a new, unrelated and computationally predicted epitope on hIL-17A".

Antibody engineering technology is at the forefront of therapeutic antibody development. The primary goal for engineering a therapeutic antibody is the generation of an antibody with a desired specificity, affinity, function, and developability profile. Mature antibodies are considered antigen specific, which may preclude their use as a starting point for antibody engineering. Here, we explore the plasticity of mature antibodies by engineering novel specificity and function to a pre-selected antibody template. Using a small, focused library, we engineered AAL160, an anti-IL-1ß antibody, to bind the unrelated antigen IL-17A, with the introduction of seven mutations. The final redesigned antibody, 11.003, retains favorable biophysical properties, binds IL-17A with sub-nanomolar affinity, inhibits IL-17A binding to its cognate receptor and is functional in a cell-based assay. The epitope of the engineered antibody can be computationally predicted based on the sequence of the template antibody, as is confirmed by the crystal structure of the 11.003/IL-17A complex. The structures of the 11.003/IL-17A and the AAL160/IL-1ß complexes highlight the contribution of germline residues to the paratopes of both the template and re-designed antibody. This case study suggests that the inherent plasticity of antibodies allows for re-engineering of mature antibodies to new targets, while maintaining desirable developability profiles.

A Paratope-Enhanced Method to Determine Breadth and Depth TCR Clonal Metrics of the Private Human T-Cell Vaccine Response after SARS-CoV-2 Vaccination.

Quantitative metrics for vaccine-induced T-cell responses are an important need for developing correlates of protection and their use in vaccine-based medical management and population health. Molecular TCR analysis is an appealing strategy but currently requires a targeted methodology involving complex integration of ex vivo data (antigen-specific functional T-cell cytokine responses and TCR molecular responses) that uncover only public antigen-specific metrics. Here, we describe an untargeted private TCR method that measures breadth and depth metrics of the T-cell response to vaccine challenge using a simple pre- and post-vaccine subject sampling, TCR immunoseq analysis, and a bioinformatic approach using self-organizing maps and GLIPH2. Among 515 subjects undergoing SARS-CoV-2 mRNA vaccination, we found that breadth and depth metrics were moderately correlated between the targeted public TCR response and untargeted private TCR response methods. The untargeted private TCR method was sufficiently sensitive to distinguish subgroups of potential clinical significance also observed using public TCR methods (the reduced T-cell vaccine response with age and the paradoxically elevated T-cell vaccine response of patients on anti-TNF immunotherapy). These observations suggest the promise of this untargeted private TCR method to produce T-cell vaccine-response metrics in an antigen-agnostic and individual-autonomous context.

Epitopes, paratopes, and other topes 30 years on: Understanding what we are talking about.

The question of which protein antigens, such as HLA class I or class II molecules, will bind, and how well, to a given antibody is often assumed to depend exclusively on the details of protein surface structure. These structures are usually based on static models resulting from X-ray crystallography. While these notions are useful, the ultimate causal factors determining how well a given antigen binds a given antibody are based in thermodynamics and can include atomic mobility and the time-varying conformations of proteins. In this article, fundamental biophysical principles of antibody-antigen interaction are discussed, concepts critical for a deeper understanding of the pertinent molecular phenomena are highlighted, and common misunderstandings are identified and debunked.

Generation and engineering of potent single domain antibody-based bispecific IL-18 mimetics resistant to IL-18BP decoy receptor inhibition.

Here, we generated bispecific antibody (bsAb) derivatives that mimic the function of interleukin (IL)-18 based on single domain antibodies (sdAbs) specific to IL-18 Rα and IL-18 Rß. For this, camelids were immunized, followed by yeast surface display (YSD)-enabled discovery of VHHs targeting the individual receptor subunits. Upon reformatting into a strictly monovalent (1 + 1) bispecific sdAb architecture, several bsAbs triggered dose-dependent IL-18 R downstream signaling on IL-18 reporter cells, as well as IFN-γ release by peripheral blood mononuclear cells in the presence of low-dose IL-12. However, compared with IL-18, potencies and efficacies were considerably attenuated. By engineering paratope valencies and the spatial orientation of individual paratopes within the overall design architecture, we were able to generate IL-18 mimetics displaying significantly augmented functionalities, resulting in bispecific cytokine mimetics that were more potent than IL-18 in triggering proinflammatory cytokine release. Furthermore, generated IL-18 mimetics were unaffected from inhibition by IL-18 binding protein decoy receptor. Essentially, we demonstrate that this strategy enables the generation of IL-18 mimetics with tailor-made cytokine functionalities.

Experimentally Observed Conformational Changes in Antibodies Due to Binding and Paratope-epitope Asymmetries.

Understanding binding related changes in antibody conformations is important for epitope prediction and antibody refinement. The increase of available data in the PDB allowed a more detailed investigation of the conformational landscape for free and bound antibodies. A dataset containing a total of 835 unique PDB entries of antibodies that were crystallized in complex with their antigen and in a free state was constructed. It was examined for binding related conformation changes. We present further evidence supporting the theory of a pre-existing-equilibrium in experimental data. Multiple sequence alignments did not show binding induced tendencies in the solvent accessibility of residues in any specific position. Evaluating the changes in solvent accessibility per residue revealed a certain binding induced increase for several amino acids. Antibody-antigen interaction statistics were established and quantify a significant directional asymmetry between many interacting antibody and antigen residue pairs, especially a richness in tyrosine in the antibody epitope compared to its paratope. This asymmetry could potentially facilitate an increase in the success rate of computationally guided antibody refinement.

Understanding the complementarity and plasticity of antibody-antigen interfaces.

MOTIVATION: While antibodies have been ground-breaking therapeutic agents, the structural determinants for antibody binding specificity remain to be fully elucidated, which is compounded by the virtually unlimited repertoire of antigens they can recognize. Here, we have explored the structural landscapes of antibody-antigen interfaces to identify the structural determinants driving target recognition by assessing concavity and interatomic interactions. RESULTS: We found that complementarity-determining regions utilized deeper concavity with their longer H3 loops, especially H3 loops of nanobody showing the deepest use of concavity. Of all amino acid residues found in complementarity-determining regions, tryptophan used deeper concavity, especially in nanobodies, making it suitable for leveraging concave antigen surfaces. Similarly, antigens utilized arginine to bind to deeper pockets of the antibody surface. Our findings fill a gap in knowledge about the antibody specificity, binding affinity, and the nature of antibody-antigen interface features, which will lead to a better understanding of how antibodies can be more effective to target druggable sites on antigen surfaces. AVAILABILITY AND IMPLEMENTATION: The data and scripts are available at: https://github.com/YoochanMyung/scripts.

Cross-linking disulfide bonds govern solution structures of diabodies.

In the last years, antibodies have emerged as a promising new class of therapeutics, due to their combination of high specificity with long serum half-life and low risk of side-effects. Diabodies are a popular novel antibody format, consisting of two Fv domains connected with short linkers. Like IgG antibodies, they simultaneously bind two target proteins. However, they offer altered properties, given their smaller size and higher rigidity. In this study, we conducted the-to our knowledge-first molecular dynamics (MD) simulations of diabodies and find a surprisingly high conformational flexibility in the relative orientation of the two Fv domains. We observe rigidifying effects through the introduction of disulfide bonds in the Fv -Fv interface and characterize the effect of different disulfide bond locations on the conformation. Additionally, we compare VH -VL orientations and paratope dynamics between diabodies and an antigen binding fragment (Fab) of the same sequence. We find mostly consistent structures and dynamics, indicating similar antigen binding properties. The most significant differences can be found within the CDR-H2 loop dynamics. Of all CDR loops, the CDR-H2 is located closest to the artificial Fv -Fv interface. All examined diabodies show similar VH -VL orientations, Fv -Fv packing and CDR loop conformations. However, the variant with a P14C-K64C disulfide bond differs most from the Fab in our measures, including the CDR-H3 loop conformational ensemble. This suggests altered antigen binding properties and underlines the need for careful validation of the disulfide bond locations in diabodies.

Viral Capsid, Antibody, and Receptor Interactions: Experimental Analysis of the Antibody Escape Evolution of Canine Parvovirus.

Canine parvovirus (CPV) is a small nonenveloped single-stranded DNA virus that causes serious diseases in dogs worldwide. The original strain of the virus (CPV-2) emerged in dogs during the late 1970s due to a host range switch of a virus similar to the feline panleukopenia virus that infected another host. The virus that emerged in dogs had altered capsid receptor and antibody binding sites, with some changes affecting both functions. Further receptor and antibody binding changes arose when the virus became better adapted to dogs or to other hosts. Here, we used in vitro selection and deep sequencing to reveal how two antibodies with known interactions select for escape mutations in CPV. The antibodies bound two distinct epitopes, and one largely overlapped the host receptor binding site. We also generated mutated antibody variants with altered binding structures. Viruses were passaged with wild-type (WT) or mutated antibodies, and their genomes were deep sequenced during the selective process. A small number of mutations were detected only within the capsid protein gene during the first few passages of selection, and most sites remained polymorphic or were slow to go to fixation. Mutations arose both within and outside the antibody binding footprints on the capsids, and all avoided the transferrin receptor type 1 binding footprint. Many selected mutations matched those that have arisen in the natural evolution of the virus. The patterns observed reveal the mechanisms by which these variants have been selected in nature and provide a better understanding of the interactions between antibody and receptor selections. IMPORTANCE Antibodies protect animals against infection by many different viruses and other pathogens, and we are gaining new information about the epitopes that induce antibody responses against viruses and the structures of the bound antibodies. However, less is known about the processes of antibody selection and antigenic escape and the constraints that apply in this system. Here, we used an in vitro model system and deep genome sequencing to reveal the mutations that arose in the virus genome during selection by each of two monoclonal antibodies or their mutated variants. High-resolution structures of each of the Fab:capsid complexes revealed their binding interactions. The wild-type antibodies or their mutated variants allowed us to examine how changes in antibody structure influence the mutational selection patterns seen in the virus. The results shed light on the processes of antibody binding, neutralization escape, and receptor binding, and they likely have parallels for many other viruses.

Unveiling CD59-Antibody Interactions to Design Paratope-Mimicking Peptides for Complement Modulation.

CD59 is an abundant immuno-regulatory human protein that protects cells from damage by inhibiting the complement system. CD59 inhibits the assembly of the Membrane Attack Complex (MAC), the bactericidal pore-forming toxin of the innate immune system. In addition, several pathogenic viruses, including HIV-1, escape complement-mediated virolysis by incorporating this complement inhibitor in their own viral envelope. This makes human pathogenic viruses, such as HIV-1, not neutralised by the complement in human fluids. CD59 is also overexpressed in several cancer cells to resist the complement attack. Consistent with its importance as a therapeutical target, CD59-targeting antibodies have been proven to be successful in hindering HIV-1 growth and counteracting the effect of complement inhibition by specific cancer cells. In this work, we make use of bioinformatics and computational tools to identify CD59 interactions with blocking antibodies and to describe molecular details of the paratope-epitope interface. Based on this information, we design and produce paratope-mimicking bicyclic peptides able to target CD59. Our results set the basis for the development of antibody-mimicking small molecules targeting CD59 with potential therapeutic interest as complement activators.

A novel brick for bispecific antibody construction.

In recent years, the development of bispecific antibodies (bsAbs) has become a major trend in the biopharmaceutical industry. By simultaneously engaging two molecular targets, bsAbs have exhibited unique mechanisms of action that could lead to clinical benefits unattainable by conventional monoclonal antibodies. The type of structure used to construct a bsAb directly influences the distance, angle, degree of freedom, and affinity between the two antibody binding sites and the interaction between the two antigens or the cells where the antigens are located, which have been bound by the antibody. Consequently, the structure of the bsAb is one of the most vital factors affecting its function. Herein, we reported for the first time a novel basic module bsAb format, VFV (Variable domain-Fab-Variable domain). And then, the feasibility of the VFV format was demonstrated by constructing a series of engager-like basic module bsAbs. Next, a series of VFV bsAbs containing Fc (VFV-Ig), Fab (VFV-Fab), or Hinge (VFV-Hinge) were developed based on Hxb module, and all of them had adequate purity and activity. Finally, a T cell engager bsAb with the potential to overcome on-target off-tumor activity was constructed according to the structural characteristics of VFV, which validated that the VFV module can be used as a new brick for the construction of various bsAbs. In a word, the successful construction of this bsAb format for the first time not only enriches the arsenal of the bsAb format, but also provides inspiration for the construction of new bsAbs. Nevertheless, we are fully aware that as a proof-of-concept study, this paper has many shortcomings, and there is still a lot of work to be done to determine whether VFV can serve as a platform for drug development.