Designing antibodies as therapeutics

Orchestrating NK and T cells via tri-specific nano-antibodies for synergistic antitumor immunity

The functions of natural killer (NK) and T cells in innate and adaptive immunity, as well as their functions in tumor eradication, are complementary and intertwined. Here we show that utilization of multi-specific antibodies or nano-antibodies capable of simultaneously targeting both NK and T cells could be a valuable approach in cancer immunotherapy. Here, we introduce a tri-specific Nano-Antibody (Tri-NAb), generated by immobilizing three types of monoclonal antibodies (mAbs), using an optimized albumin/polyester composite nanoparticle conjugated with anti-Fc antibody. This Tri-NAb, targeting PDL1, 4-1BB, and NKG2A (or TIGIT) simultaneously, effectively binds to NK and CD8+ T cells, triggering their activation and proliferation, while facilitating their interaction with tumor cells, thereby inducing efficient tumor killing. Importantly, the antitumor efficacy of Tri-NAb is validated in multiple models, including patient-derived tumor organoids and humanized mice, highlighting the translational potential of NK and T cell co-targeting.

Reprogramming human B cells with custom heavy-chain antibodies

The immunoglobulin locus of B cells can be reprogrammed by genome editing to produce custom or non-natural antibodies that are not induced by immunization. However, current strategies for antibody reprogramming require complex expression cassettes and do not allow for customization of the constant region of the antibody. Here we show that human B cells can be edited at the immunoglobulin heavy-chain locus to express heavy-chain-only antibodies that support alterations to both the fragment crystallizable domain and the antigen-binding domain, which can be based on both antibody and non-antibody components. Using the envelope protein (Env) from the human immunodeficiency virus as a model antigen, we show that B cells edited to express heavy-chain antibodies to Env support the regulated expression of B cell receptors and antibodies through alternative splicing and that the cells respond to the Env antigen in a tonsil organoid model of immunization. This strategy allows for the reprogramming of human B cells to retain the potential for in vivo amplification while producing molecules with flexibility of composition beyond that of standard antibodies.

In Migratio Noncovalent Fluorophore Labeling of Proteins by Propidium Iodide in Sodium Dodecyl Sulfate Capillary Gel Electrophoresis

Sodium dodecyl sulfate capillary gel electrophoresis is one of the frequently used methods for size-based protein separation in molecular biology laboratories and the biopharmaceutical industry. To increase throughput, quite a few multicapillary electrophoresis systems have been recently developed, but most of them only support fluorescence detection, requiring fluorophore labeling of the sample proteins. To avoid the time-consuming derivatization reaction, we developed an on-column labeling approach utilizing propidium iodide for the first time in SDS-CGE of proteins, a dye only used before for nucleic acid analysis. As a key ingredient of the gel-buffer system, the oppositely migrating positively charged propidium ligand in migratio complexes with the SDS-proteins, therefore, supports in situ labeling during the electrophoretic separation process, not requiring any extra pre- or postcolumn derivatization step. A theoretical treatment is given to shed light on the basic principles of this novel online labeling process, also addressing the influence of propidium iodide on the electroosmotic flow, resulting in reduced retardation. The concept of propidium labeling in SDS-CGE was first demonstrated using a commercially available protein sizing ladder ranging from 6.5 to 200 kDa with different isoelectric points and post-translational modifications. Considering the increasing number of protein therapeutics on the market next, we focused on the labeling optimization of a therapeutic monoclonal antibody and its subunits, including the addition of the nonglycosylated heavy chain. Peak efficiency and resolution were compared between noncovalent and covalent labeling. The effect of ligand concentration on the effective and apparent electrophoretic mobility, the resulting peak area, and the resolution were all evaluated in view of the theoretical considerations. The best detection sensitivity for the intact monoclonal antibody was obtained by using 200 μg/mL propidium iodide in the separation medium (LOD 2 μg/mL, 1.35 × 10-8 M) with excellent detection linearity over 3 orders of magnitude. On the other hand, the resolution between the biopharmaceutical protein test mixture components containing the intact and subunit fragments of the therapeutic monoclonal antibody was very good in the ligand concentration range of 50-200 μg/mL, but using the local maximum at 100 μg/mL for the nonglycosylated/glycosylated heavy chain pair is recommended. The figures of merit, including precision, sensitivity, detection linear range, and resolution for a sample mixture in hand, can be optimized by varying the propidium iodide concentration in the gel-buffer system, as demonstrated in this paper.

A Comparison of Antibody-Antigen Complex Sequence-to-Structure Prediction Methods and their Systematic Biases

The ability to accurately predict antibody-antigen complex structures from their sequences could greatly advance our understanding of the immune system and would aid in the development of novel antibody therapeutics. There have been considerable recent advancements in predicting protein-protein interactions (PPIs) fueled by progress in machine learning (ML). To understand the current state of the field, we compare six representative methods for predicting antibody-antigen complexes from sequence, including two deep learning approaches trained to predict PPIs in general (AlphaFold-Multimer, RoseTTAFold), two composite methods that initially predict antibody and antigen structures separately and dock them (using antibody-mode ClusPro), local refinement in Rosetta (SnugDock) of globally docked poses from ClusPro, and a pipeline combining homology modeling with rigid-body docking informed by ML-based epitope and paratope prediction (AbAdapt). We find that AlphaFold-Multimer outperformed other methods, although the absolute performance leaves considerable room for improvement. AlphaFold-Multimer models of lower-quality display significant structural biases at the level of tertiary motifs (TERMs) towards having fewer structural matches in non-antibody containing structures from the Protein Data Bank (PDB). Specifically, better models exhibit more common PDB-like TERMs at the antibody-antigen interface than worse ones. Importantly, the clear relationship between performance and the commonness of interfacial TERMs suggests that scarcity of interfacial geometry data in the structural database may currently limit application of machine learning to the prediction of antibody-antigen interactions.

Nuclease-assisted selection of slow-off rate aptamers

Conventional directed evolution methods offer the ability to select bioreceptors with high binding affinity for a specific target in terms of thermodynamic properties. However, there is a lack of analogous approaches for kinetic selection, which could yield affinity reagents that exhibit slow off-rates and thus remain tightly bound to targets for extended periods. Here, we describe an in vitro directed evolution methodology that uses the nuclease flap endonuclease 1 to achieve the efficient discovery of aptamers that have slow dissociation rates. Our nuclease-assisted selection strategy can yield specific aptamers for both small molecules and proteins with off-rates that are an order of magnitude slower relative to those obtained with conventional selection methods while still retaining excellent overall target affinity in terms of thermodynamics. This new methodology provides a generalizable approach for generating slow off-rate aptamers for diverse targets, which could, in turn, prove valuable for applications including molecular devices, bioimaging, and therapy.

Selective haematological cancer eradication with preserved haematopoiesis

Haematopoietic stem cell (HSC) transplantation (HSCT) is the only curative treatment for a broad range of haematological malignancies, but the standard of care relies on untargeted chemotherapies and limited possibilities to treat malignant cells after HSCT without affecting the transplanted healthy cells1. Antigen-specific cell-depleting therapies hold the promise of much more targeted elimination of diseased cells, as witnessed in the past decade by the revolution of clinical practice for B cell malignancies2. However, target selection is complex and limited to antigens expressed on subsets of haematopoietic cells, resulting in a fragmented therapy landscape with high development costs2-5. Here we demonstrate that an antibody-drug conjugate (ADC) targeting the pan-haematopoietic marker CD45 enables the antigen-specific depletion of the entire haematopoietic system, including HSCs. Pairing this ADC with the transplantation of human HSCs engineered to be shielded from the CD45-targeting ADC enables the selective eradication of leukaemic cells with preserved haematopoiesis. The combination of CD45-targeting ADCs and engineered HSCs creates an almost universal strategy to replace a diseased haematopoietic system, irrespective of disease aetiology or originating cell type. We propose that this approach could have broad implications beyond haematological malignancies.

A new era of antibody discovery: an in-depth review of AI-driven approaches

Given their high affinity and specificity for a range of macromolecules, antibodies are widely used in the treatment of autoimmune diseases, cancers, inflammatory diseases, and Alzheimer's disease (AD). Traditional experimental methods are time-consuming, expensive, and labor-intensive. Recent advances in artificial intelligence (AI) technologies provide complementary methods that can reduce the time and costs required for antibody design by minimizing failures and increasing the success rate of experimental tests. In this review, we scrutinize the plethora of AI-driven methodologies that have been deployed over the past 4 years for modeling antibody structures, predicting antibody-antigen interactions, optimizing antibody affinity, and generating novel antibody candidates. We also briefly address the challenges faced in integrating AI-based models with traditional antibody discovery pipelines and highlight the potential future directions in this burgeoning field.

Recombinant immune complexes as vaccines against infectious diseases

New vaccine technologies are needed to combat many existing infections and prepare better for those that may emerge in the future. The conventional technologies that rely on protein-based vaccines are still severely restricted by the sparsity and poor accessibility of available adjuvants. One possible solution to this problem is to enhance antigen immunogenicity by a more natural means by complexing it with antibodies in the form of immune complexes (ICs). However, natural ICs are impractical as vaccines, and significant research efforts have been made to generate them in recombinant form, with plant bioengineering being at the forefront of these efforts. Here, we describe the challenges and progress made to date to make recombinant IC vaccines applicable to humans.

Antibody-Loading of Biological Nanocarrier Vesicles Derived from Red-Blood-Cell Membranes

Antibodies, disruptive potent therapeutic agents against pharmacological targets, face a barrier in crossing immune systems and cellular membranes. To overcome these, various strategies have been explored including shuttling via liposomes or biocamouflaged nanoparticles. Here, we demonstrate the feasibility of loading antibodies into exosome-mimetic nanovesicles derived from human red-blood-cell membranes, which can act as nanocarriers for intracellular delivery. Goat-antichicken antibodies are loaded into erythrocyte-derived nanovesicles, and their loading yields are characterized and compared with smaller dUTP-cargo molecules. Applying dual-color coincident fluorescence burst analyses, the loading yield of nanocarriers is rigorously profiled at the single-vesicle level, overcoming challenges due to size-heterogeneity and demonstrating a maximum antibody-loading yield of 38-41% at the optimal vesicle radius of 52 nm. The achieved average loading yields, amounting to 14% across the entire nanovesicle population, with more than two antibodies per loaded vesicle, are fully comparable to those obtained for the much smaller dUTP molecules loaded in the nanovesicles after additional exosome-spin-column purification. The results suggest a promising new avenue for therapeutic delivery of antibodies, potentially encompassing also intracellular targets and suitable for large-scale pharmacological applications, which relies on the exosome-mimetic properties, biocompatibility, and low-immunogenicity of bioengineered nanocarriers synthesized from human erythrocyte membranes.

An integrated methodology for quality assessment of therapeutic antibodies with potential long circulation half-life in harvested cell culture fluid using FcRn immobilized hydrophilic magnetic graphene

Designing modified therapeutic antibodies with enhanced FcRn-binding affinity holds promise in the extension of circulation half-lives and potential refinement of pharmacokinetics. During the development of these new-generation therapeutic antibodies, FcRn binding affinity of IgGs is emphasized and monitored as a critical quality attribute (CQA), alongside other critical assessments including titer and aggregation level. However, the traditional workflow for assessing the overall quality of expressed IgGs in harvested cell culture fluid (HCCF) is blamed to be cumbersome and time-consuming. This study presents an integrated methodology for the rapid quality assessment of IgGs in HCCF by selectively extracting IgGs with favorable high FcRn affinity for subsequent analysis using size exclusion chromatography (SEC). The approach utilizes innovative adsorbents known as FcRn immobilized hydrophilic magnetic graphene (MG@PDA@PAMAM-FcRn) in a magnetic solid-phase extraction (MSPE) process. To simulate the in vivo binding dynamics, MSPE binding and dissociation was performed at pH 6.0 and 7.4, respectively. The composite have demonstrated enhanced extraction efficiency and impurity removal ability in comparison to commercially available magnetic beads. The SEC monomer peak area value provides the output of this method, the ranking of which enabled the facile identification of superior HCCF samples with high overall quality of IgG. Optimization of MSPE parameters was performed, and the method was validated for specificity, precision, sensitivity, and accuracy. The proposed method exhibited an analytical time of 0.6 h, which is 7-22 times shortened in comparison to the conventional workflow.

Utility of protein-protein binding surfaces composed of anti-parallel alpha-helices and beta-sheets selected by phage display

Over the past 3 decades, a diverse collection of small protein domains have been used as scaffolds to generate general purpose protein-binding reagents using a variety of protein display and enrichment technologies. To expand the repertoire of scaffolds and protein surfaces that might serve this purpose, we have explored the utility of (i) a pair of anti-parallel alpha-helices in a small highly disulfide-bonded 4-helix bundle, the CC4 domain from reversion-inducing Cysteine-rich Protein with Kazal Motifs and (ii) a concave beta-sheet surface and two adjacent loops in the human FN3 domain, the scaffold for the widely used monobody platform. Using M13 phage display and next generation sequencing, we observe that, in both systems, libraries of ∼30 million variants contain binding proteins with affinities in the low μM range for baits corresponding to the extracellular domains of multiple mammalian proteins. CC4- and FN3-based binding proteins were fused to the N- and/or C-termini of Fc domains and used for immunostaining of transfected cells. Additionally, FN3-based binding proteins were inserted into VP1 of AAV to direct AAV infection to cells expressing a defined surface receptor. Finally, FN3-based binding proteins were inserted into the Pvc13 tail fiber protein of an extracellular contractile injection system particle to direct protein cargo delivery to cells expressing a defined surface receptor. These experiments support the utility of CC4 helices B and C and of FN3 beta-strands C, D, and F together with adjacent loops CD and FG as surfaces for engineering general purpose protein-binding reagents.

Progress in novel delivery technologies to improve efficacy of therapeutic antibodies

Monoclonal antibody-based therapeutics have achieved remarkable success in treating a wide range of human diseases. However, conventional systemic delivery methods have limitations in insufficient target tissue permeability, high costs, repeated administrations, etc. Novel technologies have been developed to address these limitations and further enhance antibody therapy. Local antibody delivery via respiratory tract, gastrointestinal tract, eye and blood-brain barrier have shown promising results in increasing local concentrations and overcoming barriers. Nucleic acid-encoded antibodies expressed from plasmid DNA, viral vectors or mRNA delivery platforms also offer advantages over recombinant proteins such as sustained expression, rapid onset, and lower costs. This review summarizes recent advances in antibody delivery methods and highlights innovative technologies that have potential to expand therapeutic applications of antibodies.

Long-Acting Strategies for Antibody Drugs: Structural Modification, Controlling Release, and Changing the Administration Route

Because of their high specificity, high affinity, and targeting, antibody drugs have been widely used in the treatment of many diseases and have become the most favored new drugs for research in the world. However, some antibody drugs (such as small-molecule antibody fragments) have a short half-life and need to be administered frequently, and are often associated with injection-site reactions and local toxicities during use. Increasing attention has been paid to the development of antibody drugs that are long-acting and have fewer side effects. This paper reviews existing strategies to achieve long-acting antibody drugs, including modification of the drug structure, the application of drug delivery systems, and changing their administration route. Among these, microspheres have been studied extensively regarding their excellent tolerance at the injection site, controllable loading and release of drugs, and good material safety. Subcutaneous injection is favored by most patients because it can be quickly self-administered. Subcutaneous injection of microspheres is expected to become the focus of developing long-lasting antibody drug strategies in the near future.

Myricetin Oligomer Triggers Multi-Receptor Mediated Penetration and Autophagic Restoration of Blood-Brain Barrier for Ischemic Stroke Treatment

Restoration of blood-brain barrier (BBB) dysfunction, which drives worse outcomes of ischemic stroke, is a potential target for therapeutic opportunities, whereas a sealed BBB blocks the therapeutics entrance into the brain, making the BBB protection strategy paradoxical. Post ischemic stroke, hypoxia/hypoglycemia provokes the up-regulation of transmembrane glucose transporters and iron transporters due to multiple metabolic disorders, especially in brain endothelial cells. Herein, we develop a myricetin oligomer-derived nanostructure doped with Ce to bypass the BBB which is cointermediated by glucose transporters and iron transporters such as glucose transporters 1 (GLUT1), sodium/glucose cotransporters 1 (SGLT1), and transferrin(Tf) reporter (TfR). Moreover, it exhibits BBB restoration capacity by regulating the expression of tight junctions (TJs) through the activation of protective autophagy. The myricetin oligomers scaffold not only acts as targeting moiety but is the prominent active entity that inherits all diverse pharmacological activities of myricetin. The suppression of oxidative damage, M1 microglia activation, and inflammatory factors makes it a multitasking nanoagent with a single component as the scaffold, targeting domain and curative components.

Liquid Droplet-Mediated Formulation of Lipid Nanoparticles Encapsulating Immunoglobulin G for Cytosolic Delivery

Antibodies are promising biopharmaceuticals that offer new therapeutic options for diseases. Since antibodies are membrane impermeable, approaches that allow immunoglobulin Gs (IgGs) to access intracellular therapeutic targets would open new horizons in antibody therapies. Lipid nanoparticles (LNPs) are among the classes of vectors that deliver biopharmaceuticals into cells. Using liquid droplets formed by IgG and polyglutamate, we report here a unique approach to forming LNPs containing IgG via liquid droplets formed in the presence of polyglutamic acid (polyE). The addition of polyE promoted the formation of smaller LNPs with cationic lipids than in its absence, and the formed LNPs were much more efficient in cytosolic IgG delivery and targeting of cellular proteins. This approach also allows for the encapsulation of intact IgG without the need for chemical or sequence modification. The intracellularly delivered IgG retained its target binding ability, as demonstrated by labeling of nuclear pore complex and HRas-GFP and inhibition of antiapoptotic cell death by phosphorylated Akt protein in live cells.

Structural insights into IL-6 signaling inhibition by therapeutic antibodies

Antibody inhibitors of the interleukin-6 (IL-6) signaling pathway, such as tocilizumab and sarilumab, have been used to treat rheumatoid arthritis, chimeric antigen receptor T cell-induced cytokine storm, and severe COVID-19 pneumonia. Here, we solve the cryogenic electron microscopy structures of sarilumab and tocilizumab in complex with IL-6R to resolutions of 3.2 and 3.3 Å, respectively. These structures reveal that both tocilizumab and sarilumab bind to the D3 domain of IL-6R. The binding surfaces of the two antibodies largely overlap, but the detailed interactions are different. Functional studies of various mutants show results consistent with our structural analysis of the antibodies and IL-6R interactions. Structural comparisons with the IL-6/IL-6R/gp130 complex indicate that sarilumab and tocilizumab probably inhibit IL-6/IL-6R signaling by competing for the IL-6 binding site. In summary, this work reveals the antibody-blocking mechanism of the IL-6 signaling pathway and paves the way for future antibody discovery.

Cryo-electron microscopy-based drug design

Structure-based drug design (SBDD) has gained popularity owing to its ability to develop more potent drugs compared to conventional drug-discovery methods. The success of SBDD relies heavily on obtaining the three-dimensional structures of drug targets. X-ray crystallography is the primary method used for solving structures and aiding the SBDD workflow; however, it is not suitable for all targets. With the resolution revolution, enabling routine high-resolution reconstruction of structures, cryogenic electron microscopy (cryo-EM) has emerged as a promising alternative and has attracted increasing attention in SBDD. Cryo-EM offers various advantages over X-ray crystallography and can potentially replace X-ray crystallography in SBDD. To fully utilize cryo-EM in drug discovery, understanding the strengths and weaknesses of this technique and noting the key advancements in the field are crucial. This review provides an overview of the general workflow of cryo-EM in SBDD and highlights technical innovations that enable its application in drug design. Furthermore, the most recent achievements in the cryo-EM methodology for drug discovery are discussed, demonstrating the potential of this technique for advancing drug development. By understanding the capabilities and advancements of cryo-EM, researchers can leverage the benefits of designing more effective drugs. This review concludes with a discussion of the future perspectives of cryo-EM-based SBDD, emphasizing the role of this technique in driving innovations in drug discovery and development. The integration of cryo-EM into the drug design process holds great promise for accelerating the discovery of new and improved therapeutic agents to combat various diseases.

Subcutaneous Administration of Monoclonal Antibodies: Pharmacology, Delivery, Immunogenicity, and Learnings From Applications to Clinical Development

Subcutaneous (s.c.) administration of monoclonal antibodies (mAbs) can reduce treatment burden for patients and healthcare systems compared with intravenous (i.v.) infusion through shorter administration times, made possible by convenient, patient-centric devices. A deeper understanding of clinical pharmacology principles related to efficacy and safety of s.c.-administered mAbs over the past decade has streamlined s.c. product development. This review presents learnings from key constituents of the s.c. mAb development pathway, including pharmacology, administration variables, immunogenicity, and delivery devices. Restricted mAb transportation through the hypodermis explains their incomplete absorption at a relatively slow rate (pharmacokinetic (PK)) and may impact mAb-cellular interactions and/or onset and magnitude of physiological responses (pharmacodynamic). Injection volumes, formulation, rate and site of injection, and needle attributes may affect PKs and the occurrence/severity of adverse events like injection-site reactions or pain, with important consequences for treatment adherence. A review of immunogenicity data for numerous compounds reveals that incidence of anti-drug antibodies (ADAs) is generally comparable across i.v. and s.c. routes, and complementary factors including response magnitude (ADA titer), persistence over time, and neutralizing antibody presence are needed to assess clinical impact. Finally, four case studies showcase how s.c. biologics have been clinically developed: (i) by implementation of i.v./s.c. bridging strategies to streamline PD-1/PD-L1 inhibitor development, (ii) through co-development with i.v. presentations for anti-severe acute respiratory syndrome-coronavirus 2 antibodies to support rapid deployment of both formulations, (iii) as the lead route for bispecific T cell engagers (BTCEs) to mitigate BTCE-mediated cytokine release syndrome, and (iv) for pediatric patients in the case of dupilumab.

Human GST P1-1 Redesigned for Enhanced Catalytic Activity with the Anticancer Prodrug Telcyta and Improved Thermostability

Protein engineering can be used to tailor enzymes for medical purposes, including antibody-directed enzyme prodrug therapy (ADEPT), which can act as a tumor-targeted alternative to conventional chemotherapy for cancer. In ADEPT, the antibody serves as a vector, delivering a drug-activating enzyme selectively to the tumor site. Glutathione transferases (GSTs) are a family of naturally occurring detoxication enzymes, and the finding that some of them are overexpressed in tumors has been exploited to develop GST-activated prodrugs. The prodrug Telcyta is activated by GST P1-1, which is the GST most commonly elevated in cancer cells, implying that tumors overexpressing GST P1-1 should be particularly vulnerable to Telcyta. Promising antitumor activity has been noted in clinical trials, but the wildtype enzyme has modest activity with Telcyta, and further functional improvement would enhance its usefulness for ADEPT. We utilized protein engineering to construct human GST P1-1 gene variants in the search for enzymes with enhanced activity with Telcyta. The variant Y109H displayed a 2.9-fold higher enzyme activity compared to the wild-type GST P1-1. However, increased catalytic potency was accompanied by decreased thermal stability of the Y109H enzyme, losing 99% of its activity in 8 min at 50 °C. Thermal stability was restored by four additional mutations simultaneously introduced without loss of the enhanced activity with Telcyta. The mutation Q85R was identified as an important contributor to the regained thermostability. These results represent a first step towards a functional ADEPT application for Telcyta.

Extracellular targeted protein degradation: an emerging modality for drug discovery

Targeted protein degradation (TPD) has emerged in the past decade as a major new drug modality to remove intracellular proteins with bispecific small molecules that recruit the protein of interest (POI) to an E3 ligase for degradation in the proteasome. Unlike classic occupancy-based drugs, intracellular TPD (iTPD) eliminates the target and works catalytically, and so can be more effective and sustained, with lower dose requirements. Recently, this approach has been expanded to the extracellular proteome, including both secreted and membrane proteins. Extracellular targeted protein degradation (eTPD) uses bispecific antibodies, conjugates or small molecules to degrade extracellular POIs by trafficking them to the lysosome for degradation. Here, we focus on recent advances in eTPD, covering degrader systems, targets, molecular designs and parameters to advance them. Now almost any protein, intracellular or extracellular, is addressable in principle with TPD.

Two antibodies show broad, synergistic neutralization against SARS-CoV-2 variants by inducing conformational change within the RBD

Continual evolution of the severe acute respiratory syndrome coronavirus (SARS-CoV-2) virus has allowed for its gradual evasion of neutralizing antibodies (nAbs) produced in response to natural infection or vaccination. The rapid nature of these changes has incited a need for the development of superior broad nAbs (bnAbs) and/or the rational design of an antibody cocktail that can protect against the mutated virus strain. Here, we report two angiotensin-converting enzyme 2 competing nAbs-8H12 and 3E2-with synergistic neutralization but evaded by some Omicron subvariants. Cryo-electron microscopy reveals the two nAbs synergistic neutralizing virus through a rigorous pairing permitted by rearrangement of the 472-489 loop in the receptor-binding domain to avoid steric clashing. Bispecific antibodies based on these two nAbs tremendously extend the neutralizing breadth and restore neutralization against recent variants including currently dominant XBB.1.5. Together, these findings expand our understanding of the potential strategies for the neutralization of SARS-CoV-2 variants toward the design of broad-acting antibody therapeutics and vaccines.

Reprogramming natural killer cells for cancer therapy

The last decade has seen rapid development in the field of cellular immunotherapy, particularly in regard to chimeric antigen receptor (CAR)-modified T cells. However, challenges, such as severe treatment-related toxicities and inconsistent quality of autologous products, have hindered the broader use of CAR-T cell therapy, highlighting the need to explore alternative immune cells for cancer targeting. In this regard, natural killer (NK) cells have been extensively studied in cellular immunotherapy and were found to exert cytotoxic effects without being restricted by human leukocyte antigen and have a lower risk of causing graft-versus-host disease; making them favorable for the development of readily available "off-the-shelf" products. Clinical trials utilizing unedited NK cells or reprogrammed NK cells have shown early signs of their effectiveness against tumors. However, limitations, including limited in vivo persistence and expansion potential, remained. To enhance the antitumor function of NK cells, advanced gene-editing technologies and combination approaches have been explored. In this review, we summarize current clinical trials of antitumor NK cell therapy, provide an overview of innovative strategies for reprogramming NK cells, which include improvements in persistence, cytotoxicity, trafficking and the ability to counteract the immunosuppressive tumor microenvironment, and also discuss some potential combination therapies.

Nuclear-import receptors as gatekeepers of pathological phase transitions in ALS/FTD

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are fatal neurodegenerative disorders on a disease spectrum that are characterized by the cytoplasmic mislocalization and aberrant phase transitions of prion-like RNA-binding proteins (RBPs). The common accumulation of TAR DNA-binding protein-43 (TDP-43), fused in sarcoma (FUS), and other nuclear RBPs in detergent-insoluble aggregates in the cytoplasm of degenerating neurons in ALS/FTD is connected to nuclear pore dysfunction and other defects in the nucleocytoplasmic transport machinery. Recent advances suggest that beyond their canonical role in the nuclear import of protein cargoes, nuclear-import receptors (NIRs) can prevent and reverse aberrant phase transitions of TDP-43, FUS, and related prion-like RBPs and restore their nuclear localization and function. Here, we showcase the NIR family and how they recognize cargo, drive nuclear import, and chaperone prion-like RBPs linked to ALS/FTD. We also discuss the promise of enhancing NIR levels and developing potentiated NIR variants as therapeutic strategies for ALS/FTD and related neurodegenerative proteinopathies.

BrainBike peptidomimetic enables efficient transport of proteins across brain endothelium

Protein therapeutics cannot reach the brain in sufficient amounts because of their low permeability across the blood-brain barrier. Here we report a new family of bicyclic peptide shuttles, BrainBikes, capable of increasing transport of proteins, including antibody derivatives, in a human cell-based model of the blood-brain barrier.

Rapid depletion of "catch-and-release" anti-ASGR1 antibody in vivo

Targeting antigens with antibodies exhibiting pH/Ca2+-dependent binding against an antigen is an attractive strategy to mitigate target-mediated disposition and antigen buffering. Studies have reported improved serum exposure of antibodies exhibiting pH/Ca2+-binding against membrane-bound receptors. Asialoglycoprotein receptor 1 (ASGR1) is a membrane-bound receptor primarily localized in hepatocytes. With a high expression level of approximately one million receptors per cell, high turnover, and rapid recycling, targeting this receptor with a conventional antibody is a challenge. In this study, we identified an antibody exhibiting pH/Ca2+-dependent binding to ASGR1 and generated antibody variants with increased binding to neonatal crystallizable fragment receptor (FcRn). Serum exposures of the generated anti-ASGR1 antibodies were analyzed in transgenic mice expressing human FcRn. Contrary to published reports of increased serum exposure of pH/Ca2+-dependent antibodies, the pH/Ca2+-dependent anti-ASGR1 antibody had rapid serum clearance in comparison to a conventional anti-ASGR1 antibody. We conducted sub-cellular trafficking studies of the anti-ASGR1 antibodies along with receptor quantification analysis for mechanistic understanding of the rapid serum clearance of pH/Ca2+-dependent anti-ASGR1 antibody. The findings from our study provide valuable insights in identifying the antigens, especially membrane bound, that may benefit from targeting with pH/Ca2+-dependent antibodies to obtain increased serum exposure.

Modulation of the high concentration viscosity of IgG1 antibodies using clinically validated Fc mutations

The self-association of therapeutic antibodies can result in elevated viscosity and create problems in manufacturing and formulation, as well as limit delivery by subcutaneous injection. The high concentration viscosity of some antibodies has been reduced by variable domain mutations or by the addition of formulation excipients. In contrast, the impact of Fc mutations on antibody viscosity has been minimally explored. Here, we studied the effect of a panel of common and clinically validated Fc mutations on the viscosity of two closely related humanized IgG1, κ antibodies, omalizumab (anti-IgE) and trastuzumab (anti-HER2). Data presented here suggest that both Fab-Fab and Fab-Fc interactions contribute to the high viscosity of omalizumab, in a four-contact model of self-association. Most strikingly, the high viscosity of omalizumab (176 cP) was reduced 10.7- and 2.2-fold by Fc modifications for half-life extension (M252Y:S254T:T256E) and aglycosylation (N297G), respectively. Related single mutations (S254T and T256E) each reduced the viscosity of omalizumab by ~6-fold. An alternative half-life extension Fc mutant (M428L:N434S) had the opposite effect in increasing the viscosity of omalizumab by 1.5-fold. The low viscosity of trastuzumab (8.6 cP) was unchanged or increased by ≤ 2-fold by the different Fc variants. Molecular dynamics simulations provided mechanistic insight into the impact of Fc mutations in modulating electrostatic and hydrophobic surface properties as well as conformational stability of the Fc. This study demonstrates that high viscosity of some IgG1 antibodies can be mitigated by Fc mutations, and thereby offers an additional tool to help design future antibody therapeutics potentially suitable for subcutaneous delivery.

Variable domain mutational analysis to probe the molecular mechanisms of high viscosity of an IgG1 antibody

Subcutaneous injection is the preferred route of administration for many antibody therapeutics for reasons that include its speed and convenience. However, the small volume limit (typically ≤ 2 mL) for subcutaneous delivery often necessitates antibody formulations at high concentrations (commonly ≥100 mg/mL), which may lead to physicochemical problems. For example, antibodies with large hydrophobic or charged patches can be prone to self-interaction giving rise to high viscosity. Here, we combined X-ray crystallography with computational modeling to predict regions of an anti-glucagon receptor (GCGR) IgG1 antibody prone to self-interaction. An extensive mutational analysis was undertaken of the complementarity-determining region residues residing in hydrophobic surface patches predicted by spatial aggregation propensity, in conjunction with residue-level solvent accessibility, averaged over conformational ensembles from molecular dynamics simulations. Dynamic light scattering (DLS) was used as a medium throughput screen for self-interaction of ~ 200 anti-GCGR IgG1 variants. A negative correlation was found between the viscosity determined at high concentration (180 mg/mL) and the DLS interaction parameter measured at low concentration (2-10 mg/mL). Additionally, anti-GCGR variants were readily identified with reduced viscosity and antigen-binding affinity within a few fold of the parent antibody, with no identified impact on overall developability. The methods described here may be useful in the optimization of other antibodies to facilitate their therapeutic administration at high concentration.

Optimization of therapeutic antibodies for reduced self-association and non-specific binding via interpretable machine learning

Antibody development, delivery, and efficacy are influenced by antibody-antigen affinity interactions, off-target interactions that reduce antibody bioavailability and pharmacokinetics, and repulsive self-interactions that increase the stability of concentrated antibody formulations and reduce their corresponding viscosity. Yet identifying antibody variants with optimal combinations of these three types of interactions is challenging. Here we show that interpretable machine-learning classifiers, leveraging antibody structural features descriptive of their variable regions and trained on experimental data for a panel of 80 clinical-stage monoclonal antibodies, can identify antibodies with optimal combinations of low off-target binding in a common physiological-solution condition and low self-association in a common antibody-formulation condition. For three clinical-stage antibodies with suboptimal combinations of off-target binding and self-association, the classifiers predicted variable-region mutations that optimized non-affinity interactions while maintaining high-affinity antibody-antigen interactions. Interpretable machine-learning models may facilitate the optimization of antibody candidates for therapeutic applications.

Collagen Anchoring Protein-Nucleic Acid Chimeric Probe for In Situ In Vivo Mapping of a Tumor-Specific Protease

In situ analysis of biomarkers in the tumor microenvironment (TME) is important to reveal their potential roles in tumor progression and early diagnosis of tumors but remains a challenge. In this work, a bottom-up modular assembly strategy was proposed for a multifunctional protein-nucleic chimeric probe (PNCP) for in situ mapping of cancer-specific proteases. PNCP, containing a collagen anchoring module and a target proteolysis-responsive isothermal amplification sensor module, can be anchored in the collagen-rich TME and respond to the target protease in situ and generate amplified signals through rolling cycle amplification of tandem fluorescent RNAs. Taking matrix metalloproteinase 2 (MMP-2), a tumor-associated protease, as the model, the feasibility of PNCP was demonstrated for the in situ detection of MMP-2 activity in 3D tumor spheroids. Moreover, in situ in vivo mapping of MMP-2 activity was also achieved in a metastatic solid tumor model with high sensitivity, providing a useful tool for evaluating tumor metastasis and distinguishing highly aggressive forms of tumors.

Epitope-engineered human hematopoietic stem cells are shielded from CD123-targeted immunotherapy

Targeted eradication of transformed or otherwise dysregulated cells using monoclonal antibodies (mAb), antibody-drug conjugates (ADC), T cell engagers (TCE), or chimeric antigen receptor (CAR) cells is very effective for hematologic diseases. Unlike the breakthrough progress achieved for B cell malignancies, there is a pressing need to find suitable antigens for myeloid malignancies. CD123, the interleukin-3 (IL-3) receptor alpha-chain, is highly expressed in various hematological malignancies, including acute myeloid leukemia (AML). However, shared CD123 expression on healthy hematopoietic stem and progenitor cells (HSPCs) bears the risk for myelotoxicity. We demonstrate that epitope-engineered HSPCs were shielded from CD123-targeted immunotherapy but remained functional, while CD123-deficient HSPCs displayed a competitive disadvantage. Transplantation of genome-edited HSPCs could enable tumor-selective targeted immunotherapy while rebuilding a fully functional hematopoietic system. We envision that this approach is broadly applicable to other targets and cells, could render hitherto undruggable targets accessible to immunotherapy, and will allow continued posttransplant therapy, for instance, to treat minimal residual disease (MRD).

Intratumoral administration of unconjugated Accum™ impairs the growth of pre-established solid lymphoma tumors

The Accum™ technology was initially designed to enhance the bioaccumulation of a given molecule in target cells. It does so by triggering endosomal membrane damages allowing endocytosed products to enter the cytosol, escaping the harsh environmental cues of the endosomal lumen. In an attempt to minimize manufacturing hurdles associated with Accum™ conjugation, we tested whether free Accum™ admixed with antigens could lead to outcomes similar to those obtained with conjugated products. Surprisingly, unconjugated Accum™ was found to promote cell death in vitro, an observation further confirmed on various murine tumor cell lines (EL4, CT-26, B16, and 4 T1). At the molecular level, unconjugated Accum™ triggers the production of reactive oxygen species and elicits immunogenic cell death while retaining its innate ability to cause endosomal damages. When administered as a monotherapy to animals with pre-established EL4 T-cell lymphoma, Accum™ controlled tumor growth in a dose-dependent manner, and its therapeutic effect relies on CD4 and CD8 T cells. Although unconjugated Accum™ synergizes with various immune checkpoint inhibitors (anti-CTLA4, anti-PD-1, or anti-CD47) at controlling tumor growth, its therapeutic potency could not be further enhanced when combined with all three tested immune checkpoint inhibitors at once due to its dependency on a specific dosing regimen. In sum, we report in this study an unprecedented new function for unconjugated Accum™ as a novel anticancer molecule. These results could pave the path for a new line of investigation aimed at exploring the pro-killing properties of additional Accum™ variants as a mean to develop second-generation anticancer therapeutics.

AI Models for Protein Design are Driving Antibody Engineering

Therapeutic antibody engineering seeks to identify antibody sequences with specific binding to a target and optimized drug-like properties. When guided by deep learning, antibody generation methods can draw on prior knowledge and experimental efforts to improve this process. By leveraging the increasing quantity and quality of predicted structures of antibodies and target antigens, powerful structure-based generative models are emerging. In this review, we tie the advancements in deep learning-based protein structure prediction and design to the study of antibody therapeutics.

Phage display assisted discovery of a pH-dependent anti-α-cobratoxin antibody from a natural variable domain library

Recycling IgG antibodies bind to their target antigen at physiological pH in the blood stream and release them upon endocytosis when pH levels drop, allowing the IgG antibodies to be recycled into circulation via FcRn-mediated cellular pathways, while the antigens undergo lysosomal degradation. This enables recycling antibodies to achieve comparable therapeutic effect at lower doses than their non-recycling counterparts. The development of such antibodies is typically achieved by histidine doping of their variable regions or by performing in vitro antibody selection campaigns utilizing histidine doped libraries. Both are strategies that may introduce sequence liabilities. Here, we present a methodology that employs a naïve antibody phage display library, consisting of natural variable domains, to discover antibodies that bind α-cobratoxin from the venom of Naja kaouthia in a pH-dependent manner. As a result, an antibody was discovered that exhibits a 7-fold higher off-rate at pH 5.5 than pH 7.4 in bio-layer interferometry experiments. Interestingly, no histidine residues were found in its variable domains, and in addition, the antibody showed pH-dependent binding to a histidine-devoid antigen mutant. As such, the results demonstrate that pH-dependent antigen-antibody binding may not always be driven by histidine residues. By employing molecular dynamics simulations, different protonation states of titratable residues were found, which potentially could be responsible for the observed pH-dependent antigen binding properties of the antibody. Finally, given the typically high diversity of naïve antibody libraries, the methodology presented here can likely be applied to discover recycling antibodies against different targets ab initio without the need for histidine doping.

Effects of adding tea tree oil on growth performance, immune function, and intestinal function of broilers

The aim of this study was to investigate the effects of adding tea tree oil (TTO) in the basal diet on growth performance, immune function, and intestinal function in broilers. This study utilized 1,650 one-day-old broilers with good health and similar body weight. Subjects were randomized into 5 groups with 6 replicates each: the control group (CON, basal diet), positive control group (PCG, basal diet + 100 mg/kg oregano oil in diet), low-dose TTO group (TTO-L, 50 mg/kg TTO added in the basal diet), medium-dose TTO group (TTO-M, 100 mg/kg TTO added in the basal diet), and high-dose TTO group (TTO-H, 200 mg/kg TTO added in the basal diet). The whole test period lasted 28 d. The results showed that the broilers fed with TTO supplemented diet had significantly higher body weight and average daily gain (ADG) (P = 0.013), and had a lower feed conversion ratio (F/G) (P = 0.010) throughout the trial period. The index of thymus in TTO-M increased significantly compared to CON (P = 0.015) on d 28. On d 14 and 28, C3, IFN-γ, TNF-α, and IL-2 levels in TTO-L serum were significantly increased (P < 0.001); the 3 test groups supplemented with TTO had significantly higher titers of avian influenza H9 subtype in their serum (P < 0.05). Tea tree oil supplement in the diet also had a positive and significant effect on the intestinal morphology of broilers throughout the experiment (P < 0.05). These results indicate that TTO has the ability to promote broiler growth, regulate immunity, and improve intestinal morphology. The proposed dosage of adding 50 mg/kg in broiler basal diets provides a theoretical basis for its subsequent use in livestock feeds.

Potent antibodies against immune invasive SARS-CoV-2 Omicron subvariants

The development of neutralizing antibodies (nAbs) is an important strategy to tackle the Omicron variant. Omicron N-terminal domain (NTD) mutations including A67V, G142D, and N212I alter the antigenic structure, and mutations in the spike (S) receptor binding domain (RBD), such as N501Y, R346K, and T478K enhance affinity between the RBD and angiotensin-converting enzyme 2 (ACE2), thus conferring Omicron powerful immune evasion. Most nAbs (COV2-2130, ZCB11, REGN10933) and combinations of nAbs (COV2-2196 + COV2-2130, REGN10933 + REGN10987, Brii-196 + Brii-198) have either greatly reduced or lost their neutralizing ability against Omicron, but several nAbs such as SA55, SA58, S309, LY-CoV1404 are still effective in neutralizing most Omicron subvariants. This paper focuses on Omicron subvariants mutations and mechanisms of current therapeutic antibodies that remain efficacious against Omicron subvariants, which will guide us in exploring a new generation of broad nAbs as key therapeutics to tackle SARS-CoV-2 and accelerate the exploration of novel clinical antiviral reagents.

Position-Specific Enrichment Ratio Matrix scores predict antibody variant properties from deep sequencing data

MOTIVATION

Deep sequencing of antibody and related protein libraries after phage or yeast-surface display sorting is widely used to identify variants with increased affinity, specificity, and/or improvements in key biophysical properties. Conventional approaches for identifying optimal variants typically use the frequencies of observation in enriched libraries or the corresponding enrichment ratios. However, these approaches disregard the vast majority of deep sequencing data and often fail to identify the best variants in the libraries.

RESULTS

Here, we present a method, Position-Specific Enrichment Ratio Matrix (PSERM) scoring, that uses entire deep sequencing datasets from pre- and post-selections to score each observed protein variant. The PSERM scores are the sum of the site-specific enrichment ratios observed at each mutated position. We find that PSERM scores are much more reproducible and correlate more strongly with experimentally measured properties than frequencies or enrichment ratios, including for multiple antibody properties (affinity and non-specific binding) for a clinical-stage antibody (emibetuzumab). We expect that this method will be broadly applicable to diverse protein engineering campaigns.

AVAILABILITY AND IMPLEMENTATION

All deep sequencing datasets and code to perform the analyses presented within are available via https://github.com/Tessier-Lab-UMich/PSERM_paper.

Optimization of a Glucagon-Like Peptide 1 Receptor Antagonist Antibody for Treatment of Hyperinsulinism

Congenital hyperinsulinism (HI) is a genetic disorder in which pancreatic β-cell insulin secretion is excessive and results in hypoglycemia that, without treatment, can cause brain damage or death. Most patients with loss-of-function mutations in ABCC8 and KCNJ11, the genes encoding the β-cell ATP-sensitive potassium channel (KATP), are unresponsive to diazoxide, the only U.S. Food and Drug Administration-approved medical therapy and require pancreatectomy. The glucagon-like peptide 1 receptor (GLP-1R) antagonist exendin-(9-39) is an effective therapeutic agent that inhibits insulin secretion in both HI and acquired hyperinsulinism. Previously, we identified a highly potent antagonist antibody, TB-001-003, which was derived from our synthetic antibody libraries that were designed to target G protein-coupled receptors. Here, we designed a combinatorial variant antibody library to optimize the activity of TB-001-003 against GLP-1R and performed phage display on cells overexpressing GLP-1R. One antagonist, TB-222-023, is more potent than exendin-(9-39), also known as avexitide. TB-222-023 effectively decreased insulin secretion in primary isolated pancreatic islets from a mouse model of hyperinsulinism, Sur1-/- mice, and in islets from an infant with HI, and increased plasma glucose levels and decreased the insulin to glucose ratio in Sur1-/- mice. These findings demonstrate that targeting GLP-1R with an antibody antagonist is an effective and innovative strategy for treatment of hyperinsulinism.

ARTICLE HIGHLIGHTS

Patients with the most common and severe form of diazoxide-unresponsive congenital hyperinsulinism (HI) require a pancreatectomy. Other second-line therapies are limited in their use because of severe side effects and short half-lives. Therefore, there is a critical need for better therapies. Studies with the glucagon-like peptide 1 receptor (GLP-1R) antagonist, avexitide (exendin-(9-39)), have demonstrated that GLP-1R antagonism is effective at lowering insulin secretion and increasing plasma glucose levels. We have optimized a GLP-1R antagonist antibody with more potent blocking of GLP-1R than avexitide. This antibody therapy is a potential novel and effective treatment for HI.

Revolutionizing antiviral therapy with nanobodies: Generation and prospects

As the world continues to grapple with infectious diseases, scientists are constantly searching for effective ways to combat these deadly pathogens. One promising avenue of research is the use of nanobodies as neutralization agents. These small proteins, derived from camelid antibodies, have several unique advantages over traditional antibodies, including their small size. Nanobodies are much smaller than conventional antibodies, typically weighing in at around 15 kDa compared to the 150 kDa of a typical human antibody. This small size allows them to penetrate into tight spaces that larger molecules cannot reach, such as the crevices on the surface of viruses or bacteria. This makes them highly effective at neutralizing viruses by binding to and blocking their key functional sites. In this mini-review we discuss the construction approaches of nanobodies, and some methods to increase the half-life of nanobodies. Moreover, we discuss Nanobodies and their therapeutic potential for infectious agents.

Profiling the Biophysical Developability Properties of Common IgG1 Fc Effector Silencing Variants

Therapeutic antibodies represent the most significant modality in biologics, with around 150 approved drugs on the market. In addition to specific target binding mediated by the variable fragments (Fvs) of the heavy and light chains, antibodies possess effector functions through binding of the constant region (Fc) to Fcγ receptors (FcγR), which allow immune cells to attack and kill target cells using a variety of mechanisms. However, for some applications, including T-cell-engaging bispecifics, this effector function is typically undesired. Mutations within the lower hinge and the second constant domain (CH2) of IgG1 that comprise the FcγR binding interface reduce or eliminate effector function ("Fc silencing") while retaining binding to the neonatal Fc receptor (FcRn), important for normal antibody pharmacokinetics (PKs). Comprehensive profiling of biophysical developability properties would benefit the choice of constant region variants for development. Here, we produce a large panel of representative mutations previously described in the literature and in many cases in clinical or approved molecules, generate select combinations thereof, and characterize their binding and biophysical properties. We find that some commonly used CH2 mutations, including D265A and P331S, are effective in reducing binding to FcγR but significantly reduce stability, promoting aggregation, particularly under acidic conditions commonly employed in manufacturing. We highlight mutation sets that are particularly effective for eliminating Fc effector function with the retention of WT-like stability, including L234A, L235A, and S267K (LALA-S267K), L234A, L235E, and S267K (LALE-S267K), L234A, L235A, and P329A (LALA-P329A), and L234A, L235E, and P329G (LALE-P329G).

Identification of immunogenic cell death-related signature on prognosis and immunotherapy in kidney renal clear cell carcinoma

Background

Immunogenic cell death (ICD) is considered a particular cell death modality of regulated cell death (RCD) and plays a significant role in various cancers. The connection between kidney renal clear cell carcinoma (KIRC) and ICD remains to be thoroughly explored.

Methods

We conducted a variety of bioinformatics analyses using R software, including cluster analysis, prognostic analysis, enrichment analysis and immune infiltration analysis. In addition, we performed Quantitative Real-time PCR to evaluate RNA levels of specific ICD genes. The proliferation was measured through Cell Counting Kit-8 (CCK-8) assay and colony-formation assay in RCC cell lines.

Results

We determined two ICD subtypes through consensus clustering analysis. The two subtypes showed significantly different clinical outcomes, genomic alterations and tumor immune microenvironment. Moreover, we constructed the ICD prognostic signature based on TF, FOXP3, LY96, SLC7A11, HSP90AA1, UCN, IFNB1 and TLR3 and calculated the risk score for each patient. Kaplan-Meier survival analysis and ROC curve demonstrated that patients in the high-risk group had significantly poorer prognosis compared with the low-risk group. We then validated the signature through external cohort and further evaluated the relation between the signature and clinical features, tumor immune microenvironment and immunotherapy response. Given its critical role in ICD, we conducted further analysis on LY96. Our results indicated that downregulation of LY96 inhibited the proliferation ability of RCC cells.

Conclusions

Our research revealed the underlying function of ICD in KIRC and screened out a potential biomarker, which provided a novel insight into individualized immunotherapy in KIRC.

Ssa1-targeted antibody prevents host invasion by Candida albicans

INTRODUCTION

Candida albicans is a commensal fungus that colonizes most healthy individuals' skin and mucosal surfaces but can also cause life-threatening invasive infections, particularly in immunocompromised patients. Despite antifungal treatment availability, drug resistance is increasing, and mortality rates remain unacceptably high. Heat shock protein Ssa1, a conserved member of the Hsp70 family in yeast, is a novel invasin that binds to host cell cadherins, induces host cell endocytosis, and enables C. albicans to cause maximal damage to host cells and induces disseminated and oropharyngeal disease.

RESULT

Here we discovered a mouse monoclonal antibody (mAb 13F4) that targeting C. albicans Ssa1 with high affinity (EC50 = 39.78 ng/mL). mAb 13F4 prevented C. albicans from adhering to and invading human epithelial cells, displayed antifungal activity, and synergized with fluconazole in proof of concept in vivo studies. mAb 13F4 significantly prolonged the survival rate of the hematogenous disseminated candidiasis mice to 75%. We constructed a mAb 13F4 three-dimensional structure using homology modeling methods and found that the antigen-binding fragment (Fab) interacts with the Ssa1 N-terminus.

DISCUSSION

These results suggest that blocking Ssa1 cell surface function may effectively control invasive C. albicans infections and provide a potential new treatment strategy for invasive fungal infections.

Position-Specific Enrichment Ratio Matrix scores predict antibody variant properties from deep sequencing data

Motivation

Deep sequencing of antibody and related protein libraries after phage or yeast-surface display sorting is widely used to identify variants with increased affinity, specificity and/or improvements in key biophysical properties. Conventional approaches for identifying optimal variants typically use the frequencies of observation in enriched libraries or the corresponding enrichment ratios. However, these approaches disregard the vast majority of deep sequencing data and often fail to identify the best variants in the libraries.

Results

Here, we present a method, Position-Specific Enrichment Ratio Matrix (PSERM) scoring, that uses entire deep sequencing datasets from pre- and post-selections to score each observed protein variant. The PSERM scores are the sum of the site-specific enrichment ratios observed at each mutated position. We find that PSERM scores are much more reproducible and correlate more strongly with experimentally measured properties than frequencies or enrichment ratios, including for multiple antibody properties (affinity and non-specific binding) for a clinical-stage antibody (emibetuzumab). We expect that this method will be broadly applicable to diverse protein engineering campaigns.

Availability

All deep sequencing datasets and code to do the analyses presented within are available via GitHub.

Contact

Peter Tessier, ptessier@umich.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Alpaca single B cell interrogation and heavy-chain-only antibody discovery on an optofluidic platform

In vivo VHH discovery approaches have been limited by the lack of methodologies for camelid B cell interrogation. Here, we report a novel application of the Beacon® optofluidic platform to the discovery of heavy-chain-only antibodies by screening alpaca B cells. Methods for alpaca B cell enrichment, culture, IgG2/3 detection, and sequencing were developed and used to discover target-specific VHH from an alpaca immunized with prostate-specific membrane antigen (PSMA) or a second target. PSMA-specific hits were expressed as VHH-Fc and characterized using label-free techniques. Anti-PSMA IgG2/3 titer plateaued on day 153, when on-Beacon IgG2/3 secretion and target binding rates peaked. Of 13 recombinantly expressed VHH-Fc, all but one bound with nanomolar affinity, and five were successfully humanized. Repertoire sequencing uncovered additional variants within the clonal lineages of the validated hits. The establishment of this workflow extends the powerful Beacon technology to enable rapid VHH discovery directly from natural camelid immune repertoires.

A mammalian cell display platform based on scFab transposition

In vitro display technologies have been successfully utilized for the discovery and evolution of monoclonal antibodies (mAbs) for diagnostic and therapeutic applications, with phage display and yeast display being the most commonly used platforms due to their simplicity and high efficiency. As their prokaryotic or lower eukaryotic host organisms typically have no or different post-translational modifications, several mammalian cell-based display and screening technologies for isolation and optimization of mAbs have emerged and are being developed. We report here a novel and useful mammalian cell display platform based on the PiggyBac transposon system to display mAbs in a single-chain Fab (scFab) format on the surface of HEK293F cells. Immune rabbit antibody libraries encompassing ~7 × 107 independent clones were generated in an all-in-one transposon vector, stably delivered into HEK293F cells and displayed as an scFab with rabbit variable and human constant domains. After one round of magnetic activated cell sorting and two rounds of fluorescence activated cell sorting, mAbs with high affinity in the subnanomolar range and cross-reactivity to the corresponding human and mouse antigens were identified, demonstrating the power of this platform for antibody discovery. We developed a highly efficient mammalian cell display platform based on the PiggyBac transposon system for antibody discovery, which could be further utilized for humanization as well as affinity and specificity maturation.

Can the new adipokine asprosin be a metabolic troublemaker for cardiovascular diseases? A state-of-the-art review

Adipokines play a significant role in cardiometabolic diseases. Asprosin, a newly discovered adipokine, was first identified as a glucose-raising protein hormone. Asprosin also stimulates appetite and regulates glucose and lipid metabolism. Its identified receptors so far include Olfr734 and Ptprd. Clinical studies have found that asprosin may be associated with cardiometabolic diseases. Asprosin may have diagnostic and therapeutic potential in obesity, diabetes, metabolic syndrome and atherosclerotic cardiovascular diseases. Herein, the structure, receptors, and functions of asprosin and its relationship with cardiometabolic diseases are summarized based on recent findings.

Reprogramming human B cells with custom heavy chain antibodies

We describe a genome editing strategy to reprogram the immunoglobulin heavy chain (IgH) locus of human B cells to express custom molecules that respond to immunization. These heavy chain antibodies (HCAbs) comprise a custom antigen-recognition domain linked to an Fc domain derived from the IgH locus and can be differentially spliced to express either B cell receptor (BCR) or secreted antibody isoforms. The HCAb editing platform is highly flexible, supporting antigen-binding domains based on both antibody and non-antibody components, and also allowing alterations in the Fc domain. Using HIV Env protein as a model antigen, we show that B cells edited to express anti-Env HCAbs support the regulated expression of both BCRs and antibodies, and respond to Env antigen in a tonsil organoid model of immunization. In this way, human B cells can be reprogrammed to produce customized therapeutic molecules with the potential for in vivo amplification.

The Dawn of a New Era: Targeting the "Undruggables" with Antibody-Based Therapeutics

The high selectivity and affinity of antibodies toward their antigens have made them a highly valuable tool in disease therapy, diagnosis, and basic research. A plethora of chemical and genetic approaches have been devised to make antibodies accessible to more "undruggable" targets and equipped with new functions of illustrating or regulating biological processes more precisely. In this Review, in addition to introducing how naked antibodies and various antibody conjugates (such as antibody-drug conjugates, antibody-oligonucleotide conjugates, antibody-enzyme conjugates, etc.) work in therapeutic applications, special attention has been paid to how chemistry tools have helped to optimize the therapeutic outcome (i.e., with enhanced efficacy and reduced side effects) or facilitate the multifunctionalization of antibodies, with a focus on emerging fields such as targeted protein degradation, real-time live-cell imaging, catalytic labeling or decaging with spatiotemporal control as well as the engagement of antibodies inside cells. With advances in modern chemistry and biotechnology, well-designed antibodies and their derivatives via size miniaturization or multifunctionalization together with efficient delivery systems have emerged, which have gradually improved our understanding of important biological processes and paved the way to pursue novel targets for potential treatments of various diseases.

Study on antibody Fc-glycosylation for optimal effector functions

A comprehensive structure-activity relationship study on antibody Fc-glycosylation has been performed using the chimeric anti-SSEA4 antibody chMC813-70 as a model. The α-2,6 sialylated biantennary complex type glycan was identified as the optimal Fc-glycan with significant enhancement in antibody effector functions, including binding to different Fc receptors and ADCC.

Automated optimisation of solubility and conformational stability of antibodies and proteins

Biologics, such as antibodies and enzymes, are crucial in research, biotechnology, diagnostics, and therapeutics. Often, biologics with suitable functionality are discovered, but their development is impeded by developability issues. Stability and solubility are key biophysical traits underpinning developability potential, as they determine aggregation, correlate with production yield and poly-specificity, and are essential to access parenteral and oral delivery. While advances for the optimisation of individual traits have been made, the co-optimization of multiple traits remains highly problematic and time-consuming, as mutations that improve one property often negatively impact others. In this work, we introduce a fully automated computational strategy for the simultaneous optimisation of conformational stability and solubility, which we experimentally validate on six antibodies, including two approved therapeutics. Our results on 42 designs demonstrate that the computational procedure is highly effective at improving developability potential, while not affecting antigen-binding. We make the method available as a webserver at www-cohsoftware.ch.cam.ac.uk.

Artificial intelligence in cancer immunotherapy: Applications in neoantigen recognition, antibody design and immunotherapy response prediction

Cancer immunotherapy is a method of controlling and eliminating tumors by reactivating the body's cancer-immunity cycle and restoring its antitumor immune response. The increased availability of data, combined with advancements in high-performance computing and innovative artificial intelligence (AI) technology, has resulted in a rise in the use of AI in oncology research. State-of-the-art AI models for functional classification and prediction in immunotherapy research are increasingly used to support laboratory-based experiments. This review offers a glimpse of the current AI applications in immunotherapy, including neoantigen recognition, antibody design, and prediction of immunotherapy response. Advancing in this direction will result in more robust predictive models for developing better targets, drugs, and treatments, and these advancements will eventually make their way into the clinical setting, pushing AI forward in the field of precision oncology.