Cell-Binding Assays for Determining the Affinity of Protein-Protein Interactions: Technologies and Considerations

Binding affinity between coronavirus spike protein and human ACE2 receptor

Coronaviruses (CoVs) pose a major risk to global public health due to their ability to infect diverse animal species and potential for emergence in humans. The CoV spike protein mediates viral entry into the cell and plays a crucial role in determining the binding affinity to host cell receptors. With particular emphasis on α- and β-coronaviruses that infect humans and domestic animals, current research on CoV receptor use suggests that the exploitation of the angiotensin-converting enzyme 2 (ACE2) receptor poses a significant threat for viral emergence with pandemic potential. This review summarizes the approaches used to study binding interactions between CoV spike proteins and the human ACE2 (hACE2) receptor. Solid-phase enzyme immunoassays and cell binding assays allow qualitative assessment of binding but lack quantitative evaluation of affinity. Surface plasmon resonance, Bio-layer interferometry, and Microscale Thermophoresis on the other hand, provide accurate affinity measurement through equilibrium dissociation constants (KD). In silico modeling predicts affinity through binding structure modeling, protein-protein docking simulations, and binding energy calculations but reveals inconsistent results due to the lack of a standardized approach. Machine learning and deep learning models utilize simulated and experimental protein-protein interaction data to elucidate the critical residues associated with CoV binding affinity to hACE2. Further optimization and standardization of existing approaches for studying binding affinity could aid pandemic preparedness. Specifically, prioritizing surveillance of CoVs that can bind to human receptors stands to mitigate the risk of zoonotic spillover.

BiSim Tool: a binding simulation tool to aid and simplify ligand-binding assay design and development

Ligand-binding assays (LBAs) rely on the reversible, noncovalent binding between the analyte of interest and the assay reagents, and understanding their dynamic equilibrium is key to building robust LBA methods. Although the dynamic interplay of free and bound fractions can be calculated using mathematical models, these are not routinely applied. This approach is costly in terms of both assay development time and reagents, and can result in an under-exploration of the possible parameter combinations. Therefore, we have created a user-friendly simulation tool to facilitate LBA development (the BiSim Tool). We describe the models driving the mathematical simulations and the main features of our software solution by means of case studies, illustrating the tool's value in drug development. To support drug development for all patients worldwide, the BiSim Tool is now available as an open-source code project and as a free web-based tool at https://proteinbindingsimulation.shinyapps.io/BiSim-ProteinBindingSimulation [1].

Engineered CD47 protects T cells for enhanced antitumour immunity

Adoptively transferred T cells and agents designed to block the CD47-SIRPα axis are promising cancer therapeutics that activate distinct arms of the immune system1,2. Here we administered anti-CD47 antibodies in combination with adoptively transferred T cells with the goal of enhancing antitumour efficacy but observed abrogated therapeutic benefit due to rapid macrophage-mediated clearance of T cells expressing chimeric antigen receptors (CARs) or engineered T cell receptors. Anti-CD47-antibody-mediated CAR T cell clearance was potent and rapid enough to serve as an effective safety switch. To overcome this challenge, we engineered the CD47 variant CD47(Q31P) (47E), which engages SIRPα and provides a 'don't eat me' signal that is not blocked by anti-CD47 antibodies. TCR or CAR T cells expressing 47E are resistant to clearance by macrophages after treatment with anti-CD47 antibodies, and mediate substantial, sustained macrophage recruitment to the tumour microenvironment. Although many of the recruited macrophages manifested an M2-like profile3, the combined therapy synergistically enhanced antitumour efficacy. Our study identifies macrophages as major regulators of T cell persistence and illustrates the fundamental challenge of combining T-cell-directed therapeutics with those designed to activate macrophages. It delivers a therapeutic approach that is capable of simultaneously harnessing the antitumour effects of T cells and macrophages, offering enhanced potency against solid tumours.

Identification of a potent PCNA-p15-interaction inhibitor by autodisplay-based peptide library screening

Proliferating cell nuclear antigen (PCNA) is an essential factor for DNA metabolism. The influence of PCNA on DNA replication and repair, combined with the high expression rate of PCNA in various tumours renders PCNA a promising target for cancer therapy. In this context, an autodisplay-based screening method was developed to identify peptidic PCNA interaction inhibitors. A 12-mer randomized peptide library consisting of 2.54 × 106 colony-forming units was constructed and displayed at the surface of Escherichia coli BL21 (DE3) cells by autodisplay. Cells exhibiting an enhanced binding to fluorescent mScarlet-I-PCNA were enriched in four sorting rounds by flow cytometry. This led to the discovery of five peptide variants with affinity to mScarlet-I-PCNA. Among these, P3 (TCPLRWITHDHP) exhibited the highest binding signal. Subsequent flow cytometric analysis revealed a dissociation constant of 0.62 μM for PCNA-P3 interaction. Furthermore, the inhibition of PCNA interactions was investigated using p15, a PIP-box containing protein involved in DNA replication and repair. P3 inhibited the PCNA-p1551-70 interaction with a half maximal inhibitory activity of 16.2 μM, characterizing P3 as a potent inhibitor of the PCNA-p15 interaction.

Comparing in vitro affinity measurements of antibodies to TfR1: Surface plasmon resonance versus on-cell affinity

Despite years of utilizing the transferrin receptor 1 (TfR1) to transport large biomolecules into the brain, there is no consensus on how to optimally measure affinity to it. The aim of this study was to compare different methods for measuring the affinities of anti-TfR1 antibodies. Antibodies 15G11, OX26 and 8D3 are known to successfully carry large biologics across the blood-brain barrier in humans, rats, and mice, respectively. The affinity to their respective species of TfR1 was measured with different surface plasmon resonance setups in Biacore and an on-cell assay. When the antibody was captured and TfR1 was the analyte, the dissociation in Biacore was very slow. The dissociation was faster when the antibody was the analyte and TfR1 was the ligand. The Biacore setup with capture of N-terminal FLAG-tag TfR1 yielded the most similar apparent affinities as the cell assay. In conclusion, it is important to evaluate assay parameters including assay orientation, surface capture method, and antibody-format when comparing binding kinetics for TfR1 antibodies. Although it seems possible to determine relative affinities of TfR1 antibodies using the methods described here, both the FLAG-tag TfR1 capture setup and cell assays likely yield apparent affinities that are most translatable in vivo.

Efficient evolution of human antibodies from general protein language models

Natural evolution must explore a vast landscape of possible sequences for desirable yet rare mutations, suggesting that learning from natural evolutionary strategies could guide artificial evolution. Here we report that general protein language models can efficiently evolve human antibodies by suggesting mutations that are evolutionarily plausible, despite providing the model with no information about the target antigen, binding specificity or protein structure. We performed language-model-guided affinity maturation of seven antibodies, screening 20 or fewer variants of each antibody across only two rounds of laboratory evolution, and improved the binding affinities of four clinically relevant, highly mature antibodies up to sevenfold and three unmatured antibodies up to 160-fold, with many designs also demonstrating favorable thermostability and viral neutralization activity against Ebola and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pseudoviruses. The same models that improve antibody binding also guide efficient evolution across diverse protein families and selection pressures, including antibiotic resistance and enzyme activity, suggesting that these results generalize to many settings.

Quantification of Binding of Small Molecules to Native Proteins Overexpressed in Living Cells

The affinity and selectivity of small molecules for proteins drive drug discovery and development. We report a fluorescent probe cellular binding assay (FPCBA) for determination of these values for native (untagged) proteins overexpressed in living cells. This method uses fluorophores such as Pacific Blue (PB) linked to cell-permeable protein ligands to generate probes that rapidly and reversibly equilibrate with intracellular targets, as established by kinetic assays of cellular uptake and efflux. To analyze binding to untagged proteins, an internal ribosomal entry site (IRES) vector was employed that allows a single mRNA to encode both the protein target and a separate orthogonal fluorescent protein (mVenus). This enabled cellular uptake of the probe to be correlated with protein expression by flow cytometry, allowing measurement of cellular dissociation constants (Kd) of the probe. This approach was validated by studies of the binding of allosteric activators to eight different Protein Kinase C (PKC) isozymes. Full-length PKCs expressed in transiently transfected HEK293T cells were used to measure cellular Kd values of a probe comprising PB linked to the natural product phorbol via a carbamate. These values were further used to determine competitive binding constants (cellular Ki values) of the nonfluorescent phorbol ester PDBu and the anticancer agent bryostatin 1 for each isozyme. For some PKC-small molecule pairs, these cellular Ki values matched known biochemical Ki values, but for others, altered selectivity was observed in cells. This approach can facilitate quantification of interactions of small molecules with physiologically relevant native proteins.

Development of nanobodies against Staphylococcus enterotoxin B through yeast surface display

Staphylococcus enterotoxin B (SEB) is one of the primary virulence factors of Staphylococcus aureus but there is still a lack of targeted drugs. SEB activates immune cells via interacting with MHC-II on antigen-presenting cells, leading to the production of large amounts of pro-inflammatory cytokines. Blocking the interaction between SEB and MHC-II can avert the overactivation of immune cells. Nanobodies are the smallest functional antibodies that can bind stably to antigens. In this study, an ideal approach to obtain specific nanobodies without immunizing camelids was introduced. We constructed a library containing up to 5 × 108 nanobodies, and then screened those targeting SEB by using yeast surface display (YSD) technique and fluorescence-activated cell sorting (FACS). A total of 8 nanobodies with divergent complementarity-determining regions (CDRs) sequences were identified and one candidate Nb8 with high affinity to SEB was isolated. In vitro study demonstrated that Nb8 significantly inhibited SEB-induced inflammatory response. Molecular docking simulation indicated that the unique CDR3 sequence contributed to the binding of Nb8 to the MHC-II binding domain of SEB and accordingly cut off the connection between SEB and MHC-II. Our efforts contributed to the development of specific nanobodies for eliminating the threats of SEB.

Solving the mystery of the FMC63-CD19 affinity

The majority of approved CAR T cell products are based on the FMC63-scFv directed against CD19. Surprisingly, although antigen binding affinity is a major determinant for CAR function, the affinity of the benchmark FMC63-scFv has not been unambiguously determined. That is, a wide range of affinities have been reported in literature, differing by more than 100-fold. Using a range of techniques, we demonstrate that suboptimal experimental designs can cause artefacts that lead to over- or underestimation of the affinity. To minimize these artefacts, we performed SPR with strictly monomeric and correctly folded soluble CD19, yielding an FMC63-scFv affinity of 2-6 nM. Together, apart from analyzing the FMC63-scFv affinity under optimized conditions, we also provide potential explanations for the wide range of published affinities. We expect that this study will be highly valuable for interpretations of CAR affinity-function relationships, as well as for the design of future CAR T cell generations.

A novel, label-free, pre-equilibrium assay to determine the association and dissociation rate constants of therapeutic antibodies on living cells

BACKGROUND AND PURPOSE

Monoclonal antibodies (Ab) represent the fastest growing drug class. Knowledge of the biophysical parameters (kon , koff and KD ) that dictate Ab:receptor interaction is critical during the drug discovery process. However, with the increasing complexity of Ab formats and their targets, it became apparent that existing technologies present limitations and are not always suitable to determine these parameters. Therefore, novel affinity determination methods represent an unmet assay need.

EXPERIMENTAL APPROACH

We developed a pre-equilibrium kinetic exclusion assay using recent mathematical advances to determine the kon , koff and KD of monoclonal Ab:receptor interactions on living cells. The assay is amenable to all human IgG1 and rabbit Abs.

KEY RESULTS

Using our novel assay, we demonstrated for several monoclonal Ab:receptor pairs that the calculated kinetic rate constants were comparable with orthogonal methods that were lower throughput or more resource consuming. We ran simulations to predict the critical conditions to improve the performance of the assays. We further showed that this method could successfully be applied to both suspension and adherent cells. Finally, we demonstrated that kon and koff , but not KD , correlate with in vitro potency for a panel of monoclonal Abs.

CONCLUSIONS AND IMPLICATIONS

Our novel assay has the potential to systematically probe binding kinetics of monoclonal Abs to cells and can be incorporated in a screening cascade to identify new therapeutic candidates. Wide-spread adoption of pre-equilibrium assays using physiologically relevant systems will lead to a more holistic understanding of how Ab binding kinetics influence their potency.

Diphtheria toxin-derived, anti-PD-1 immunotoxin, a potent and practical tool to selectively deplete PD-1+ cells

Programmed death-1 (PD-1), an immune checkpoint receptor, is expressed on activated lymphocytes, macrophages, and some types of tumor cells. While PD-1+ cells have been implicated in outcomes of cancer immunity, autoimmunity, and chronic infections, the exact roles of these cells in various physiological and pathological processes remain elusive. Molecules that target and deplete PD-1+ cells would be instrumental in defining the roles unambiguously. Previously, an immunotoxin has been generated for the depletion of PD-1+ cells though its usage is impeded by its low production yield. Thus, a more practical molecular tool is desired to deplete PD-1+ cells and to examine functions of these cells. We designed and generated a novel anti-PD1 diphtheria immunotoxin, termed PD-1 DIT, targeting PD-1+ cells. PD-1 DIT is comprised of two single chain variable fragments (scFv) derived from an anti-PD-1 antibody, coupled with the catalytic and translocation domains of the diphtheria toxin. PD-1 DIT was produced using a yeast expression system that has been engineered to efficiently produce protein toxins. The yield of PD-1 DIT reached 1-2 mg/L culture, which is 10 times higher than the previously reported immunotoxin. Flow cytometry and confocal microscopy analyses confirmed that PD-1 DIT specifically binds to and enters PD-1+ cells. The binding avidities between PD-1 DIT and two PD-1+ cell lines are approximately 25 nM. Moreover, PD-1 DIT demonstrated potent cytotoxicity toward PD-1+ cells, with a half maximal effective concentration (EC50 ) value of 1 nM. In vivo experiments further showed that PD-1 DIT effectively depleted PD-1+ cells and enabled mice inoculated with PD-1+ tumor cells to survive throughout the study. Our findings using PD-1 DIT revealed the critical role of pancreatic PD-1+ T cells in the development of type-1 diabetes (T1D). Additionally, we observed that PD-1 DIT treatment ameliorated relapsing-remitting experimental autoimmune encephalomyelitis (RR-EAE), a mouse model of relapsing-remitting multiple sclerosis (RR-MS). Lastly, we did not observe significant hepatotoxicity in mice treated with PD-1 DIT, which had been reported for other immunotoxins derived from the diphtheria toxin. With its remarkable selective and potent cytotoxicity toward PD-1+ cells, coupled with its high production yield, PD-1 DIT emerges as a powerful biotechnological tool for elucidating the physiological roles of PD-1+ cells. Furthermore, the potential of PD-1 DIT to be developed into a novel therapeutic agent becomes evident.

Multiplexed on-yeast serological assay for immune escape screening of SARS-CoV-2 variants

The emergence of the SARS-CoV-2 Omicron variant altered patient risk profiles and shifted the trajectory of the COVID-19 pandemic. Therefore, sensitive serological tests capable of analyzing patient IgG responses to multiple variants in parallel are highly desirable. Here, we present an adaptable serological test based on yeast surface display and serum biopanning that characterizes immune profiles against SARS-CoV-2 Wuhan (B lineage), Delta (B.1.617.2 lineage), and Omicron (B.1.1.529 lineage) receptor-binding domain (RBD) variants. We examined IgG titers from 30 serum samples from COVID-19-convalescent and vaccinated cohorts in Switzerland, and assessed the relative affinity of polyclonal serum IgG for RBD domains. We demonstrate that serum IgGs from patients recovered from severe COVID-19 between March-June 2021 bound tightly to both original Wuhan and Delta RBD variants, but failed to recognize Omicron RBDs, representing an affinity loss of >10- to 20-fold. Our yeast immunoassay is easily tailored, expandable and parallelized with newly emerging RBD variants.

A Novel Flow Cytometry-Based Assay for the Identification of HCN4 CNBD Ligands

Hyperpolarization-activated and cyclic nucleotide-gated (HCN) channels are promising therapeutic targets because of their association with the genesis of several diseases. The identification of selective compounds that alter cAMP-induced ion channel modulation by binding to the cyclic nucleotide-binding domain (CNBD) will facilitate HCN channel-specific drug development. In this study, a fast and protein purification-free ligand-binding approach with a surface-displayed HCN4 C-Linker-CNBD on E. coli is presented. 8-Fluo-cAMP ligand binding was monitored by single-cell analysis via flow cytometry, and a K_d-value of 173 ± 46 nM was determined. The K_d value was confirmed by ligand depletion analysis and equilibrium state measurements. Applying increasing concentrations of cAMP led to a concentration-dependent decrease in fluorescence intensity, indicating a displacement of 8-Fluo-cAMP. A K_i-value of 8.5 ± 2 µM was determined. The linear relationship of IC₅₀ values obtained for cAMP as a function of ligand concentration confirmed the competitive binding mode: IC₅₀: 13 ± 2 µM/16 ± 3 µM/23 ± 1 µM/27 ± 1 µM for 50 nM/150 nM/250 nM/500 nM 8-Fluo-cAMP. A similar competitive mode of binding was confirmed for 7-CH-cAMP, and an IC₅₀ value of 230 ± 41 nM and a K_i of 159 ± 29 nM were determined. Two established drugs were tested in the assay. Ivabradine, an approved HCN channel pore blocker and gabapentin, is known to bind to HCN4 channels in preference to other isoforms with an unknown mode of action. As expected, ivabradine had no impact on ligand binding. In addition, gabapentin had no influence on 8-Fluo-cAMP's binding to HCN4-CNBD. This is the first indication that gabapentin is not interacting with this part of the HCN4 channel. The ligand-binding assay as described can be used to determine binding constants for ligands such as cAMP and derivatives. It could also be applied for the identification of new ligands binding to the HCN4-CNBD.

Genotype-phenotype landscapes for immune-pathogen coevolution

Our immune systems constantly coevolve with the pathogens that challenge them, as pathogens adapt to evade our defense responses, with our immune repertoires shifting in turn. These coevolutionary dynamics take place across a vast and high-dimensional landscape of potential pathogen and immune receptor sequence variants. Mapping the relationship between these genotypes and the phenotypes that determine immune-pathogen interactions is crucial for understanding, predicting, and controlling disease. Here, we review recent developments applying high-throughput methods to create large libraries of immune receptor and pathogen protein sequence variants and measure relevant phenotypes. We describe several approaches that probe different regions of the high-dimensional sequence space and comment on how combinations of these methods may offer novel insight into immune-pathogen coevolution.

GPR160 is not a receptor of anorexigenic cocaine- and amphetamine-regulated transcript peptide

COCAINE: and amphetamine-regulated transcript peptide (CARTp) is an anorexigenic neuropeptide whose receptor is undisclosed. Previously, we reported the specific binding of CART(61-102) to pheochromocytoma PC12 cells, where CART(61-102) affinity and the number of binding sites per cell corresponded to ligand-receptor binding. Recently, Yosten et al. designated orphan GPR160 as the CARTp receptor, because the GPR160 antibody abolished neuropathic pain and anorexigenic effects induced by CART(55-102) and exogenous CART(55-102) coimmunoprecipitated with GPR160 in KATOIII cells. As no direct evidence that CARTp is a ligand for GPR160 has been described, we decided to verify this hypothesis by testing CARTp affinity to the GPR160 receptor. We investigated the GPR160 expression in PC12 cells since it is cell line known to specifically bind CARTp. Moreover, we examined the specific CARTp binding in THP1 cells, with high endogenous GPR160 expression and GPR160-transfected cell lines U2OS and U-251 MG. In PC12 cells, the GPR160 antibody did not compete for specific binding with ¹²⁵I-CART(61-102) or with ¹²⁵I-CART(55-102), and GPR160 mRNA expression and GPR160 immunoreactivity were not detected. Moreover, THP1 cells did not show any ¹²⁵I-CART(61-102) or ¹²⁵I-CART(55-102) specific binding despite GPR160 detection by fluorescent immunocytochemistry (ICC). Finally, no ¹²⁵I-CART(61-102) or ¹²⁵I-CART(55-102) specific binding in the GPR160-transfected cell lines U2OS and U-251 MG, selected due to their negligible endogenous expression of GPR160, was detected, despite the detection of GPR160 by fluorescent ICC. Our binding studies clearly demonstrated that GPR160 cannot be a receptor for CARTp. Further studies are needed to identify true CARTp receptors.

Aided-efflux and high production of β-amyrin realized by β-cyclodextrin in situ synthesized on surface of Saccharomyces cerevisiae

As a plant-derived pentacyclic triterpenoid, β-amyrin has been heterogeneously synthesized in Saccharomyces cerevisiae. However, β-amyrin is intracellularly produced in a lower gram scale using recombinant S. cerevisiae, which limits the industrial applications. Although many strategies have been proven to be effective to improve the production of β-amyrin, the intracellularly accumulation is still a challenge in reaching higher titer and simplifying the extraction process. To solve this problem, the amphiphilic β-cyclodextrin (β-CD) has been previously employed to aid the efflux of β-amyrin out of the cells. Nevertheless, the supplemented β-CD in the medium is not consistent with β-amyrin synthesis and has the disadvantage of rather high cost. Therefore, an aided-efflux system based on in situ synthesis of β-CD was developed in this study to enhance the biosynthesis of β-amyrin and its efflux. The in situ synthesis of β-CD was started from starch by the surface displayed cyclodextrin glycosyltransferase (CGTase) on yeast cells. As a result, the synthesized β-CD could capture 16% of the intracellular β-amyrin and improve the total production by 77%. Furthermore, more strategies including inducing system remodeling, precursor supply enhancement, two-phase fermentation and lipid synthesis regulation were employed. Finally, the production of β-amyrin was increased to 73 mg/L in shake flask, 31 folds higher than the original strain, containing 31 mg/L of extracellular β-amyrin. Overall, this work provides novel strategies for the aided-efflux of natural products with high hydrophobicity in engineered S. cerevisiae.

LRRC15 mediates an accessory interaction with the SARS-CoV-2 spike protein

The interactions between Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and human host factors enable the virus to propagate infections that lead to Coronavirus Disease 2019 (COVID-19). The spike protein is the largest structural component of the virus and mediates interactions essential for infection, including with the primary angiotensin-converting enzyme 2 (ACE2) receptor. We performed two independent cell-based systematic screens to determine whether there are additional proteins by which the spike protein of SARS-CoV-2 can interact with human cells. We discovered that in addition to ACE2, expression of LRRC15 also causes spike protein binding. This interaction is distinct from other known spike attachment mechanisms such as heparan sulfates or lectin receptors. Measurements of orthologous coronavirus spike proteins implied the interaction was functionally restricted to SARS-CoV-2 by accessibility. We localized the interaction to the C-terminus of the S1 domain and showed that LRRC15 shares recognition of the ACE2 receptor binding domain. From analyzing proteomics and single-cell transcriptomics, we identify LRRC15 expression as being common in human lung vasculature cells and fibroblasts. Levels of LRRC15 were greatly elevated by inflammatory signals in the lungs of COVID-19 patients. Although infection assays demonstrated that LRRC15 alone is not sufficient to permit viral entry, we present evidence that it can modulate infection of human cells. This unexpected interaction merits further investigation to determine how SARS-CoV-2 exploits host LRRC15 and whether it could account for any of the distinctive features of COVID-19.

Development of sandwich ELISAs for detecting glucagon-like peptide-1 secretion from intestinal L-cells and their application in STC-1 cells and mice

Certain nutrients stimulate glucagon-like peptide-1 (GLP-1) secretion from the intestinal enteroendocrine L-cells, but due to rapid degradation by the DPP-4 enzyme, >90% is converted to inactive metabolite before reaching the target organs via circulation. Plants are a source of potent bioactive compounds that promote endogenous secretion of GLP-1 from L-cells. To search for the effective bioactive compound from a vast library of natural compounds, a reliable and low-cost assay is required considering the high cost of commercial assays. We developed a low-cost sandwich enzyme-linked immunosorbent assays (s-ELISAs) for detecting 'total', 'sensitive active', and 'wide-range active' GLP-1. The s-ELISAs exhibited high sensitivity with measurement ranges between 0.94~240, 0.98~62.5, and 4.8~4,480 pmol/L, respectively. High precision was observed; i.e., CVs within 5% and 20% for intra- and inter-assay variations, respectively, and excellent recovery of exogenous GLP-1 from assay buffer. The developed s-ELISAs had the same performance as the commercial kits and approximately 80% cheaper cost. For their application, cinnamtannin A2-induced GLP-1 secretion was confirmed in STC-1 cells consistent with our previous findings. The s-ELISAs were further validated by measuring plasma GLP-1 level in mice after oral administration of black soy bean seed coat extract containing cinnamtannin A2.

A Novel Anti-CD22 scFv.Bim Fusion Protein Effectively Induces Apoptosis in Malignant B cells and Promotes Cytotoxicity

CD22 is a B-cell surface antigen which is highly expressed in cancerous B-cell lineages. Anti-CD22 antibodies are currently under focus as promising biologics against hematologic B-cell malignancies. Herein, we introduce a novel active recombinant anti-CD22 scFv.Bim fusion protein for targeting this cancerous antigen. An expression cassette encoding anti-CD22 scFv.Bim fusion protein was expressed in Pichia pastoris. The binding ability, cytotoxicity, and apoptotic activity of the purified recombinant protein against CD22⁺ Raji cell line were assessed by flow cytometry, microscopy, and MTT assay. Using bioinformatics, the 3D structure of the fusion protein and its interaction with CD22 were assessed. The in vitro binding analysis by immunofluorescence microscopy and flow cytometry demonstrated the specific binding of scFv.Bim to CD22⁺ Raji cells but not to CD22^- Jurkat cells. MTT data and Annexin V/PI flow cytometry analysis confirmed the apoptotic activity of anti-CD22 scFv.Bim against Raji cells but not Jurkat cells. In silico analysis also revealed the satisfactory stereochemical quality of the 3D model and molecular interactions toward CD22. This novel recombinant anti-CD22 scFv.Bim fusion protein could successfully deliver the pro-apoptotic peptide, BIM, to the target cells and thus nominates it as a promising molecule in treating B-cell malignancies.

Polymorphisms in common antihypertensive targets: Pharmacogenomic implications for the treatment of cardiovascular disease

The idea of personalized medicine came to fruition with sequencing the human genome; however, aside from a few cases, the genetic revolution has yet to materialize. Cardiovascular diseases are the leading cause of death globally, and hypertension is a common prelude to nearly all cardiovascular diseases. Thus, hypertension is an ideal candidate disease to apply tenants of personalized medicine to lessen cardiovascular disease. Herein is a survey that visually depicts the polymorphisms in the top eight antihypertensive targets. Although there are numerous genome-wide association studies regarding cardiovascular disease, few studies look at the effects of receptor polymorphisms on drug treatment. With 17,000+ polymorphisms in the combined target proteins examined, it is expected that some of the clinical variability in the treatment of hypertension is due to polymorphisms in the drug targets. Recent advances in techniques and technology, such as high throughput examination of single mutations, structure prediction, computational power for modeling, and CRISPR models of point mutations, allow for a relatively rapid and comprehensive examination of the effects of known and future polymorphisms on drug affinity and effects. As hypertension is easy to measure and has a plethora of clinically viable ligands, hypertension makes an excellent disease to study pharmacogenomics in the lab and the clinic. If the promises of personalized medicine are to materialize, a concerted effort to examine the effects polymorphisms have on drugs is required. A clinician with the knowledge of a patient's genotype can then prescribe drugs that are optimal for treating that specific patient.

Aptamers for SARS-CoV-2: Isolation, Characterization, and Diagnostic and Therapeutic Developments

The SARS‐CoV‐2 virus and COVID‐19 pandemic continue to demand effective diagnostic and therapeutic solutions. Finding these solutions requires highly functional molecular recognition elements. Nucleic acid aptamers represent a possible solution. Characterized by their high affinity and specificity, aptamers can be rapidly identified from random‐sequence nucleic acid libraries. Over the past two years, many labs around the world have rushed to create diverse aptamers that target two important structural proteins of SARS‐CoV‐2: the spike (S) protein and nucleocapsid (N) protein. These have led to the identification of many aptamers that show real promise for the development of diagnostic tests and therapeutic agents for SARS‐CoV‐2. Herein we review all these developments, with a special focus on the development of diverse aptasensors for detecting SARS‐CoV‐2. These include electrochemical and optical sensors, lateral flow devices, and aptamer‐linked immobilized sorbent assays.

RNA aptamers specific for transmembrane p24 trafficking protein 6 and Clusterin for the targeted delivery of imaging reagents and RNA therapeutics to human β cells

The ability to detect and target β cells in vivo can substantially refine how diabetes is studied and treated. However, the lack of specific probes still hampers a precise characterization of human β cell mass and the delivery of therapeutics in clinical settings. Here, we report the identification of two RNA aptamers that specifically and selectively recognize mouse and human β cells. The putative targets of the two aptamers are transmembrane p24 trafficking protein 6 (TMED6) and clusterin (CLUS). When given systemically in immune deficient mice, these aptamers recognize the human islet graft producing a fluorescent signal proportional to the number of human islets transplanted. These aptamers cross-react with endogenous mouse β cells and allow monitoring the rejection of mouse islet allografts. Finally, once conjugated to saRNA specific for X-linked inhibitor of apoptosis (XIAP), they can efficiently transfect non-dissociated human islets, prevent early graft loss, and improve the efficacy of human islet transplantation in immunodeficient in mice.

Modified Histone Peptides Linked to Magnetic Beads Reduce Binding Specificity

Histone post-translational modifications are small chemical changes to the histone protein structure that have cascading effects on diverse cellular functions. Detecting histone modifications and characterizing their binding partners are critical steps in understanding chromatin biochemistry and have been accessed using common reagents such as antibodies, recombinant assays, and FRET-based systems. High-throughput platforms could accelerate work in this field, and also could be used to engineer de novo histone affinity reagents; yet, published studies on their use with histones have been noticeably sparse. Here, we describe specific experimental conditions that affect binding specificities of post-translationally modified histones in classic protein engineering platforms and likely explain the relative difficulty with histone targets in these platforms. We also show that manipulating avidity of binding interactions may improve specificity of binding.

Deep mutational engineering of broadly-neutralizing nanobodies accommodating SARS-CoV-1 and 2 antigenic drift

Here, we report the molecular engineering of nanobodies that bind with picomolar affinity to both SARS-CoV-1 and SARS-CoV-2 receptor-binding domains (RBD) and are highly neutralizing. We applied deep mutational engineering to VHH72, a nanobody initially specific for SARS-CoV-1 RBD with little cross-reactivity to SARS-CoV-2 antigen. We first identified all the individual VHH substitutions that increase binding to SARS-CoV-2 RBD and then screened highly focused combinatorial libraries to isolate engineered nanobodies with improved properties. The corresponding VHH-Fc molecules show high affinities for SARS-CoV-2 antigens from various emerging variants and SARS-CoV-1, block the interaction between ACE2 and RBD, and neutralize the virus with high efficiency. Its rare specificity across sarbecovirus relies on its peculiar epitope outside the immunodominant regions. The engineered nanobodies share a common motif of three amino acids, which contribute to the broad specificity of recognition. Our results show that deep mutational engineering is a very powerful method, especially to rapidly adapt existing antibodies to new variants of pathogens.

Affinity and Stability Analysis of Yeast Displayed Proteins

Yeast surface display is a powerful protein engineering technology that is extensively used to improve various properties of proteins, including affinity, specificity, and stability or even to add novel functions (usually ligand binding). Apart from its robustness and versatility as an engineering tool, yeast display offers a further critical advantage: Once the selection campaign is finished, usually resulting in an oligoclonal pool, these enriched protein variants can be analyzed individually on the surface of yeast without the need for any sub-cloning, soluble expression, and purification. Here, we provide detailed protocols for determining both the affinity and the thermal stability of yeast displayed proteins. In addition, we discuss the advantages, challenges, and potential pitfalls associated with affinity and stability analysis using yeast surface display.

A general model of multivalent binding with ligands of heterotypic subunits and multiple surface receptors

Multivalent cell surface receptor binding is a ubiquitous biological phenomenon with functional and therapeutic significance. Predicting the amount of ligand binding for a cell remains an important question in computational biology as it can provide great insight into cell-to-cell communication and rational drug design toward specific targets. In this study, we extend a mechanistic, two-step multivalent binding model. This model predicts the behavior of a mixture of different multivalent ligand complexes binding to cells expressing various types of receptors. It accounts for the combinatorially large number of interactions between multiple ligands and receptors, optionally allowing a mixture of complexes with different valencies and complexes that contain heterogeneous ligand units. We derive the macroscopic predictions and demonstrate how this model enables large-scale predictions on mixture binding and the binding space of a ligand. This model thus provides an elegant and computationally efficient framework for analyzing multivalent binding.

Surface Proteomics Reveals CD72 as a Target for In Vitro-Evolved Nanobody-Based CAR-T Cells in KMT2A/MLL1-Rearranged B-ALL

Alternative strategies are needed for patients with B-cell malignancy relapsing after CD19-targeted immunotherapy. Here, cell surface proteomics revealed CD72 as an optimal target for poor-prognosis KMT2A/MLL1-rearranged (MLLr) B-cell acute lymphoblastic leukemia (B-ALL), which we further found to be expressed in other B-cell malignancies. Using a recently described, fully in vitro system, we selected synthetic CD72-specific nanobodies, incorporated them into chimeric antigen receptors (CAR), and demonstrated robust activity against B-cell malignancy models, including CD19 loss. Taking advantage of the role of CD72 in inhibiting B-cell receptor signaling, we found that SHIP1 inhibition increased CD72 surface density. We establish that CD72-nanobody CAR-T cells are a promising therapy for MLLr B-ALL. SIGNIFICANCE: Patients with MLLr B-ALL have poor prognoses despite recent immunotherapy advances. Here, surface proteomics identifies CD72 as being enriched on MLLr B-ALL but also widely expressed across B-cell cancers. We show that a recently described, fully in vitro nanobody platform generates binders highly active in CAR-T cells and demonstrate its broad applicability for immunotherapy development.This article is highlighted in the In This Issue feature, p. 1861.

An engineered ligand trap inhibits leukemia inhibitory factor as pancreatic cancer treatment strategy

Leukemia inhibitory factor (LIF), a cytokine secreted by stromal myofibroblasts and tumor cells, has recently been highlighted to promote tumor progression in pancreatic and other cancers through KRAS-driven cell signaling. We engineered a high affinity soluble human LIF receptor (LIFR) decoy that sequesters human LIF and inhibits its signaling as a therapeutic strategy. This engineered 'ligand trap', fused to an antibody Fc-domain, has ~50-fold increased affinity (~20 pM) and improved LIF inhibition compared to wild-type LIFR-Fc, potently blocks LIF-mediated effects in pancreatic cancer cells, and slows the growth of pancreatic cancer xenograft tumors. These results, and the lack of apparent toxicity observed in animal models, further highlights ligand traps as a promising therapeutic strategy for cancer treatment.

A Predictive Model of Antibody Binding in the Presence of IgG-Interacting Bacterial Surface Proteins

Many bacteria can interfere with how antibodies bind to their surfaces. This bacterial antibody targeting makes it challenging to predict the immunological function of bacteria-associated antibodies. The M and M-like proteins of group A streptococci (GAS) exhibit IgGFc-binding regions, which they use to reverse IgG binding orientation depending on the host environment. Unraveling the mechanism behind these binding characteristics may identify conditions under which bound IgG can drive an efficient immune response. Here, we have developed a biophysical model for describing these complex protein-antibody interactions. We show how the model can be used as a tool for studying the binding behavior of various IgG samples to M protein by performing in silico simulations and correlating this data with experimental measurements. Besides its use for mechanistic understanding, this model could potentially be used as a tool to aid in the development of antibody treatments. We illustrate this by simulating how IgG binding to GAS in serum is altered as specified amounts of monoclonal or pooled IgG is added. Phagocytosis experiments link this altered antibody binding to a physiological function and demonstrate that it is possible to predict the effect of an IgG treatment with our model. Our study gives a mechanistic understanding of bacterial antibody targeting and provides a tool for predicting the effect of antibody treatments in the presence of bacteria with IgG-modulating surface proteins.

Identification of N-Terminally Diversified GLP-1R Agonists Using Saturation Mutagenesis and Chemical Design

The glucagon-like peptide 1 receptor (GLP-1R) is a class B G-protein coupled receptor (GPCR) and diabetes drug target expressed mainly in pancreatic β-cells that, when activated by its agonist glucagon-like peptide 1 (GLP-1) after a meal, stimulates insulin secretion and β-cell survival and proliferation. The N-terminal region of GLP-1 interacts with membrane-proximal residues of GLP-1R, stabilizing its active conformation to trigger intracellular signaling. The best-studied agonist peptides, GLP-1 and exendin-4, share sequence homology at their N-terminal region; however, modifications that can be tolerated here are not fully understood. In this work, a functional screen of GLP-1 variants with randomized N-terminal domains reveals new GLP-1R agonists and uncovers a pattern whereby a negative charge is preferred at the third position in various sequence contexts. We further tested this sequence-structure-activity principle by synthesizing peptide analogues where this position was mutated to both canonical and noncanonical amino acids. We discovered a highly active GLP-1 analogue in which the native glutamate residue three positions from the N-terminus was replaced with the sulfo-containing amino acid cysteic acid (GLP-1-CYA). The receptor binding and downstream signaling properties elicited by GLP-1-CYA were similar to the wild type GLP-1 peptide. Computational modeling identified a likely mode of interaction of the negatively charged side chain in GLP-1-CYA with an arginine on GLP-1R. This work highlights a strategy of combinatorial peptide screening coupled with chemical exploration that could be used to generate novel agonists for other receptors with peptide ligands.

Binding affinity determination of therapeutic antibodies to membrane protein targets: Kinetic Exclusion Assay using cellular membranes for anti-CD20 antibody

Antibody-based therapeutics targeting membrane proteins have evolved as a major modality for the treatment of cancer, inflammation and autoimmune diseases. There are numerous challenges, ranging from desired epitope expression to reliable binding/functional assays which are associated with developing antibodies for this target class. Specifically, having a robust methodology for characterizing antibody interaction with a membrane protein target is essential for providing guidance on dosing, potency and thus expected efficacy. Fluorescence-activated cell sorting (FACS) has been commonly used to characterize antibodies binding to membrane protein targets. FACS provides information about the antibody-receptor complex (antibody bound to cells) and the apparent equilibrium dissociation constant (K_D^') is elucidated by fitting the antibody-receptor binding isotherm as a function of total antibody concentration to a nonlinear regression model. Conversely, Kinetic Exclusion Assay (KinExA) has been used to measure solution-based equilibrium dissociation constant (K_D) of antibodies. Here, K_D is determined by measuring the free antibody concentration at equilibrium in a series of solutions in which the antibody is at constant concentration and the receptor (either in the membrane or the cell) is titrated. We measured the binding affinity of the anti-CD20 antibody, Rituximab, using both FACS and KinExA. There was ~25-fold difference in the binding affinity measured by these two techniques. We have explored this discrepancy through additional experiments around the mathematical framework involved in the analysis of these two different binding assays. Finally, our study concluded that KinExA enables accurate measurement of the K_D for strong protein-protein interactions (sub-nanomolar values) compared to FACS.

An approach to computer analysis of the ligand binding assay data on example of radioligand assay data

As a rule, receptor-ligand assay data are fitted by logistic functions (4PL model, 5PL model, Feldman's model). The preparation of the initial estimates for parameters of these functions is an important problem for processing receptor-ligand interaction data. This study represents a new mathematical approach to calculate the initial estimates more closely to the true values of parameters. The main idea of this approach is in using the modified linear least squares method for calculations of the parameters for the 4PL model and the Feldman's model. In this study, the convergence of model parameters to true values is verified for the simulated data with different statistical scatter. Also, the results of processing real data for the 4PL model and the Feldman's model are presented. A comparison is made of the parameter values calculated by the presented and a nonlinear method. The developed approach has demonstrated its efficiency in calculating the parameters of the complex Feldman"s models up to 4 ligands and 4 sites.

Polymorphic Region-Specific Antibody for Evaluation of Affinity-Associated Profile of Chimeric Antigen Receptor

Antibody applications in cancer immunotherapy involve diverse strategies, some of which redirect T cell-mediated immunity via engineered antibodies. Affinity is a trait that is crucial for these strategies, as optimal affinity reduces unwanted side effects while retaining therapeutic function. Antibody-antigen pairs possessing a broad affinity range are required to define optimal affinity and to investigate the affinity-associated functional profiles of T cell-engaging strategies such as bispecific antibodies and chimeric antigen receptor-engineered T cells. Here, we demonstrate the unique binding characteristic of the developed antibody clone MVR, which exhibits robust binding to B-lymphoid cell lines. Intriguingly, MVR specifically recognizes the highly polymorphic human leukocyte antigen (HLA)-DR complex and exhibits varying affinities that are dependent upon the HLA-DRB1 allele type. Remarkably, MVR binds to the conformational epitope that consists of two hypervariable regions. As an application of MVR, we demonstrate an MVR-engineered chimeric antigen receptor (CAR) that elicits affinity-dependent function in response to a panel of target cell lines that express different HLA-DRB1 alleles. This tool evaluates the effect of affinity on cytotoxic killing, polyfunctionality, and activation-induced cell death of CAR-engineered T cells. Collectively, MVR exhibits huge potential for the evaluation of the affinity-associated profile of T cells that are redirected by engineered antibodies.

Generating quantitative binding landscapes through fractional binding selections combined with deep sequencing and data normalization

Quantifying the effects of various mutations on binding free energy is crucial for understanding the evolution of protein-protein interactions and would greatly facilitate protein engineering studies. Yet, measuring changes in binding free energy (ΔΔG_bind) remains a tedious task that requires expression of each mutant, its purification, and affinity measurements. We developed an attractive approach that allows us to quantify ΔΔG_bind for thousands of protein mutants in one experiment. Our protocol combines protein randomization, Yeast Surface Display technology, deep sequencing, and a few experimental ΔΔG_bind data points on purified proteins to generate ΔΔG_bind values for the remaining numerous mutants of the same protein complex. Using this methodology, we comprehensively map the single-mutant binding landscape of one of the highest-affinity interaction between BPTI and Bovine Trypsin (BT). We show that ΔΔG_bind for this interaction could be quantified with high accuracy over the range of 12 kcal mol⁻¹ displayed by various BPTI single mutants.

Quantifying the effect of mutations on binding free energy is important to understand protein-protein interaction (PPI). Here the authors develop a method based on yeast display and next-generation sequencing to generate quantitative binding landscapes for any PPI regardless of their Kd value.

Affinity maturation of antibodies by combinatorial codon mutagenesis versus error-prone PCR

IN VITRO

affinity maturation of therapeutic monoclonal antibodies is commonly applied to achieve desired properties, such as improved binding kinetics and affinity. Currently there are no universally accepted protocols for generation of variegated antibody libraries or selection thereof. Here, we performed affinity maturation using a yeast-based single-chain variable fragment (scFv) expression system to compare two mutagenesis methods: random mutagenesis across the entire V(D)J region by error-prone PCR, and a novel combinatorial mutagenesis process limited to the complementarity-determining regions (CDRs). We applied both methods of mutagenesis to four human antibodies against well-known immuno-oncology target proteins. Detailed sequence analysis showed an even mutational distribution across the entire length of the scFv for the error-prone PCR method and an almost exclusive targeting of the CDRs for the combinatorial method. Though there were distinct mutagenesis profiles for each target antibody and mutagenesis method, we found that both methods improved scFv affinity with similar efficiency. When a subset of the affinity-matured antibodies was expressed as full-length immunoglobulin, the measured affinity constants were mostly comparable to those of the respective scFv, but the full-length antibodies were inferior to their scFv counterparts for one of the targets. Furthermore, we found that improved affinity for the full-length antibody did not always translate into enhanced binding to cell-surface expressed antigen or improved immune checkpoint blocking ability, suggesting that screening with full-length antibody or antigen-binding fragment formats might be advantageous and the subject of a future study.

Antitumor activity of an engineered decoy receptor targeting CLCF1-CNTFR signaling in lung adenocarcinoma

Proinflammatory cytokines in the tumor microenvironment can promote tumor growth, yet their value as therapeutic targets remains underexploited. We validated the functional significance of the cardiotrophin-like cytokine factor 1 (CLCF1)-ciliary neurotrophic factor receptor (CNTFR) signaling axis in lung adenocarcinoma (LUAD) and generated a high-affinity soluble receptor (eCNTFR-Fc) that sequesters CLCF1, thereby inhibiting its oncogenic effects. eCNTFR-Fc inhibits tumor growth in multiple xenograft models and in an autochthonous, highly aggressive genetically engineered mouse model of LUAD, driven by activation of oncogenic Kras and loss of Trp53. Abrogation of CLCF1 through eCNTFR-Fc appears most effective in tumors driven by oncogenic KRAS. We observed a correlation between the effectiveness of eCNTFR-Fc and the presence of KRAS mutations that retain the intrinsic capacity to hydrolyze guanosine triphosphate, suggesting that the mechanism of action may be related to altered guanosine triphosphate loading. Overall, we nominate blockade of CLCF1-CNTFR signaling as a novel therapeutic opportunity for LUAD and potentially for other tumor types in which CLCF1 is present in the tumor microenvironment.

Depletion of PD-1-positive cells ameliorates autoimmune disease

Targeted suppression of autoimmune diseases without collateral suppression of normal immunity remains an elusive yet clinically important goal. Targeted blockade of programmed-cell-death-protein-1 (PD-1)-an immune checkpoint factor expressed by activated T cells and B cells-is an efficacious therapy for potentiating immune activation against tumours. Here we show that an immunotoxin consisting of an anti-PD-1 single-chain variable fragment, an albumin-binding domain and Pseudomonas exotoxin targeting PD-1-expressing cells, selectively recognizes and induces the killing of the cells. Administration of the immunotoxin to mouse models of autoimmune diabetes delays disease onset, and its administration in mice paralysed by experimental autoimmune encephalomyelitis ameliorates symptoms. In all mouse models, the immunotoxin reduced the numbers of PD-1-expressing cells, of total T cells and of cells of an autoreactive T-cell clone found in inflamed organs, while maintaining active adaptive immunity, as evidenced by full-strength immune responses to vaccinations. The targeted depletion of PD-1-expressing cells contingent to the preservation of adaptive immunity might be effective in the treatment of a wide range of autoimmune diseases.

Fab is the most efficient format to express functional antibodies by yeast surface display

Multiple formats are available for engineering of monoclonal antibodies (mAbs) by yeast surface display, but they do not all lead to efficient expression of functional molecules. We therefore expressed four anti-tumor necrosis factor and two anti-IpaD mAbs as single-chain variable fragment (scFv), antigen-binding fragment (Fab) or single-chain Fabs and compared their expression levels and antigen-binding efficiency. Although the scFv and scFab formats are widely used in the literature, 2 of 6 antibodies were either not or weakly expressed. In contrast, all 6 antibodies expressed as Fab revealed strong binding and high affinity, comparable to that of the soluble form. We also demonstrated that the variations in expression did not affect Fab functionality and were due to variations in light chain display and not to misfolded dimers. Our results suggest that Fab is the most versatile format for the engineering of mAbs.

Labeling for Quantitative Comparison of Imaging Measurements in Vitro and in Cells

Qualitative imaging of biomolecular localization and distribution inside cells has revolutionized cell biology. Most of these powerful techniques require modifications to the target biomolecule. Over the past 10 years, these techniques have been extended to quantitative measurements, from in-cell protein folding rates to complex dissociation constants to RNA lifetimes. Such measurements can be affected even when a target molecule is just mildly perturbed by its labels. Here, the impact of labeling on protein (and RNA) structure, stability, and function in cells is discussed via practical examples from the recent literature. General guidelines for selecting and validating modification sites are provided to bring the best from cell biology and imaging to quantitative biophysical experiments inside cells.

Engineering a potent inhibitor of matriptase from the natural hepatocyte growth factor activator inhibitor type-1 (HAI-1) protein

Dysregulated matriptase activity has been established as a key contributor to cancer progression through its activation of growth factors, including the hepatocyte growth factor (HGF). Despite its critical role and prevalence in many human cancers, limitations to developing an effective matriptase inhibitor include weak binding affinity, poor selectivity, and short circulating half-life. We applied rational and combinatorial approaches to engineer a potent inhibitor based on the hepatocyte growth factor activator inhibitor type-1 (HAI-1), a natural matriptase inhibitor. The first Kunitz domain (KD1) of HAI-1 has been well established as a minimal matriptase-binding and inhibition domain, whereas the second Kunitz domain (KD2) is inactive and involved in negative regulation. Here, we replaced the inactive KD2 domain of HAI-1 with an engineered chimeric variant of KD2/KD1 domains and fused the resulting construct to an antibody Fc domain to increase valency and circulating serum half-life. The final protein variant contains four stoichiometric binding sites that we showed were needed to effectively inhibit matriptase with a K_i of 70 ± 5 pm, an increase of 120-fold compared with the natural HAI-1 inhibitor, to our knowledge making it one of the most potent matriptase inhibitors identified to date. Furthermore, the engineered inhibitor demonstrates a protease selectivity profile similar to that of wildtype KD1 but distinct from that of HAI-1. It also inhibits activation of the natural pro-HGF substrate and matriptase expressed on cancer cells with at least an order of magnitude greater efficacy than KD1.

Bacterial Surface Glycans: Microarray and QCM Strategies for Glycophenotyping and Exploration of Recognition by Host Receptors

Bacterial surfaces are decorated with a diversity of carbohydrate structures that play important roles in the bacteria-host relationships. They may offer protection against host defense mechanisms, elicit strong antigenic responses, or serve as ligands for host receptors, including lectins of the innate immune system. Binding by these lectins may trigger defense responses or, alternatively, promote attachment, thereby enhancing infection. The outcome will depend on the particular bacterial surface landscape, which may substantially differ among species and strains. In this chapter, we describe two novel methods for exploring interactions directly on the bacterial surface, based on the generation of bacterial microarrays and quartz crystal microbalance (QCM) sensor chips. Bacterial microarrays enable profiling of accessible carbohydrate structures and screening of their recognition by host receptors, also providing information on binding avidity, while the QCM approach allows determination of binding affinity and kinetics. In both cases, the chief element is the use of entire bacterial cells, so that recognition of the bacterial glycan epitopes is explored in their natural environment.

Engineered ligand-based VEGFR antagonists with increased receptor binding affinity more effectively inhibit angiogenesis

Pathologic angiogenesis is mediated by the coordinated action of the vascular endothelial growth factor (VEGF)/vascular endothelial growth factor receptor 2 (VEGFR2) signaling axis, along with crosstalk contributed by other receptors, notably α_vβ₃ integrin. We build on earlier work demonstrating that point mutations can be introduced into the homodimeric VEGF ligand to convert it into an antagonist through disruption of binding to one copy of VEGFR2. This inhibitor has limited potency, however, due to loss of avidity effects from bivalent VEGFR2 binding. Here, we used yeast surface display to engineer a variant with VEGFR2 binding affinity approximately 40‐fold higher than the parental antagonist, and 14‐fold higher than the natural bivalent VEGF ligand. Increased VEGFR2 binding affinity correlated with the ability to more effectively inhibit VEGF‐mediated signaling, both in vitro and in vivo, as measured using VEGFR2 phosphorylation and Matrigel implantation assays. High affinity mutations found in this variant were then incorporated into a dual‐specific antagonist that we previously designed to simultaneously bind to and inhibit VEGFR2 and α_vβ₃ integrin. The resulting dual‐specific protein bound to human and murine endothelial cells with relative affinities of 120 ± 10 pM and 360 ± 50 pM, respectively, which is at least 30‐fold tighter than wild‐type VEGF (3.8 ± 0.5 nM). Finally, we demonstrated that this engineered high‐affinity dual‐specific protein could inhibit angiogenesis in a murine corneal neovascularization model. Taken together, these data indicate that protein engineering strategies can be combined to generate unique antiangiogenic candidates for further clinical development.

Engineering High Affinity Protein-Protein Interactions Using a High-Throughput Microcapillary Array Platform

Affinity maturation of protein-protein interactions requires iterative rounds of protein library generation and high-throughput screening to identify variants that bind with increased affinity to a target of interest. We recently developed a multipurpose protein engineering platform, termed μSCALE (Microcapillary Single Cell Analysis and Laser Extraction). This technology enables high-throughput screening of libraries of millions of cell-expressing protein variants based on their binding properties or functional activity. Here, we demonstrate the first use of the μSCALE platform for affinity maturation of a protein-protein binding interaction. In this proof-of-concept study, we engineered an extracellular domain of the Axl receptor tyrosine kinase to bind tighter to its ligand Gas6. Within 2 weeks, two iterative rounds of library generation and screening resulted in engineered Axl variants with a 50-fold decrease in kinetic dissociation rate, highlighting the use of μSCALE as a new tool for directed evolution.