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/).

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.

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).

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.

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.

Five computational developability guidelines for therapeutic antibody profiling.

Therapeutic mAbs must not only bind to their target but must also be free from "developability issues" such as poor stability or high levels of aggregation. While small-molecule drug discovery benefits from Lipinski's rule of five to guide the selection of molecules with appropriate biophysical properties, there is currently no in silico analog for antibody design. Here, we model the variable domain structures of a large set of post-phase-I clinical-stage antibody therapeutics (CSTs) and calculate in silico metrics to estimate their typical properties. In each case, we contextualize the CST distribution against a snapshot of the human antibody gene repertoire. We describe guideline values for five metrics thought to be implicated in poor developability: the total length of the complementarity-determining regions (CDRs), the extent and magnitude of surface hydrophobicity, positive charge and negative charge in the CDRs, and asymmetry in the net heavy- and light-chain surface charges. The guideline cutoffs for each property were derived from the values seen in CSTs, and a flagging system is proposed to identify nonconforming candidates. On two mAb drug discovery sets, we were able to selectively highlight sequences with developability issues. We make available the Therapeutic Antibody Profiler (TAP), a computational tool that builds downloadable homology models of variable domain sequences, tests them against our five developability guidelines, and reports potential sequence liabilities and canonical forms. TAP is freely available at opig.stats.ox.ac.uk/webapps/sabdab-sabpred/TAP.php.

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.

Hapten-directed spontaneous disulfide shuffling: a universal technology for site-directed covalent coupling of payloads to antibodies.

Humanized hapten-binding IgGs were designed with an accessible cysteine close to their binding pockets, for specific covalent payload attachment. Individual analyses of known structures of digoxigenin (Dig)- and fluorescein (Fluo) binding antibodies and a new structure of a biotin (Biot)-binder, revealed a "universal" coupling position (52(+2)) in proximity to binding pockets but without contributing to hapten interactions. Payloads that carry a free thiol are positioned on the antibody and covalently linked to it via disulfides. Covalent coupling is achieved and driven toward complete (95-100%) payload occupancy by spontaneous redox shuffling between antibody and payload. Attachment at the universal position works with different haptens, antibodies, and payloads. Examples are the haptens Fluo, Dig, and Biot combined with various fluorescent or peptidic payloads. Disulfide-bonded covalent antibody-payload complexes do not dissociate in vitro and in vivo. Coupling requires the designed cysteine and matching payload thiol because payload or antibody without the Cys/thiol are not linked (<5% nonspecific coupling). Hapten-mediated positioning is necessary as hapten-thiol-payload is only coupled to antibodies that bind matching haptens. Covalent complexes are more stable in vivo than noncovalent counterparts because digoxigeninylated or biotinylated fluorescent payloads without disulfide-linkage are cleared more rapidly in mice (approximately 50% reduced 48 hour serum levels) compared with their covalently linked counterparts. The coupling technology is applicable to many haptens and hapten binding antibodies (confirmed by automated analyses of the structures of 140 additional hapten binding antibodies) and can be applied to modulate the pharmacokinetics of small compounds or peptides. It is also suitable to link payloads in a reduction-releasable manner to tumor- or tissue-targeting delivery vehicles.

Prediction of VH-VL domain orientation for antibody variable domain modeling.

The antigen-binding site of antibodies forms at the interface of their two variable domains, VH and VL, making VH-VL domain orientation a factor that codetermines antibody specificity and affinity. Preserving VH-VL domain orientation in the process of antibody engineering is important in order to retain the original antibody properties, and predicting the correct VH-VL orientation has also been recognized as an important factor in antibody homology modeling. In this article, we present a fast sequence-based predictor that predicts VH-VL domain orientation with Q(2) values ranging from 0.54 to 0.73 on the evaluation set. We describe VH-VL orientation in terms of the six absolute ABangle parameters that have recently been proposed as a means to separate the different degrees of freedom of VH-VL domain orientation. In order to assess the impact of adjusting VH-VL orientation according to our predictions, we use the set of antibody structures of the recently published Antibody Modeling Assessment (AMA) II study. In comparison to the original AMAII homology models, we find an improvement in the accuracy of VH-VL orientation modeling, which also translates into an improvement in the average root-mean-square deviation with regard to the crystal structures.

Rapid quantification of digitoxin and its metabolites using differential ion mobility spectrometry-tandem mass spectrometry.

This study focuses on the quantitative analysis of the cardiac glycoside drug digitoxin and its three main metabolites digitoxigenin-bisdigitoxose, digitoxigenin-monodigitoxose, and digitoxigenin using electrospray ionization-differential ion mobility spectrometry-tandem mass spectrometry (ESI-DMS-MS/MS). Despite large molecular weight differences, gas-phase separation of the four compounds in the DMS drift cell was not possible, even by utilizing additional volatile chemical modifiers. Baseline separation was achieved after adduct formation with alkali metal ions, however, and efficiency was shown to improve with increasing size of the alkali ion, reaching optimum conditions for the largest cesium ion. Subsequently, an assay was developed for quantification of digitoxin and its metabolites from human serum samples and its analytical performance assessed in a series of proof-of-concept experiments. The method was applied to spiked human serum pools with concentration levels between 2 and 80 ng/mL. After a short reversed-phase chromatographic step for desalting the sample, rapid DMS separation of the analytes was carried out, resulting in a total run time of less than 1.5 min. The instrumental method showed good repeatability; the calculated coefficients of variation ranged from 2% to 13%.

Peptide-polymer ligands for a tandem WW-domain, an adaptive multivalent protein-protein interaction: lessons on the thermodynamic fitness of flexible ligands.

Three polymers, poly(N-(2-hydroxypropyl)methacrylamide) (pHPMA), hyperbranched polyglycerol (hPG), and dextran were investigated as carriers for multivalent ligands targeting the adaptive tandem WW-domain of formin-binding protein (FBP21). Polymer carriers were conjugated with 3-9 copies of the proline-rich decapeptide GPPPRGPPPR-NH2 (P1). Binding of the obtained peptide-polymer conjugates to the tandem WW-domain was investigated employing isothermal titration calorimetry (ITC) to determine the binding affinity, the enthalpic and entropic contributions to free binding energy, and the stoichiometry of binding for all peptide-polymer conjugates. Binding affinities of all multivalent ligands were in the µM range, strongly amplified compared to the monovalent ligand P1 with a K D > 1 mM. In addition, concise differences were observed, pHPMA and hPG carriers showed moderate affinity and bound 2.3-2.8 peptides per protein binding site resulting in the formation of aggregates. Dextran-based conjugates displayed affinities down to 1.2 µM, forming complexes with low stoichiometry, and no precipitation. Experimental results were compared with parameters obtained from molecular dynamics simulations in order to understand the observed differences between the three carrier materials. In summary, the more rigid and condensed peptide-polymer conjugates based on the dextran scaffold seem to be superior to induce multivalent binding and to increase affinity, while the more flexible and dendritic polymers, pHPMA and hPG are suitable to induce crosslinking upon binding.

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.

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 ).

Quantifying the rebinding effect in multivalent chemical ligand-receptor systems.

Multivalent ligand-receptor systems often show an enhancement in binding compared to the constituent monovalent systems. This "cooperativity effect" is often attributed to the favorable spatial preorganisation of the ligands by the connecting spacer that leads to a reduction of entropy loss at ligand binding. A different factor that has been proposed to contribute to the cooperativity effect is "rebinding": As soon as a single ligand-receptor complex dissociates, the presence of another ligand "on coat-tails" will increase the probability of another binding event, which in turn will drive the system to a state where all ligands are bound. In this article, we derive a first quantitative description of the rebinding effect. In order to model the inherent memory effect of a spacer-connected system, we pursue a mathematical approach based on Markov state models and conformation dynamics. The theoretical investigations are illustrated by studying different prototypic ligand-receptor systems.

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.

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.

Conformational analysis of bivalent estrogen receptor ligands: from intramolecular to intermolecular binding.

The estrogen receptor binding affinities of bivalent raloxifene ligands tethered by flexible spacers of different lengths have been evaluated in vitro. Two bivalent binding modes, intra- and intermolecular, were hypothesized to explain their different binding properties. The binding affinities of these bivalent ligands in an aqueous environment are influenced by their conformations, which can be determined by 2D NMR and UV spectral methods. Moreover, computer modeling and simulations were performed to explain the binding modes of these bivalent ligands and to estimate the conformational entropy difference between their unbound and bound states. It was found that bivalent ligands tethered by long spacers had weaker binding affinities because of the shielding of the binding moieties that results from their folded conformations; those tethered by short spacers had stronger affinities because they exposed their ligands to the receptor.

Towards a rational spacer design for bivalent inhibition of estrogen receptor.

Estrogen receptors are known drug targets that have been linked to several kinds of cancer. The structure of the estrogen receptor ligand binding domain is available and reveals a homodimeric layout. In order to improve the binding affinity of known estrogen receptor inhibitors, bivalent compounds have been developed that consist of two individual ligands linked by flexible tethers serving as spacers. So far, binding affinities of the bivalent compounds do not surpass their monovalent counterparts. In this article, we focus our attention on the molecular spacers that are used to connect the individual ligands to form bivalent compounds, and describe their thermodynamic contribution during the ligand binding process. We use computational methods to predict structural and entropic parameters of different spacer structures. We find that flexible spacers introduce a number of effects that may interfere with ligand binding and possibly can be connected to the low binding affinities that have been reported in binding assays. Based on these findings, we try to provide guidelines for the design of novel molecular spacers.