The physiological interactome of TCR-like antibody therapeutics in human tissues.

Selective binding of TCR-like antibodies that target a single tumour-specific peptide antigen presented by human leukocyte antigens (HLA) is the absolute prerequisite for their therapeutic suitability and patient safety. To date, selectivity assessment has been limited to peptide library screening and predictive modeling. We developed an experimental platform to de novo identify interactomes of TCR-like antibodies directly in human tissues using mass spectrometry. As proof of concept, we confirm the target epitope of a MAGE-A4-specific TCR-like antibody. We further determine cross-reactive peptide sequences for ESK1, a TCR-like antibody with known off-target activity, in human liver tissue. We confirm off-target-induced T cell activation and ESK1-mediated liver spheroid killing. Off-target sequences feature an amino acid motif that allows a structural groove-coordination mimicking that of the target peptide, therefore allowing the interaction with the engager molecule. We conclude that our strategy offers an accurate, scalable route for evaluating the non-clinical safety profile of TCR-like antibody therapeutics prior to first-in-human clinical application.

The Patent and Literature Antibody Database (PLAbDab): an evolving reference set of functionally diverse, literature-annotated antibody sequences and structures.

Antibodies are key proteins of the adaptive immune system, and there exists a large body of academic literature and patents dedicated to their study and concomitant conversion into therapeutics, diagnostics, or reagents. These documents often contain extensive functional characterisations of the sets of antibodies they describe. However, leveraging these heterogeneous reports, for example to offer insights into the properties of query antibodies of interest, is currently challenging as there is no central repository through which this wide corpus can be mined by sequence or structure. Here, we present PLAbDab (the Patent and Literature Antibody Database), a self-updating repository containing over 150,000 paired antibody sequences and 3D structural models, of which over 65 000 are unique. We describe the methods used to extract, filter, pair, and model the antibodies in PLAbDab, and showcase how PLAbDab can be searched by sequence, structure, or keyword. PLAbDab uses include annotating query antibodies with potential antigen information from similar entries, analysing structural models of existing antibodies to identify modifications that could improve their properties, and facilitating the compilation of bespoke datasets of antibody sequences/structures that bind to a specific antigen. PLAbDab is freely available via Github (https://github.com/oxpig/PLAbDab) and as a searchable webserver (https://opig.stats.ox.ac.uk/webapps/plabdab/).

ImmuneBuilder: Deep-Learning models for predicting the structures of immune proteins.

Immune receptor proteins play a key role in the immune system and have shown great promise as biotherapeutics. The structure of these proteins is critical for understanding their antigen binding properties. Here, we present ImmuneBuilder, a set of deep learning models trained to accurately predict the structure of antibodies (ABodyBuilder2), nanobodies (NanoBodyBuilder2) and T-Cell receptors (TCRBuilder2). We show that ImmuneBuilder generates structures with state of the art accuracy while being far faster than AlphaFold2. For example, on a benchmark of 34 recently solved antibodies, ABodyBuilder2 predicts CDR-H3 loops with an RMSD of 2.81Å, a 0.09Å improvement over AlphaFold-Multimer, while being over a hundred times faster. Similar results are also achieved for nanobodies, (NanoBodyBuilder2 predicts CDR-H3 loops with an average RMSD of 2.89Å, a 0.55Å improvement over AlphaFold2) and TCRs. By predicting an ensemble of structures, ImmuneBuilder also gives an error estimate for every residue in its final prediction. ImmuneBuilder is made freely available, both to download ( https://github.com/oxpig/ImmuneBuilder ) and to use via our webserver ( http://opig.stats.ox.ac.uk/webapps/newsabdab/sabpred ). We also make available structural models for ~150 thousand non-redundant paired antibody sequences ( https://doi.org/10.5281/zenodo.7258553 ).

Structural mechanism of Fab domain dissociation as a measure of interface stability.

Therapeutic antibodies should not only recognize antigens specifically, but also need to be free from developability issues, such as poor stability. Thus, the mechanistic understanding and characterization of stability are critical determinants for rational antibody design. In this study, we use molecular dynamics simulations to investigate the melting process of 16 antigen binding fragments (Fabs). We describe the Fab dissociation mechanisms, showing a separation in the VH-VL and in the CH1-CL domains. We found that the depths of the minima in the free energy curve, corresponding to the bound states, correlate with the experimentally determined melting temperatures. Additionally, we provide a detailed structural description of the dissociation mechanism and identify key interactions in the CDR loops and in the CH1-CL interface that contribute to stabilization. The dissociation of the VH-VL or CH1-CL domains can be represented by conformational changes in the bend angles between the domains. Our findings elucidate the melting process of antigen binding fragments and highlight critical residues in both the variable and constant domains, which are also strongly germline dependent. Thus, our proposed mechanisms have broad implications in the development and design of new and more stable antigen binding fragments.

Bispecific antibodies-effects of point mutations on CH3-CH3 interface stability.

A new format of therapeutic proteins is bispecific antibodies, in which two different heavy chains heterodimerize to obtain two different binding sites. Therefore, it is crucial to understand and optimize the third constant domain (CH3-CH3) interface to favor heterodimerization over homodimerization, and to preserve the physicochemical properties, as thermal stability. Here, we use molecular dynamics simulations to investigate the dissociation process of 19 CH3-CH3 crystal structures that differ from each other in few point mutations. We describe the dissociation of the dimeric interface as a two-steps mechanism. As confirmed by a Markov state model, apart from the bound and the dissociated state, we observe an additional intermediate state, which corresponds to an encounter complex. The analysis of the interdomain contacts reveals key residues that stabilize the interface. We expect that our results will improve the understanding of the CH3-CH3 interface interactions and thus advance the developability and design of new antibodies formats.

Corrigendum: Comparing Antibody Interfaces to Inform Rational Design of New Antibody Formats.

[This corrects the article DOI: 10.3389/fmolb.2022.812750.].

Comparing Antibody Interfaces to Inform Rational Design of New Antibody Formats.

As the current biotherapeutic market is dominated by antibodies, the design of different antibody formats, like bispecific antibodies and other new formats, represent a key component in advancing antibody therapy. When designing new formats, a targeted modulation of pairing preferences is key. Several existing approaches are successful, but expanding the repertoire of design possibilities would be desirable. Cognate immunoglobulin G antibodies depend on homodimerization of the fragment crystallizable regions of two identical heavy chains. By modifying the dimeric interface of the third constant domain (CH3-CH3), with different mutations on each domain, the engineered Fc fragments form rather heterodimers than homodimers. The first constant domain (CH1-CL) shares a very similar fold and interdomain orientation with the CH3-CH3 dimer. Thus, numerous well-established design efforts for CH3-CH3 interfaces, have also been applied to CH1-CL dimers to reduce the number of mispairings in the Fabs. Given the high structural similarity of the CH3-CH3 and CH1-CL domains we want to identify additional opportunities in comparing the differences and overlapping interaction profiles. Our vision is to facilitate a toolkit that allows for the interchangeable usage of different design tools from crosslinking the knowledge between these two interface types. As a starting point, here, we use classical molecular dynamics simulations to identify differences of the CH3-CH3 and CH1-CL interfaces and already find unexpected features of these interfaces shedding new light on possible design variations. Apart from identifying clear differences between the similar CH3-CH3 and CH1-CL dimers, we structurally characterize the effects of point-mutations in the CH3-CH3 interface on the respective dynamics and interface interaction patterns. Thus, this study has broad implications in the field of antibody engineering as it provides a structural and mechanistical understanding of antibody interfaces and thereby presents a crucial aspect for the design of bispecific antibodies.

ABlooper: fast accurate antibody CDR loop structure prediction with accuracy estimation.

MOTIVATION: Antibodies are a key component of the immune system and have been extensively used as biotherapeutics. Accurate knowledge of their structure is central to understanding their antigen-binding function. The key area for antigen binding and the main area of structural variation in antibodies are concentrated in the six complementarity determining regions (CDRs), with the most important for binding and most variable being the CDR-H3 loop. The sequence and structural variability of CDR-H3 make it particularly challenging to model. Recently deep learning methods have offered a step change in our ability to predict protein structures. RESULTS: In this work, we present ABlooper, an end-to-end equivariant deep learning-based CDR loop structure prediction tool. ABlooper rapidly predicts the structure of CDR loops with high accuracy and provides a confidence estimate for each of its predictions. On the models of the Rosetta Antibody Benchmark, ABlooper makes predictions with an average CDR-H3 RMSD of 2.49 Å, which drops to 2.05 Å when considering only its 75% most confident predictions. AVAILABILITY AND IMPLEMENTATION: https://github.com/oxpig/ABlooper. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Protein engineering of a stable and potent anti-inflammatory IL-37-Fc fusion with enhanced therapeutic potential.

Harnessing the immunomodulatory activity of cytokines is a focus of therapies targeting inflammatory disease. The interleukin (IL)-1 superfamily contains pro-inflammatory and anti-inflammatory members that help orchestrate the immune response in adaptive and innate immunity. Of these molecules, IL-37 has robust anti-inflammatory activity across a range of disease models through inhibition of pro-inflammatory signaling cascades downstream of tumor necrosis factor, IL-1, and toll-like receptor pathways. We find that IL-37 is unstable with a poor pharmacokinetic and manufacturing profile. Here, we present the engineering of IL-37 from an unstable cytokine into an anti-inflammatory molecule with an excellent therapeutic likeness. We overcame these shortcomings through site-directed mutagenesis, the addition of a non-native disulfide bond, and the engineering of IL-37 as an Fc-fusion protein. Our results provide a platform for preclinical testing of IL-37 Fc-fusion proteins. The engineering approaches undertaken herein will apply to the conversion of similar potent yet short-acting cytokines into therapeutics.

Germline-Dependent Antibody Paratope States and Pairing Specific VH-VL Interface Dynamics.

Antibodies have emerged as one of the fastest growing classes of biotherapeutic proteins. To improve the rational design of antibodies, we investigate the conformational diversity of 16 different germline combinations, which are composed of 4 different kappa light chains paired with 4 different heavy chains. In this study, we systematically show that different heavy and light chain pairings strongly influence the paratope, interdomain interaction patterns and the relative VH-VL interface orientations. We observe changes in conformational diversity and substantial population shifts of the complementarity determining region (CDR) loops, resulting in distinct dominant solution structures and differently favored canonical structures. Additionally, we identify conformational changes in the structural diversity of the CDR-H3 loop upon different heavy and light chain pairings, as well as upon changes in sequence and structure of the neighboring CDR loops, despite having an identical CDR-H3 loop amino acid sequence. These results can also be transferred to all CDR loops and to the relative VH-VL orientation, as certain paratope states favor distinct interface angle distributions. Furthermore, we directly compare the timescales of sidechain rearrangements with the well-described transition kinetics of conformational changes in the backbone of the CDR loops. We show that sidechain flexibilities are strongly affected by distinct heavy and light chain pairings and decipher germline-specific structural features co-determining stability. These findings reveal that all CDR loops are strongly correlated and that distinct heavy and light chain pairings can result in different paratope states in solution, defined by a characteristic combination of CDR loop conformations and VH-VL interface orientations. Thus, these results have broad implications in the field of antibody engineering, as they clearly show the importance of considering paired heavy and light chains to understand the antibody binding site, which is one of the key aspects in the design of therapeutics.

Targeting intracellular WT1 in AML with a novel RMF-peptide-MHC-specific T-cell bispecific antibody.

Antibody-based immunotherapy is a promising strategy for targeting chemoresistant leukemic cells. However, classical antibody-based approaches are restricted to targeting lineage-specific cell surface antigens. By targeting intracellular antigens, a large number of other leukemia-associated targets would become accessible. In this study, we evaluated a novel T-cell bispecific (TCB) antibody, generated by using CrossMAb and knob-into-holes technology, containing a bivalent T-cell receptor-like binding domain that recognizes the RMFPNAPYL peptide derived from the intracellular tumor antigen Wilms tumor protein (WT1) in the context of HLA-A*02. Binding to CD3ε recruits T cells irrespective of their T-cell receptor specificity. WT1-TCB elicited antibody-mediated T-cell cytotoxicity against AML cell lines in a WT1- and HLA-restricted manner. Specific lysis of primary acute myeloid leukemia (AML) cells was mediated in ex vivo long-term cocultures by using allogeneic (mean ± standard error of the mean [SEM] specific lysis, 67 ± 6% after 13-14 days; n = 18) or autologous, patient-derived T cells (mean ± SEM specific lysis, 54 ± 12% after 11-14 days; n = 8). WT1-TCB-treated T cells exhibited higher cytotoxicity against primary AML cells than an HLA-A*02 RMF-specific T-cell clone. Combining WT1-TCB with the immunomodulatory drug lenalidomide further enhanced antibody-mediated T-cell cytotoxicity against primary AML cells (mean ± SEM specific lysis on days 3-4, 45.4 ± 9.0% vs 70.8 ± 8.3%; P = .015; n = 9-10). In vivo, WT1-TCB-treated humanized mice bearing SKM-1 tumors exhibited a significant and dose-dependent reduction in tumor growth. In summary, we show that WT1-TCB facilitates potent in vitro, ex vivo, and in vivo killing of AML cell lines and primary AML cells; these results led to the initiation of a phase 1 trial in patients with relapsed/refractory AML (#NCT04580121).

Ab-Ligity: identifying sequence-dissimilar antibodies that bind to the same epitope.

Solving the structure of an antibody-antigen complex gives atomic level information of the interactions between an antibody and its antigen, but such structures are expensive and hard to obtain. Alternative experimental sources include epitope mapping and binning experiments, which can be used as a surrogate to identify key interacting residues. However, their resolution is usually not sufficient to identify if two antibodies have identical interactions. Computational approaches to this problem have so far been based on the premise that antibodies with similar sequences behave similarly. Such approaches will fail to identify sequence-distant antibodies that target the same epitope. Here, we present Ab-Ligity, a structure-based similarity measure tailored to antibody-antigen interfaces. Using predicted paratopes on model antibody structures, we assessed its ability to identify those antibodies that target highly similar epitopes. Most antibodies adopting similar binding modes can be identified from sequence similarity alone, using methods such as clonotyping. In the challenging subset of antibodies whose sequences differ significantly, Ab-Ligity is still able to predict antibodies that would bind to highly similar epitopes (precision of 0.95 and recall of 0.69). We compared Ab-Ligity's performance to an existing tool for comparing general protein interfaces, InterComp, and showed improved performance on antibody cases achieved in a substantially reduced time. These results suggest that Ab-Ligity will allow the identification of diverse (sequence-dissimilar) antibodies that bind to the same epitopes from large datasets such as immune repertoires. The tool is available at http://opig.stats.ox.ac.uk/resources.

Surprisingly Fast Interface and Elbow Angle Dynamics of Antigen-Binding Fragments.

Fab consist of a heavy and light chain and can be subdivided into a variable (V H and V L ) and a constant region (C H 1 and C L ). The variable region contains the complementarity-determining region (CDR), which is formed by six hypervariable loops, shaping the antigen binding site, the paratope. Apart from the CDR loops, both the elbow angle and the relative interdomain orientations of the V H -V L and the C H 1-C L domains influence the shape of the paratope. Thus, characterization of the interface and elbow angle dynamics is essential to antigen specificity. We studied nine antigen-binding fragments (Fab) to investigate the influence of affinity maturation, antibody humanization, and different light-chain types on the interface and elbow angle dynamics. While the CDR loops reveal conformational transitions in the micro-to-millisecond timescale, both the interface and elbow angle dynamics occur on the low nanosecond timescale. Upon affinity maturation, we observe a substantial rigidification of the V H and V L interdomain and elbow-angle flexibility, reflected in a narrower and more distinct distribution. Antibody humanization describes the process of grafting non-human CDR loops onto a representative human framework. As the antibody framework changes upon humanization, we investigated if both the interface and the elbow angle distributions are changed or shifted. The results clearly showed a substantial shift in the relative V H -V L distributions upon antibody humanization, indicating that different frameworks favor distinct interface orientations. Additionally, the interface and elbow angle dynamics of five antibody fragments with different light-chain types are included, because of their strong differences in elbow angles. For these five examples, we clearly see a high variability and flexibility in both interface and elbow angle dynamics, highlighting the fact that Fab interface orientations and elbow angles interconvert between each other in the low nanosecond timescale. Understanding how the relative interdomain orientations and the elbow angle influence antigen specificity, affinity, and stability has broad implications in the field of antibody modeling and engineering.

Characterization of the pathoimmunology of necrotizing enterocolitis reveals novel therapeutic opportunities.

Necrotizing enterocolitis (NEC) is a severe, currently untreatable intestinal disease that predominantly affects preterm infants and is driven by poorly characterized inflammatory pathways. Here, human and murine NEC intestines exhibit an unexpected predominance of type 3/TH17 polarization. In murine NEC, pro-inflammatory type 3 NKp46-RORγt+Tbet+ innate lymphoid cells (ILC3) are 5-fold increased, whereas ILC1 and protective NKp46+RORγt+ ILC3 are obliterated. Both species exhibit dysregulation of intestinal TLR repertoires, with TLR4 and TLR8 increased, but TLR5-7 and TLR9-12 reduced. Transgenic IL-37 effectively protects mice from intestinal injury and mortality, whilst exogenous IL-37 is only modestly efficacious. Mechanistically, IL-37 favorably modulates immune homeostasis, TLR repertoires and microbial diversity. Moreover, IL-37 and its receptor IL-1R8 are reduced in human NEC epithelia, and IL-37 is lower in blood monocytes from infants with NEC and/or lower birthweight. Our results on NEC pathomechanisms thus implicate type 3 cytokines, TLRs and IL-37 as potential targets for novel NEC therapies.

CAR-J cells for antibody discovery and lead optimization of TCR-like immunoglobulins.

T-cell bispecific antibodies (TCBs) are a novel class of engineered immunoglobulins that unite monovalent binding to the T-cell receptor (TCR) CD3e chain and bivalent binding to tumor-associated antigens in order to recruit and activate T-cells for tumor cell killing. In vivo, T-cell activation is usually initiated via the interaction of the TCR with the peptide-HLA complex formed by the human leukocyte antigen (HLA) and peptides derived from intracellular proteins. TCR-like antibodies (TCRLs) that recognize pHLA-epitopes extend the target space of TCBs to peptides derived from intracellular proteins, such as those overexpressed during oncogenesis or created via mutations found in cancer. One challenge during lead identification of TCRL-TCBs is to identify TCRLs that specifically, and ideally exclusively, recognize the desired pHLA, but not unrelated pHLAs. In order to identify TCRLs suitable for TCRL-TCBs, large numbers of TCRLs have to be tested in the TCB format. Here, we propose a novel approach using chimeric antigen receptors (CARs) to facilitate the identification of highly selective TCRLs. In this new so-called TCRL-CAR-J approach, TCRL-candidates are transduced as CARs into Jurkat reporter-cells, and subsequently assessed for their specificity profile. This work demonstrates that the CAR-J reporter-cell assay can be applied to predict the profile of TCRL-TCBs without the need to produce each candidate in the final TCB format. It is therefore useful in streamlining the identification of TCRL-TCBs.

Antibodies exhibit multiple paratope states influencing VH-VL domain orientations.

In the last decades, antibodies have emerged as one of the most important and successful classes of biopharmaceuticals. The highest variability and diversity of an antibody is concentrated on six hypervariable loops, also known as complementarity determining regions (CDRs) shaping the antigen-binding site, the paratope. Whereas it was assumed that certain sequences can only adopt a limited set of backbone conformations, in this study we present a kinetic classification of several paratope states in solution. Using molecular dynamics simulations in combination with experimental structural information we capture the involved conformational transitions between different canonical clusters and additional dominant solution structures occurring in the micro-to-millisecond timescale. Furthermore, we observe a strong correlation of CDR loop movements. Another important aspect when characterizing different paratope states is the relative VH/VL orientation and the influence of the distinct CDR loop states on the VH/VL interface. Conformational rearrangements of the CDR loops do not only have an effect on the relative VH/VL orientations, but also influence in some cases the elbow-angle dynamics and shift the respective distributions. Thus, our results show that antibodies exist as several interconverting paratope states, each contributing to the antibody's properties.

The Contorsbody, an antibody format for agonism: Design, structure, and function.

The careful design of the antibody architecture is becoming more and more important, especially when the purpose is agonism. We present the design of a novel antibody format that is able to promote receptor dimerization and induce signal transduction resulting in cell proliferation. Mono-specific bivalent Y-shape IgGs made of two light chains and two heavy chains are engineered into single chain dimers of two modified heavy chains, resulting in the fixation of the two Fab fragments along the Fc dimerizing moiety. By this, an antagonist of the Her-receptor family, Trastuzumab, is re-formatted into an agonist by simply incorporating the original binding motif into a different geometrically and sterically constrained conformation. This novel format, named Contorsbody, retains antigen binding properties of the parental IgGs and can be produced by standard technologies established for recombinant IgGs. Structural analyses using molecular dynamics and electron microscopy are described to guide the initial design and to confirm the Contorsbody as a very compact molecule, respectively. Contorsbodies show increased rigidity compared to IgGs and their Fab moieties are positioned parallel and adjacent to each other. This geometry has an increased potential to trigger cell surface antigen or receptor 'cis'-dimerization without 'trans'-bridging of cells or mere receptor blockade.

VH -VL interdomain dynamics observed by computer simulations and NMR.

The relative orientation of the two variable domains, VH and VL , influences the shape of the antigen binding site, that is, the paratope, and is essential to understand antigen specificity. ABangle characterizes the VH -VL orientation by using five angles and a distance and compares it to other known structures. Molecular dynamics simulations of antibody variable domains (Fvs) reveal fluctuations in the relative domain orientations. The observed dynamics between these domains are confirmed by NMR experiments on a single-chain variable fragment antibody (scFv) in complex with IL-1ß and an antigen-binding fragment (Fab). The variability of these relative domain orientations can be interpreted as a structural feature of antibodies, which increases the antibody repertoire significantly and can enlarge the number of possible binding partners substantially. The movements of the VH and VL domains are well sampled with molecular dynamics simulations and are in agreement with the NMR ensemble. Fast Fourier transformation of the ABangle metrics allows to assign timescales of 0.1-10 GHz to the fastest collective interdomain movements. The results clearly show the necessity of dynamics to understand and characterize the favorable orientations of the VH and VL domains implying a considerable binding interface flexibility and reveal in all antibody fragments (Fab, scFv, and Fv) very similar VH -VL interdomain variations comparable to the distributions observed for known X-ray structures of antibodies. SIGNIFICANCE STATEMENT: Antibodies have become key players as therapeutic agents. The binding ability of antibodies is determined by the antigen-binding fragment (Fab), in particular the variable fragment region (Fv). Antigen-binding is mediated by the complementarity-determining regions consisting of six loops, each three of the heavy and light chain variable domain VH and VL . The relative orientation of the VH and VL domains influences the shape of the antigen-binding site and is a major objective in antibody design. In agreement with NMR experiments and molecular dynamics simulations, we show a considerable binding site flexibility in the low nanosecond timescale. Thus we suggest that this flexibility and its implications for binding and specificity should be considered when designing and optimizing therapeutic antibodies.

Thera-SAbDab: the Therapeutic Structural Antibody Database.

The Therapeutic Structural Antibody Database (Thera-SAbDab; http://opig.stats.ox.ac.uk/webapps/therasabdab) tracks all antibody- and nanobody-related therapeutics recognized by the World Health Organisation (WHO), and identifies any corresponding structures in the Structural Antibody Database (SAbDab) with near-exact or exact variable domain sequence matches. Thera-SAbDab is synchronized with SAbDab to update weekly, reflecting new Protein Data Bank entries and the availability of new sequence data published by the WHO. Each therapeutic summary page lists structural coverage (with links to the appropriate SAbDab entries), alignments showing where any near-matches deviate in sequence, and accompanying metadata, such as intended target and investigated conditions. Thera-SAbDab can be queried by therapeutic name, by a combination of metadata, or by variable domain sequence - returning all therapeutics that are within a specified sequence identity over a specified region of the query. The sequences of all therapeutics listed in Thera-SAbDab (461 unique molecules, as of 5 August 2019) are downloadable as a single file with accompanying metadata.

Back-to-Germline (B2G) Procedure for Antibody Devolution.

Bispecific antibodies (bsAbs) with avidity-enhanced specificity can be used to address target cells with increased specificity, ideally binding efficiently to cells that express two cognate antigens, yet not to cells that express only one of those. Building blocks required to generate such bsAbs are binders that recognize the two antigens with high specificity yet with various (including very low monovalent) affinities. The herein described 'back-to-germline' (B2G) procedure defines such derivatives. It converts parent antibodies with high specificity to derivatives that retain specificity but modulate affinity. The approach defines mutations to be introduced into antibody complementarity-determining regions (CDRs) regions without requiring structures of antibody-antigen complexes. Instead, it reverses the B-cell maturation process that increases affinities, with preference on CDR residues with high antigen contact probability. Placing germline residues at those positions generates VH and VL domains and Fv-combinations thereof that retain specificities but are 'de-matured' to different degrees. De-maturation influences on-rates and off-rates, and can produce entities with extremely low affinity for which binding can only be detected in bivalent formats. A comparison with alanine replacement in CDRs (so far, the most frequently applied technology) indicates that B2G may be more reliable/predictable without introduction of stickiness or poly-reactivity. The applicability for generating sets of affinity-modulated monospecific variants is exemplarily shown for antibodies that bind CD138, Her2/neu, and EGFR.