The protein-protein interface evolution acts in a similar way to antibody affinity maturation

High-throughput analysis system of interaction kinetics for data-driven antibody design

Surface plasmon resonance (SPR) is widely used for antigen-antibody interaction kinetics analysis. However, it has not been used in the screening phase because of the low throughput of measurement and analysis. Herein, we proposed a high-throughput SPR analysis system named "BreviA" using the Brevibacillus expression system. Brevibacillus was transformed using a plasmid library containing various antibody sequences, and single colonies were cultured in 96-well plates. Sequence analysis was performed using bacterial cells, and recombinant antibodies secreted in the supernatant were immobilized on a sensor chip to analyze their interactions with antigens using high-throughput SPR. Using this system, the process from the transformation to 384 interaction analyses can be performed within a week. This system utility was tested using an interspecies specificity design of an anti-human programmed cell death protein 1 (PD-1) antibody. A plasmid library containing alanine and tyrosine mutants of all complementarity-determining region residues was generated. A high-throughput SPR analysis was performed against human and mouse PD-1, showing that the mutation in the specific region enhanced the affinity for mouse PD-1. Furthermore, deep mutational scanning of the region revealed two mutants with > 100-fold increased affinity for mouse PD-1, demonstrating the potential efficacy of antibody design using data-driven approach.

Structure-Based Affinity Maturation of Antibody Based on Double-Point Mutations

Structure-based site-directed affinity maturation of antibodies can be expanded by multiple-point mutations to obtain various mutants. However, selecting the appropriate number of promising mutants for experimental evaluation from the vast number of combinations of multiple-point mutations is challenging. In this report, we describe how to narrow candidate mutants using the so-called weak interaction analysis such as CH-π and CH-O in addition to widely recognized interactions such as hydrogen bonds.

Machine learning modeling to identify affinity improved biobetter anticancer drug trastuzumab and the insight of molecular recognition of trastuzumab towards its antigen HER2

In the present study, a machine learning (ML) model was developed to predict the epistatic phenomena of combination mutants to improve the anticancer antibody-drug trastuzumab's binding affinity towards its antigen human epidermal growth factor receptor 2 (HER2). An ML algorithm, Support Vector Regression (SVR) was used to develop ML models with a data set consists of 193 affinity values of single mutants of trastuzumab and its associated various amino acid sequence derived descriptors. The subset selection of descriptors and SVR hyperparameters were done using the Genetic Algorithm (GA) within the SVR and the wrapper approach called GA-SVR. A 100 evolutionary cycles of GA produced the best 100 probable GA-SVR models based on their fitness score (Q2) estimated using a stratified 5 fold cross-validation procedure. The final ML model found to be highly predictive of test data set of six combination mutants and one single mutant with Rpre2 = 0.71. The analysis of descriptors in the ML model highlighted the importance of mutant induced secondary structural variation causes the binding affinity variation of the trastuzumab. The same was verified using a short 20 ns and a long 100 ns in duplicate molecular dynamics simulation of a wild and mutant variant of trastuzumab. The secondary structure induced affinity change due to mutations in the CDR-H3 is a novel insight that came out of this study. That should help rational mutant selection to develop a biobetter trastuzumab with a multifold improved binding affinity into the market quickly.Communicated by Ramaswamy H. Sarma.

Gastric DLBCL clonal evolution as function of patient age

Diffuse large B cell lymphoma (DLBCL) is the most common type of NHL, accounting for about 40% of NHL cases, and is one of the most aggressive lymphomas. DLBCL is widespread in individuals aged more than 50 years old, with a maximum incidence in the seventh decade, but it may also occur in younger patients. DLBCL may occur in any immune system tissue, including those around the gastrointestinal tract, and even in the stomach, though gastric DLBCL has yet to be sufficiently investigated. This study aimed to understand changes in gastric Diffuse Large B cell lymphoma (gastric DLBCL) development with age. Immunoglobulin (Ig) heavy chain variable region genes were amplified from sections of nine preserved biopsies, from patients whose age varied between 25 and 89 years, sequenced and analyzed. We show first that identification of the malignant clone based on the biopsies is much less certain than was previously assumed; and second that, contrary to expectations, the repertoire of gastric B cell clones is more diverse among the elderly DLBCL patients than among the young.

Quantification of HER2 in COS7 cells using quantum weak measurement

A Mach-Zehnder interferometer system based on weak measurement was set up to determinate the concentration variation of molecule by measuring the phase difference change between the two optical paths. The spectrum of the light was recorded to monitor the concentration of trastuzumab (Herceptin), which is a humanised monoclonal antibody, targeted to human epidermal growth factor receptor 2 (HER2). The trastuzumab targeting to HER2 was real-time detected and continuously monitored, the HER2 numbers of COS7 cells on a coverslip was determined at pico-molar level. Our weak measurement enabled method proposes an alternative approach for the concentration detection of molecules, providing a promising functional tool for the quantification of HER2 in cancer cells, possibly promoting fields such as the diagnosis and treatment of cancer.

IsAb: a computational protocol for antibody design

The design of therapeutic antibodies has attracted a large amount of attention over the years. Antibodies are widely used to treat many diseases due to their high efficiency and low risk of adverse events. However, the experimental methods of antibody design are time-consuming and expensive. Although computational antibody design techniques have had significant advances in the past years, there are still some challenges that need to be solved, such as the flexibility of antigen structure, the lack of antibody structural data and the absence of standard antibody design protocol. In the present work, we elaborated on an in silico antibody design protocol for users to easily perform computer-aided antibody design. First, the Rosetta web server will be applied to generate the 3D structure of query antibodies if there is no structural information available. Then, two-step docking will be used to identify the binding pose of an antibody-antigen complex when the binding information is unknown. ClusPro is the first method to be used to conduct the global docking, and SnugDock is applied for the local docking. Sequentially, based on the predicted binding poses, in silico alanine scanning will be used to predict the potential hotspots (or key residues). Finally, computational affinity maturation protocol will be used to modify the structure of antibodies to theoretically increase their affinity and stability, which will be further validated by the bioassays in the future. As a proof of concept, we redesigned antibody D44.1 and compared it with previously reported data in order to validate IsAb protocol. To further illustrate our proposed protocol, we used cemiplimab antibody, a PD-1 checkpoint inhibitor, as an example to showcase a step-by-step tutorial.

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.

Structure-based design and discovery of novel anti-tissue factor antibodies with cooperative double-point mutations, using interaction analysis

The generation of a wide range of candidate antibodies is important for the successful development of drugs that simultaneously satisfy multiple requirements. To find cooperative mutations and increase the diversity of mutants, an in silico double-point mutation approach, in which 3D models of all possible double-point mutant/antigen complexes are constructed and evaluated using interaction analysis, was developed. Starting from an antibody with very high affinity, four double-point mutants were designed in silico. Two of the double-point mutants exhibited improved affinity or affinity comparable to that of the starting antibody. The successful identification of two active double-point mutants showed that a cooperative mutation could be found by utilizing information regarding the interactions. The individual single-point mutants of the two active double-point mutants showed decreased affinity or no expression. These results suggested that the two active double-point mutants cannot be obtained through the usual approach i.e. a combination of improved single-point mutants. In addition, a triple-point mutant, which combines the distantly located active double-point mutation and an active single-point mutation collaterally obtained in the process of the double-point mutation strategy, was designed. The triple-point mutant showed improved affinity. This finding suggested that the effects of distantly located mutations are independent and additive. The double-point mutation approach using the interaction analysis of 3D structures expands the design repertoire for mutants, and hopefully paves a way for the identification of cooperative multiple-point mutations.

T-Cell Receptor Variable β Domains Rigidify During Affinity Maturation

We investigated T-cell receptor variable β chains binding to the superantigen staphylococcal enterotoxin C3 (SEC 3) with structure information in different stages of affinity maturation. Metadynamics in combination with molecular dynamics simulations allow to access the micro-to-millisecond timescale and reveal a strong effect of energetically significant mutations on the flexibility of the antigen-binding site. The observed changes in dynamics of the complementarity determining region (CDR) loops, especially the CDR 2, and HV 4 loop on this specific pathway of affinity maturation are reflected in their structural diversity, thermodynamics of conformations and kinetics of structural transitions. In addition, this affinity maturation pathway follows the concept of conformational selection, because even without the presence of the antigen the binding competent state is present in this pre-existing ensemble of conformations. In all stages of this affinity maturation process we observe a link between specificity and reduced flexibility.

Antibody Structure and Function: The Basis for Engineering Therapeutics

Antibodies and antibody-derived macromolecules have established themselves as the mainstay in protein-based therapeutic molecules (biologics). Our knowledge of the structure–function relationships of antibodies provides a platform for protein engineering that has been exploited to generate a wide range of biologics for a host of therapeutic indications. In this review, our basic understanding of the antibody structure is described along with how that knowledge has leveraged the engineering of antibody and antibody-related therapeutics having the appropriate antigen affinity, effector function, and biophysical properties. The platforms examined include the development of antibodies, antibody fragments, bispecific antibody, and antibody fusion products, whose efficacy and manufacturability can be improved via humanization, affinity modulation, and stability enhancement. We also review the design and selection of binding arms, and avidity modulation. Different strategies of preparing bispecific and multispecific molecules for an array of therapeutic applications are included.

Cognizance of Molecular Methods for the Generation of Mutagenic Phage Display Antibody Libraries for Affinity Maturation

Antibodies leverage on their unique architecture to bind with an array of antigens. The strength of interaction has a direct relation to the affinity of the antibodies towards the antigen. In vivo affinity maturation is performed through multiple rounds of somatic hypermutation and selection in the germinal centre. This unique process involves intricate sequence rearrangements at the gene level via molecular mechanisms. The emergence of in vitro display technologies, mainly phage display and recombinant DNA technology, has helped revolutionize the way antibody improvements are being carried out in the laboratory. The adaptation of molecular approaches in vitro to replicate the in vivo processes has allowed for improvements in the way recombinant antibodies are designed and tuned. Combinatorial libraries, consisting of a myriad of possible antibodies, are capable of replicating the diversity of the natural human antibody repertoire. The isolation of target-specific antibodies with specific affinity characteristics can also be accomplished through modification of stringent protocols. Despite the ability to screen and select for high-affinity binders, some 'fine tuning' may be required to enhance antibody binding in terms of its affinity. This review will provide a brief account of phage display technology used for antibody generation followed by a summary of different combinatorial library characteristics. The review will focus on available strategies, which include molecular approaches, next generation sequencing, and in silico approaches used for antibody affinity maturation in both therapeutic and diagnostic applications.

Antibody Affinity Maturation by Computational Design

The immune systems protect our bodies from foreign molecules or antigens, where antibodies play important roles. Antibodies evolve over time upon antigen encounter by somatically mutating their genome sequences. The end result is a series of antibodies that display higher affinities and specificities to specific antigens. This process is called affinity maturation. Recent improvements in computer hardware and modeling algorithms now enable the rational design of protein structures and functions, and several works on computer-aided antibody design have been published. In this chapter, we briefly describe computational methods for antibody affinity maturation, focusing on methods for sampling antibody conformations and for scoring designed antibody variants. We also discuss lessons learned from the successful computer-aided design of antibodies.

Optimization of anti-CD20 humanized antibody hu8E4 by site-directed mutation based on epitope analysis

Despite the effectiveness of the anti-CD20 chimeric antibody (mAb), rituximab, in treating B-cell lymphomas, its efficacy remains variable and often modest. Hu8E4 is an anti-CD20 humanized antibody which exhibits markedly higher antitumor activity compared with rituximab. Previous studies have indicated that rituximab and almost all known anti-CD20 murine mAbs recognize the A170/P172 motif within the large extracellular loop of CD20. In this study, we demonstrated that hu8E4 also recognized the A170/P172 motif, suggesting that the epitopes recognized by rituximab and hu8E4 are very similar. Based on this, three single mutations (D57E, Y102K and Y102T) at the heavy chain variable region that can improve the affinity of rituximab were transferred to hu8E4. The results showed that D57E and Y102T but not Y102K successfully enhanced the binding of hu8E4 to CD20. Out of these hu8E4 mutants, hu8E4D57E exhibited the highest affinity. The in vitro and in vivo antitumor activity of hu8E4D57E was further investigated. Our data indicated that hu8E4D57E was as effective as hu8E4 in mediating CDC and inducing apoptosis in B-lymphoma cells, but it was more potent in ADCC than hu8E4. Importantly, hu8E4D57E was shown to be significantly more effective than Hu8E4 in prolonging the survival of SCID mice bearing disseminated B-lymphoma cells, suggesting that it might be a promising therapeutic agent for B-cell lymphomas. Moreover, this study also suggests that the mutations that can improve the affinity of rituximab may be transferred to other anti-CD20 murine mAbs to enhance their binding to CD20.

Combating HER2-overexpressing breast cancer through induction of calreticulin exposure by Tras-Permut CrossMab

Although trastuzumab has succeeded in breast cancer treatment, acquired resistance is one of the prime obstacles for breast cancer therapies. There is an urgent need to develop novel HER2 antibodies against trastuzumab resistance. Here, we first rational designed avidity-imporved trastuzumab and pertuzumab variants, and explored the correlation between the binding avidity improvement and their antitumor activities. After characterization of a pertuzumab variant L56TY with potent antitumor activities, a bispecific immunoglobulin G-like CrossMab (Tras-Permut CrossMab) was generated from trastuzumab and binding avidity-improved pertuzumab variant L56TY. Although, the antitumor efficacy of trastuzumab was not enhanced by improving its binding avidity, binding avidity improvement could significantly increase the anti-proliferative and antibody-dependent cellular cytotoxicity (ADCC) activities of pertuzumab. Further studies showed that Tras-Permut CrossMab exhibited exceptional high efficiency to inhibit the progression of trastuzumab-resistant breast cancer. Notably, we found that calreticulin (CRT) exposure induced by Tras-Permut CrossMab was essential for induction of tumor-specific T cell immunity against tumor recurrence. These data indicated that simultaneous blockade of HER2 protein by Tras-Permut CrossMab could trigger CRT exposure and subsequently induce potent tumor-specific T cell immunity, suggesting it could be a promising therapeutic strategy against trastuzumab resistance.

Large-scale analysis of somatic hypermutations in antibodies reveals which structural regions, positions and amino acids are modified to improve affinity

The principles of affinity maturation of antibodies (Abs), which underlies B cell-mediated immunity, are still under debate. It is unclear whether the antigen (Ag) binding site is a preferred target for mutations, and what the role of activation-induced deaminase (AID) hotspots is in this process. Here we report a structural analysis of 3495 residues that have been replaced through somatic hypermutations (SHMs) in 196 Abs. We show that there is no correlation between the propensity of an amino acid to be in AID hotspot and the probability that it is replaced during the SHM process. Although AID hotspots may be necessary to enable SHMs, they are not a major driving force in determining which residues are mutated. We identified Ab positions that are highly mutated and significantly affect binding. The effect of mutation on binding energy is a major factor in determining which structural regions of the Ab are mutated. There is a clear preference for mutations at the Ag-binding site. However, positions outside this region that also affect binding are often preferred targets for SHMs. As for amino acid preferences, a general trend during SHM is to make Ab-Ag interfaces more similar to protein-protein interfaces in general. In different regions of the Ab, there are different sets of preferences for amino acid substitution. This mapping improves our understanding of Ab affinity maturation and may assist in Ab engineering.

Effective suppression of breast tumor growth by an anti-EGFR/ErbB2 bispecific antibody

Despite the effectiveness of the anti-ErbB2 humanized antibody trastuzumab, less than 35% of patients with ErbB2-overexpressing breast cancer respond to the treatment. Here we engineered an anti-EGFR/ErbB2 bispecific antibody (TC-BsAb) using trastuzumab and cetuximab, an anti-EGFR chimeric antibody. TC-BsAb treatment led to internalization of both EGFR and ErbB2, whereas trastuzumab and cetuximab, either alone or in combination, failed to induce ErbB2 internalization. Both in vitro and in vivo experiments indicated that TC-BsAb was significantly more potent in inhibiting the growth of breast cancer cell lines than trastuzumab, cetuximab, and trastuzumab plus cetuximab, suggesting its potential use for treating breast cancer.