Tozorakimab (MEDI3506): an anti-IL-33 antibody that inhibits IL-33 signalling via ST2 and RAGE/EGFR to reduce inflammation and epithelial dysfunction.

Interleukin (IL)-33 is a broad-acting alarmin cytokine that can drive inflammatory responses following tissue damage or infection and is a promising target for treatment of inflammatory disease. Here, we describe the identification of tozorakimab (MEDI3506), a potent, human anti-IL-33 monoclonal antibody, which can inhibit reduced IL-33 (IL-33red) and oxidized IL-33 (IL-33ox) activities through distinct serum-stimulated 2 (ST2) and receptor for advanced glycation end products/epidermal growth factor receptor (RAGE/EGFR complex) signalling pathways. We hypothesized that a therapeutic antibody would require an affinity higher than that of ST2 for IL-33, with an association rate greater than 107 M-1 s-1, to effectively neutralize IL-33 following rapid release from damaged tissue. An innovative antibody generation campaign identified tozorakimab, an antibody with a femtomolar affinity for IL-33red and a fast association rate (8.5 × 107 M-1 s-1), which was comparable to soluble ST2. Tozorakimab potently inhibited ST2-dependent inflammatory responses driven by IL-33 in primary human cells and in a murine model of lung epithelial injury. Additionally, tozorakimab prevented the oxidation of IL-33 and its activity via the RAGE/EGFR signalling pathway, thus increasing in vitro epithelial cell migration and repair. Tozorakimab is a novel therapeutic agent with a dual mechanism of action that blocks IL-33red and IL-33ox signalling, offering potential to reduce inflammation and epithelial dysfunction in human disease.

Characterization of Citrullination Sites in Neutrophils and Mast Cells Activated by Ionomycin via Integration of Mass Spectrometry and Machine Learning.

Citrullination is an important post-translational modification implicated in many diseases including rheumatoid arthritis (RA), Alzheimer's disease, and cancer. Neutrophil and mast cells have different expression profiles for protein-arginine deiminases (PADs), and ionomycin-induced activation makes them an ideal cellular model to study proteins susceptible to citrullination. We performed high-resolution mass spectrometry and stringent data filtration to identify citrullination sites in neutrophil and mast cells treated with and without ionomycin. We identified a total of 833 validated citrullination sites on 395 proteins. Several of these citrullinated proteins are important components of pathways involved in innate immune responses. Using this benchmark primary sequence data set, we developed machine learning models to predict citrullination in neutrophil and mast cell proteins. We show that our models predict citrullination likelihood with 0.735 and 0.766 AUCs (area under the receiver operating characteristic curves), respectively, on independent validation sets. In summary, this study provides the largest number of validated citrullination sites in neutrophil and mast cell proteins. The use of our novel motif analysis approach to predict citrullination sites will facilitate the discovery of novel protein substrates of protein-arginine deiminases (PADs), which may be key to understanding immunopathologies of various diseases.

Oxidation of the alarmin IL-33 regulates ST2-dependent inflammation.

In response to infections and irritants, the respiratory epithelium releases the alarmin interleukin (IL)-33 to elicit a rapid immune response. However, little is known about the regulation of IL-33 following its release. Here we report that the biological activity of IL-33 at its receptor ST2 is rapidly terminated in the extracellular environment by the formation of two disulphide bridges, resulting in an extensive conformational change that disrupts the ST2 binding site. Both reduced (active) and disulphide bonded (inactive) forms of IL-33 can be detected in lung lavage samples from mice challenged with Alternaria extract and in sputum from patients with moderate-severe asthma. We propose that this mechanism for the rapid inactivation of secreted IL-33 constitutes a 'molecular clock' that limits the range and duration of ST2-dependent immunological responses to airway stimuli. Other IL-1 family members are also susceptible to cysteine oxidation changes that could regulate their activity and systemic exposure through a similar mechanism.

A novel IgE-neutralizing antibody for the treatment of severe uncontrolled asthma.

The critical role played by IgE in allergic asthma is well-documented and clinically precedented, but some patients in whom IgE neutralization may still offer clinical benefit are excluded from treatment with the existing anti-IgE therapy, omalizumab, due to high total IgE levels or body mass. In this study, we sought to generate a novel high affinity anti-IgE antibody (MEDI4212) with potential to treat a broad severe asthma patient population. Analysis of body mass, total and allergen-specific IgE levels in a cohort of severe asthmatics was used to support the rationale for development of a high affinity IgE-targeted antibody therapeutic. Phage display technology was used to generate a human IgG1 lead antibody, MEDI4212, which was characterized in vitro using binding, signaling and functional assay systems. Protein crystallography was used to determine the details of the interaction between MEDI4212 and IgE. MEDI4212 bound human IgE with an affinity of 1.95 pM and was shown to target critical residues in the IgE Cε3 domain critical for interaction with FcεRI. MEDI4212 potently inhibited responses through FcεRI and also prevented the binding of IgE to CD23. When used ex vivo at identical concentration, MEDI4212 depleted free-IgE from human sera to levels ~1 log lower than omalizumab. Our results thus indicate that MEDI4212 is a novel, high affinity antibody that binds specifically to IgE and prevents IgE binding to its receptors. MEDI4212 effectively depleted free-IgE from human sera ex vivo to a level (1 IU/mL) anticipated to provide optimal IgE suppression in severe asthma patients.

High-precision, high-throughput stability determinations facilitated by robotics and a semiautomated titrating fluorometer.

The use of statistical modeling to test hypotheses concerning the determinants of protein structure requires stability data (e.g., the free energy of denaturation in H(2)O, DeltaG(HOH)) from hundreds of protein mutants. Fluorescence-monitored chemical denaturation provides a convenient method for high-precision, high-throughput DeltaG(HOH) determination. For eglin c we find that a throughput of about 20 min per protein can be attained in a two-channel semiautomated titrating fluorometer. We find also that the use of robotics for protein purification and preparation of the solutions for chemical denaturation gives highly precise DeltaG(HOH) values in which the standard deviation of values from multiple preparations (+/-0.051 kcal/mol) differs very little from multiple measurements from a single preparation (+/-0.040 kcal/mol). Since the variance introduced into model fitting by DeltaG(HOH) increases as the square of measurement error, there is a premium on precision. In fact, the fraction of stability behavior explicable by otherwise perfect models goes from 98% to only 50% over the error range commonly reported for chemical denaturation measurements (0.1-0.6 kcal/mol). We have found that the precision of chemical denaturation DeltaG(HOH) measurements depends most heavily on the precision of the instrument used, followed by protein purity and the capacity to precisely prepare the solutions used for titrations.

Testing hypotheses about determinants of protein structure with high-precision, high-throughput stability measurements and statistical modeling.

Statistical modeling provides the mathematics to use data from large numbers of mutant proteins to generate information about hypotheses concerning protein structure not easily obtained from anecdotal studies on small numbers of mutants. Here we use the unfolding free energies of 303 unique eglin c mutant proteins obtained from high-precision, high-throughput chemical denaturation measurements to assess models concerning helix stability. A model with helix propensity as the sole determinant of stability accounts for 83% of the mutant-to-mutant variation in stability for 99% of the mutant proteins (three outliers). When position effects and side chain-side chain interactions are added to the model, the fraction of variation explained increases to 92%. The propensity parameters in this model are identical to helix propensity values derived from other approaches. Measurement error accounts for another 1% of the mutant-to-mutant variation in stability. While the data support terms for several of the expected stabilizing/destabilizing effects, it does not support terms for several others, including i, i + 3 effects in the center of the helix and helix-dipole effects. In addition, the model does better with terms for several stabilizing/destabilizing effects for which we cannot identify the physical basis. The precision of our unfolding stability measurements (+/-0.087 kcal/mol) allows us to conclude that the 7% of variation in stabilities of the mutant proteins not accounted for by the model or by measurement variation is both real and large with respect to the nonpropensity terms in the model. The analysis also shows that the common practice of using C(m)m(av) instead of C(m)m(mut) to calculate DeltaG(HOH,N-D) values for each mutant protein results in a loss of information. We see no correlation between the residuals derived from the full model and m(mut) - m(wt), and hence it is unlikely our m(mut) values reflect mutant-to-mutant differences in the denatured state.