mAbs最新文献

Prenatal administration of monoclonal antibodies (mAbs) is a strategy that could be exploited to prevent viral infections during pregnancy and early life. To reach protective levels in fetuses, mAbs must be transported across the placenta, a selective barrier that actively and specifically promotes the transfer of antibodies (Abs) into the fetus through the neonatal Fc receptor (FcRn). Because FcRn also regulates Ab half-life, Fc mutations like the M428L/N434S, commonly known as LS mutations, and others have been developed to enhance binding affinity to FcRn and improve drug pharmacokinetics. We hypothesized that these FcRn-enhancing mutations could similarly affect the delivery of therapeutic Abs to the fetus. To test this hypothesis, we measured the transplacental transfer of leronlimab, an anti-CCR5 mAb, in clinical development for preventing HIV infections, using pregnant rhesus macaques to model in utero mAb transfer. We also generated a stabilized and FcRn-enhanced form of leronlimab, termed leronlimab-PLS. Leronlimab-PLS maintained higher levels within the maternal compartment while also reaching higher mAb levels in the fetus and newborn circulation. Further, a single dose of leronlimab-PLS led to complete CCR5 receptor occupancy in mothers and newborns for almost a month after birth. These findings support the optimization of FcRn interactions in mAb therapies designed for administration during pregnancy.

Cachexia is a complicated metabolic syndrome mainly associated with cancers, characterized by extreme weight loss and muscle wasting. It is a debilitating condition that negatively affects prognosis and survival. However, there is currently no effective pharmacological intervention that can reverse body weight loss and improve physical performance in patients with cachexia. Growth differentiation factor 15 (GDF15) can suppress appetite and regulate energy balance through binding to glial cell-derived neurotrophic factor receptor alpha-like (GFRAL). In order to develop a novel, effective treatment for cachexia, we generated a GDF15-targeting VHH nanobody, GB18-06, that was able to bind GDF15 with high affinity. In vitro, GB18-06 potently inhibited the GDF15-GFRAL signaling pathway, leading to a reduction of downstream ERK and AKT phosphorylation levels; in vivo, GB18-06 alleviated weight loss (>20%) in cancer and chemotherapy-induced cachexia models in mice. Compared with the control (phosphate-buffered saline) group, the ambulatory activity of mice in the GB18-06-treated group also increased 77%. Furthermore, GB18-06 exhibited desirable pharmacokinetic properties and an excellent developability profile. Our study has demonstrated a means of developing targeted treatment for cachexia with high efficacy, potentially leading to improved clinical outcomes and quality of life for patients with cachexia.

Protein formulation development relies on the selection of excipients that inhibit protein-protein interactions preventing aggregation. Empirical strategies involve screening many excipient and buffer combinations by physicochemical characterization using forced degradation or temperature-induced stress, mostly under accelerated conditions. Such methods do not readily provide information on the inter- and intramolecular interactions responsible for the effects of excipients. Here, we describe a combined experimental and computational approach for investigating the effect of protein-excipient interactions on formulation stability, which allows the identification of preferential interaction sites and thus can aid in the selection of excipients to be experimentally screened. Model systems composed of two marketed therapeutic IgG1 monoclonal antibodies with identical Fc domain sequences, trastuzumab and omalizumab, were investigated with commonly used excipients arginine, glutamate, and equimolar arginine/glutamate mixtures. Protein-excipient interactions were studied using all-atom molecular dynamics (MD) simulations, which show accumulation of the excipients at specific antibody regions. Preferential excipient-interaction sites were particularly found for charged and aromatic residues and in the complementary-determining regions, with more pronounced arginine contacts for omalizumab than trastuzumab. These computational findings are in line with the more pronounced stabilizing effects of arginine observed in the long-term storage stability study. Furthermore, the aggregation and solubility propensity predicted by commonly used in silico tools do not align with the preferential excipient-interaction sites identified by the MD simulations, suggesting that different physicochemical mechanisms are at play.

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.

Rabbits produce robust antibody responses and have unique features in their antibody repertoire that make them an attractive alternative to rodents for in vivo discovery. However, the frequent occurrence of a non-canonical disulfide bond between complementarity-determining region (CDR) H1 (C35a) and CDRH2 (C50) is often seen as a liability for therapeutic antibody development, despite limited reports of its effect on antibody binding, function, and stability. Here, we describe the discovery and humanization of a human-mouse cross-reactive anti-programmed cell death 1 (PD-1) monoclonal rabbit antibody, termed h1340.CC, which possesses this non-canonical disulfide bond. Initial removal of the non-canonical disulfide resulted in a loss of PD-1 affinity and cross-reactivity, which led us to explore protein engineering approaches to recover these. First, guided by the sequence of a related clone and the crystal structure of h1340.CC in complex with PD-1, we generated variant h1340.SA.LV with a potency and cross-reactivity similar to h1340.CC, but only partially recovered affinity. Side-by-side developability assessment of both h1340.CC and h1340.SA.LV indicate that they possess similar, favorable properties. Next, and prompted by recent developments in machine learning (ML)-guided protein engineering, we used an unbiased ML- and structure-guided approach to rapidly and efficiently generate a different variant with recovered affinity. Our case study thus indicates that, while the non-canonical inter-CDR disulfide bond found in rabbit antibodies does not necessarily constitute an obstacle to therapeutic antibody development, combining structure- and ML-guided approaches can provide a fast and efficient way to improve antibody properties and remove potential liabilities.

The surge in the clinical use of therapeutic antibodies has reshaped the landscape of pharmaceutical therapy for many diseases, including rare and challenging conditions. However, the administration of exogenous biologics could potentially trigger unwanted immune responses such as generation of anti-drug antibodies (ADAs). Real-world experiences have illuminated the clear correlation between the ADA occurrence and unsatisfactory therapeutic outcomes as well as immune-related adverse events. By retrospectively examining research involving immunogenicity analysis, we noticed the growing emphasis on elucidating the immunogenic epitope profiles of antibody-based therapeutics aiming for mechanistic understanding the immunogenicity generation and, ideally, mitigating the risks. As such, we have comprehensively summarized here the progress in both experimental and computational methodologies for the characterization of T and B cell epitopes of therapeutics. Furthermore, the successful practice of epitope-driven deimmunization of biotherapeutics is exceptionally highlighted in this article.

In silico immunogenicity risk assessment has been an important step in the development path for many biologic therapeutics, including monoclonal antibodies. Even if the source of a given biologic is 'fully human', T cell epitopes that are contained in the sequences of the biologic may activate the immune system, enabling the development of anti-drug antibodies that can reduce drug efficacy and may contribute to adverse events. Computational tools that identify T cell epitopes from primary amino acid sequences have been used to assess the immunogenic potential of therapeutic candidates for several decades. To facilitate larger scale analyses and accelerate preclinical immunogenicity risk assessment, our group developed an integrated web-based platform called ISPRI, (Immunogenicity Screening and Protein Re-engineering Interface) that provides hands-on access through a secure web-based interface for scientists working in large and mid-sized biotech companies in the US, Europe, and Japan. This toolkit has evolved and now contains an array of algorithms that can be used individually and/or consecutively for immunogenicity assessment and protein engineering. Most analyses start with the advanced epitope mapping tool (EpiMatrix), then proceed to identify epitope clusters using ClustiMer, and then use a tool called JanusMatrix to define whether any of the T cell epitope clusters may generate a regulatory T cell response which may diminish or eliminate anti-drug antibody formation. Candidates can be compared to similar products on a normalized immunogenicity scale. Should modifications to the biologic sequence be an option, a tool for moderating putative immunogenicity by editing T cell epitopes out of the sequence is available (OptiMatrix). Although this perspective discusses the in-silico immunogenicity risk assessment for monoclonal antibodies, bi-specifics, multi-specifics, and antibody-drug conjugates, the analysis of additional therapeutic modalities such as enzyme replacement proteins, blood factor proteins, CAR-T, gene therapy products, and peptide drugs is also made available on the ISPRI platform.

The development of specific, safe, and potent monoclonal antibodies (Abs) has led to novel therapeutic options for infectious disease. In addition to preventing viral infection through neutralization, Abs can clear infected cells and induce immunomodulatory functions through engagement of their crystallizable fragment (Fc) with complement proteins and Fc receptors on immune cells. Little is known about the role of Fc effector functions of neutralizing Abs in the context of encephalitic alphavirus infection. To determine the role of Fc effector function in therapeutic efficacy against Venezuelan equine encephalitis virus (VEEV), we compared the potently neutralizing anti-VEEV human IgG F5 (hF5) Ab with intact Fc function (hF5-WT) or containing the loss of function Fc mutations L234A and L235A (hF5-LALA) in the context of VEEV infection. We observed significantly reduced binding to complement and Fc receptors, as well as differential in vitro kinetics of Fc-mediated cytotoxicity for hF5-LALA compared to hF5-WT. The in vivo efficacy of hF5-LALA was comparable to hF5-WT at -24 and + 24 h post infection, with both Abs providing high levels of protection. However, when hF5-WT and hF5-LALA were administered + 48 h post infection, there was a significant decrease in the therapeutic efficacy of hF5-LALA. Together these results demonstrate that optimal therapeutic Ab treatment of VEEV, and possibly other encephalitic alphaviruses, requires neutralization paired with engagement of immune effectors via the Fc region.

Over the past two decades, therapeutic antibodies have emerged as a rapidly expanding domain within the field of biologics. In silico tools that can streamline the process of antibody discovery and optimization are critical to support a pipeline that is growing more numerous and complex every year. High-quality structural information remains critical for the antibody optimization process, but antibody-antigen complex structures are often unavailable and in silico antibody docking methods are still unreliable. In this study, DeepAb, a deep learning model for predicting antibody Fv structure directly from sequence, was used in conjunction with single-point experimental deep mutational scanning (DMS) enrichment data to design 200 potentially optimized variants of an anti-hen egg lysozyme (HEL) antibody. We sought to determine whether DeepAb-designed variants containing combinations of beneficial mutations from the DMS exhibit enhanced thermostability and whether this optimization affected their developability profile. The 200 variants were produced through a robust high-throughput method and tested for thermal and colloidal stability (T_onset, T_m, T_agg), affinity (K_D) relative to the parental antibody, and for developability parameters (nonspecific binding, aggregation propensity, self-association). Of the designed clones, 91% and 94% exhibited increased thermal and colloidal stability and affinity, respectively. Of these, 10% showed a significantly increased affinity for HEL (5- to 21-fold increase) and thermostability (>2.5C increase in T_m1), with most clones retaining the favorable developability profile of the parental antibody. Additional in silico tests suggest that these methods would enrich for binding affinity even without first collecting experimental DMS measurements. These data open the possibility of in silico antibody optimization without the need to predict the antibody-antigen interface, which is notoriously difficult in the absence of crystal structures.

A sensitive and specific bioanalytical method was required to measure the exposure of a LAGA-mutated surrogate mouse IgG2a monoclonal antibody in mouse plasma, but the lack of highly specific reagents for the LAGA mutant hindered the development of a ligand-binding assay. Equally problematic is that no sensitive unique tryptic peptides suitable for quantitative mass spectrometric analysis could be identified in the mIgG2a complementarity-determining regions. To overcome these challenges, a trypsin alternative pepsin, an aspartic protease, was systematically investigated for its use in digesting the mutated mIgG2a antibody to allow generation of signature peptides for the bioanalytical quantification purpose. After a series of evaluations, a rapid one-hour pepsin digestion protocol was established for the mutated Fc backbone. Consequently, a new pepsin digestion-based liquid chromatography-tandem mass spectrometry (LC/MS/MS) method was successfully developed to support the mouse pharmacokinetic (PK) sample analysis. In brief, robust and reproducible C-terminal cleavage of both leucine and phenylalanine near the double mutation site of the mutated mIgG2a was accomplished at pH ≤2 and 37°C. Combined with a commercially available rat anti-mIgG2a heavy-chain antibody, the established immunoaffinity LC/MS/MS assay achieved a limit of quantitation of 20 ng/mL in the dynamic range of interest with satisfactory assay precision and accuracy. The successful implementation of this novel approach in discovery PK studies eliminates the need for tedious and costly generation of specific immunocapturing reagents for the LAGA mutants. The approach should be widely applicable for developing popular LAGA mutant-based biological therapeutics.