Effective binding to protein antigens by antibodies from antibody libraries designed with enhanced protein recognition propensities

Prediction of Paratope-Epitope Pairs Using Convolutional Neural Networks

Antibodies play a central role in the adaptive immune response of vertebrates through the specific recognition of exogenous or endogenous antigens. The rational design of antibodies has a wide range of biotechnological and medical applications, such as in disease diagnosis and treatment. However, there are currently no reliable methods for predicting the antibodies that recognize a specific antigen region (or epitope) and, conversely, epitopes that recognize the binding region of a given antibody (or paratope). To fill this gap, we developed ImaPEp, a machine learning-based tool for predicting the binding probability of paratope-epitope pairs, where the epitope and paratope patches were simplified into interacting two-dimensional patches, which were colored according to the values of selected features, and pixelated. The specific recognition of an epitope image by a paratope image was achieved by using a convolutional neural network-based model, which was trained on a set of two-dimensional paratope-epitope images derived from experimental structures of antibody-antigen complexes. Our method achieves good performances in terms of cross-validation with a balanced accuracy of 0.8. Finally, we showcase examples of application of ImaPep, including extensive screening of large libraries to identify paratope candidates that bind to a selected epitope, and rescoring and refining antibody-antigen docking poses.

Significance of antibody numbering systems in the development of antibody engineering

Immunotherapy has become increasingly popular in recent years for treating a variety of diseases including inflammatory, neurological, oncological, and auto-immune disorders. The significant interest in antibody development is due to the high binding affinity and specificity of an antibody against a specific antigen. Recent advances in antibody engineering have provided a different view on how to engineer antibodies in silico for therapeutic and diagnostic applications. In order to improve the clinical utility of therapeutic antibodies, it is of paramount importance to understand the various molecular properties which impact antigen targeting and its potency. In antibody engineering, antibody numbering (AbN) systems play an important role to identify the complementarity determining regions (CDRs) and the framework regions (FR). Hence, it is crucial to accurately define and understand the CDR, FR and the crucial residues of heavy and light chains that aid in the binding of the antibody to the antigenic site. Detailed understanding of amino acids positions are useful for modifying the binding affinity, specificity, physicochemical features, and half-life of an antibody. In this review, we have summarized the different antibody numbering systems that are widely used in antibody engineering and highlighted their significance. Here, we have systematically explored and mentioned the various tools and servers that harness different AbN systems.

Computational Analysis of Antibody Paratopes for Antibody Sequences in Antibody Libraries

To ensure the functionalities of the antibodies in phage-displayed synthetic antibody libraries, we use computational method to evaluate the designs of the antibody libraries. The computational methodologies developed in our lab for designing antibody library provide rich information on the function of the designed antibody sequences-adequate antibody designs for a specific antigen type should have predicted paratopes for the antigen type. This computational assessment of the designed antibody sequences helps eliminate non-functional designs before proceeding to construct the library designs in the wet lab. As such, only reasonable antibody designs are constructed for antibody discoveries.

Antibody CDR amino acids underlying the functionality of antibody repertoires in recognizing diverse protein antigens

Antibodies recognize protein antigens with exquisite specificity in a complex aqueous environment, where interfacial waters are an integral part of the antibody–protein complex interfaces. In this work, we elucidate, with computational analyses, the principles governing the antibodies’ specificity and affinity towards their cognate protein antigens in the presence of explicit interfacial waters. Experimentally, in four model antibody–protein complexes, we compared the contributions of the interaction types in antibody–protein antigen complex interfaces with the antibody variants selected from phage-displayed synthetic antibody libraries. Evidently, the specific interactions involving a subset of aromatic CDR (complementarity determining region) residues largely form the predominant determinant underlying the specificity of the antibody–protein complexes in nature. The interfacial direct/water-mediated hydrogen bonds accompanying the CDR aromatic interactions are optimized locally but contribute little in determining the epitope location. The results provide insights into the phenomenon that natural antibodies with limited sequence and structural variations in an antibody repertoire can recognize seemingly unlimited protein antigens. Our work suggests guidelines in designing functional artificial antibody repertoires with practical applications in developing novel antibody-based therapeutics and diagnostics for treating and preventing human diseases.

Generation of synthetic antibody fragments with optimal complementarity determining region lengths for Notch-1 recognition

Synthetic antibodies have been engineered against a wide variety of antigens with desirable biophysical, biochemical, and pharmacological properties. Here, we describe the generation and characterization of synthetic antigen-binding fragments (Fabs) against Notch-1. Three single-framework synthetic Fab libraries, named S, F, and modified-F, were screened against the recombinant human Notch-1 extracellular domain using phage display. These libraries were built on a modified trastuzumab framework, containing two or four diversified complementarity-determining regions (CDRs) and different CDR diversity designs. In total, 12 Notch-1 Fabs were generated with 10 different CDRH3 lengths. These Fabs possessed a high affinity for Notch-1 (sub-nM to mid-nM K_Dapp values) and exhibited different binding profiles (mono-, bi-or tri-specific) toward Notch/Jagged receptors. Importantly, we showed that screening focused diversity libraries, implementing next-generation sequencing approaches, and fine-tuning the CDR length diversity provided improved binding solutions for Notch-1 recognition. These findings have implications for antibody library design and antibody phage display.

A Novel Synthetic Antibody Library with Complementarity-Determining Region Diversities Designed for an Improved Amplification Profile

Antibody discovery by phage display consists of two phases, i.e., the binding phase and the amplification phase. Ideally, the selection process is dominated by the former, and all the retrieved clones are amplified equally during the latter. In reality, the amplification efficiency of antibody fragments varies widely among different sequences and, after a few rounds of phage display panning, the output repertoire often includes rapidly amplified sequences with low or no binding activity, significantly diminishing the efficiency of antibody isolation. In this work, a novel synthetic single-chain variable fragment (scFv) library with complementarity-determining region (CDR) diversities aimed at improved amplification efficiency was designed and constructed. A previously reported synthetic scFv library with low, non-combinatorial CDR diversities was panned against protein A superantigen, and the library repertoires before and after the panning were analyzed by next generation sequencing. The enrichment or depletion patterns of CDR sequences after panning served as the basis for the design of the new library. Especially for CDR-H3 with a higher and more random diversity, a machine learning method was applied to predict potential fast-amplified sequences among a simulated sequence repertoire. In a direct comparison with the previous generation library, the new library performed better against a panel of antigens in terms of the number of binders isolated, the number of unique sequences, and/or the speed of binder enrichment. Our results suggest that the amplification-centric design of sequence diversity is a valid strategy for the construction of highly functional phage display antibody libraries.

Functionalized Terpolymer-Brush-Based Biointerface with Improved Antifouling Properties for Ultra-Sensitive Direct Detection of Virus in Crude Clinical Samples

New analytical techniques that overcome major drawbacks of current routinely used viral infection diagnosis methods, i.e., the long analysis time and laboriousness of real-time reverse-transcription polymerase chain reaction (qRT-PCR) and the insufficient sensitivity of "antigen tests", are urgently needed in the context of SARS-CoV-2 and other highly contagious viruses. Here, we report on an antifouling terpolymer-brush biointerface that enables the rapid and sensitive detection of SARS-CoV-2 in untreated clinical samples. The developed biointerface carries a tailored composition of zwitterionic and non-ionic moieties and allows for the significant improvement of antifouling capabilities when postmodified with biorecognition elements and exposed to complex media. When deployed on a surface of piezoelectric sensor and postmodified with human-cell-expressed antibodies specific to the nucleocapsid (N) protein of SARS-CoV-2, it made possible the quantitative analysis of untreated samples by a direct detection assay format without the need of additional amplification steps. Natively occurring N-protein-vRNA complexes, usually disrupted during the sample pre-treatment steps, were detected in the untreated clinical samples. This biosensor design improved the bioassay sensitivity to a clinically relevant limit of detection of 1.3 × 10⁴ PFU/mL within a detection time of only 20 min. The high specificity toward N-protein-vRNA complexes was validated both by mass spectrometry and qRT-PCR. The performance characteristics were confirmed by qRT-PCR through a comparative study using a set of clinical nasopharyngeal swab samples. We further demonstrate the extraordinary fouling resistance of this biointerface through exposure to other commonly used crude biological samples (including blood plasma, oropharyngeal, stool, and nasopharyngeal swabs), measured via both the surface plasmon resonance and piezoelectric measurements, which highlights the potential to serve as a generic platform for a wide range of biosensing applications.

Eradicating mesothelin-positive human gastric and pancreatic tumors in xenograft models with optimized anti-mesothelin antibody-drug conjugates from synthetic antibody libraries

Mesothelin (MSLN) is an attractive candidate of targeted therapy for several cancers, and hence there are increasing needs to develop MSLN-targeting strategies for cancer therapeutics. Antibody–drug conjugates (ADCs) targeting MSLN have been demonstrated to be a viable strategy in treating MSLN-positive cancers. However, developing antibodies as targeting modules in ADCs for toxic payload delivery to the tumor site but not to normal tissues is not a straightforward task with many potential hurdles. In this work, we established a high throughput engineering platform to develop and optimize anti-MSLN ADCs by characterizing more than 300 scFv CDR-variants and more than 50 IgG CDR-variants of a parent anti-MSLN antibody as candidates for ADCs. The results indicate that only a small portion of the complementarity determining region (CDR) residues are indispensable in the MSLN-specific targeting. Also, the enhancement of the hydrophilicity of the rest of the CDR residues could drastically increase the overall solubility of the optimized anti-MSLN antibodies, and thus substantially improve the efficacies of the ADCs in treating human gastric and pancreatic tumor xenograft models in mice. We demonstrated that the in vivo treatments with the optimized ADCs resulted in almost complete eradication of the xenograft tumors at the treatment endpoints, without detectable off-target toxicity because of the ADCs’ high specificity targeting the cell surface tumor-associated MSLN. The technological platform can be applied to optimize the antibody sequences for more effective targeting modules of ADCs, even when the candidate antibodies are not necessarily feasible for the ADC development due to the antibodies’ inferior solubility or affinity/specificity to the target antigen.

High-efficacy, high-manufacturability human VH domain antibody therapeutics from transgenic sources

Interest in single-domain antibodies (sdAbs) stems from their unique structural/pronounced, hence therapeutically desirable, features. From the outset-as therapeutic modalities-human antibody heavy chain variable domains (VHs) attracted a particular attention compared with 'naturally-occurring' camelid and shark heavy-chain-only antibody variable domains (VHHs and VNARs, respectively) due to their perceived lack of immunogenicity. However, they have not quite lived up to their initial promise as the VH hits, primarily mined from synthetic VH phage display libraries, have too often been plagued with aggregation tendencies, low solubility and low affinity. Largely unexplored, synthetic camelized human VH display libraries appeared to have remediated the aggregation problem, but the low affinity of the VH hits still persisted, requiring undertaking additional, laborious affinity maturation steps to render VHs therapeutically feasible. A wholesome resolution has recently emerged with the development of non-canonical transgenic rodent antibody discovery platforms that appear to facilely and profusely generate high affinity, high solubility and aggregation-resistant human VHs.

Combinatorial mutagenesis with alternative CDR-L1 and -H2 loop lengths contributes to affinity maturation of antibodies

Loop length variation in the complementary determining regions (CDRs) 1 and 2 encoded in germline variable antibody genes provides structural diversity in naïve antibody libraries. In synthetic single framework libraries the parental CDR-1 and CDR-2 length is typically unchanged and alternative lengths are provided only at CDR-3 sites. Based on an analysis of the germline repertoire and structure-solved anti-hapten and anti-peptide antibodies, we introduced combinatorial diversity with alternative loop lengths into the CDR-L1, CDR-L3 and CDR-H2 loops of anti-digoxigenin and anti-microcystin-LR single chain Fv fragments (scFvs) sharing human IGKV3-20/IGHV3-23 frameworks. The libraries were phage display selected for folding and affinity, and analysed by single clone screening and deep sequencing. Among microcystin-LR binders the most frequently encountered alternative loop lengths were one amino acid shorter (6 aa) and four amino acids longer (11 aa) CDR-L1 loops leading up to 17- and 28-fold improved affinity, respectively. Among digoxigenin binders, 2 amino acids longer (10 aa) CDR-H2 loops were strongly enriched, but affinity improved anti-digoxigenin scFvs were also encountered with 7 aa CDR-H2 and 11 aa CDR-L1 loops. Despite the fact that CDR-L3 loop length variants were not specifically enriched in selections, one clone with 22-fold improved digoxigenin binding affinity was identified containing a 2 residues longer (10 aa) CDR-L3 loop. Based on our results the IGKV3-20/IGHV3-23 scaffold tolerates loop length variation, particularly in CDR-L1 and CDR-H2 loops, without compromising antibody stability, laying the foundation for developing novel synthetic antibody libraries with loop length combinations not existing in the natural human Ig gene repertoire.

A panel of anti-influenza virus nucleoprotein antibodies selected from phage-displayed synthetic antibody libraries with rapid diagnostic capability to distinguish diverse influenza virus subtypes

Immunoassays based on sandwich immuno-complexes of capture and detection antibodies simultaneously binding to the target analytes have been powerful technologies in molecular analyses. Recent developments in single molecule detection technologies enable the detection limit of the sandwich immunoassays approaching femtomolar (10^-15 M), driving the needs of developing sensitive and specific antibodies for ever-increasingly broad applications in detecting and quantifying biomarkers. The key components underlying the sandwich immunoassays are antibody-based affinity reagents, for which the conventional sources are mono- or poly-clonal antibodies from immunized animals. The downsides of the animal-based antibodies as affinity reagents arise from the requirement of months of development timespan and limited choices of antibody candidates due to immunodominance of humoral immune responses in animals. Hence, developing animal antibodies capable of distinguishing highly related antigens could be challenging. To overcome the limitation imposed by the animal immune systems, we developed an in vitro methodology based on phage-displayed synthetic antibody libraries for diverse antibodies as affinity reagents against closely related influenza virus nucleoprotein (NP) subtypes, aiming to differentiating avian influenza virus (H5N1) from seasonal influenza viruses (H1N1 and H3N2), for which the NPs are closely related by 90-94% in terms of pairwise amino acid sequence identity. We applied the methodology to attain, within four weeks, a panel of IgGs with distinguishable specificities against a group of representative NPs with pairwise amino acid sequence identities up to more than 90%, and the antibodies derived from the antibody libraries without further affinity refinement had comparable affinity of mouse antibodies to the NPs with the detection limit less than 1 nM of viral NP from lysed virus with sandwich ELISA. The panel of IgGs were capable of rapidly distinguishing infections due to virulent avian influenza virus from infections of seasonal flu, in responding to a probable emergency scenario where avian influenza virus would be transmissible among humans overlapping with the seasonal influenza infections. The results indicate that the in vitro antibody development methodology enables developing diagnostic antibodies that would not otherwise be available from animal-based antibody technologies.