Nuclera and Cytiva Collaborate on Protein Characterization for Drug Development

A crucial question often addressed during preclinical development focuses on the in vivo stability of therapeutic antibodies. Increasing the half-life of a therapeutic antibody has several benefits ranging from higher treatment efficacy to increased advantages for the patients who will have a fewer number of therapy sessions and a reduced cost. Given these compelling benefits, following the identification of therapeutic antibodies with the desired specificity, developers usually subject them to a refinement step to increase their stability. This process is often hindered by the lack of reliable experimental tools to predict the half-life of antibodies in patients. The major hurdle of using mouse models to predict antibody stability in the serum lies in the way immunoglobulin proteins are processed by the organism. In mammals, most proteins circulating in the serum undergo constant uptake by endothelial cells and are routed through the endosomes to the lysosomal compartment for degradation. In the endosomes, immunoglobulin G (IgG) proteins are recognized and bound by a transmembrane protein, called the neonatal Fc receptor (FcRn), which mediates their recycling to the plasma membrane and subsequent release back into the serum. As a result, the half-life of IgGs are significantly extended by this mechanism. Since most therapeutic antibodies belong to the IgG class, this recycling system is very relevant for their relative stability in the body. Remarkably, the relative affinity between IgGs and FcRn is extremely disparate between different species, with the mouse receptor showing a much higher affinity than its human counterpart.

Another obstacle to discovering new PPI inhibitors is the lack of libraries designed to hunt for them, points out Philippe Roche, PhD, senior scientist at the Integrative Structural and Chemical Biology team at the Cancer Research Center of Marseilles, France. “If you screen PPIs using libraries that were designed for kinases or GPCRs, that’s why you don’t get a lot of good results,” he says. To that end, his group began assembling a library focused on orthosteric inhibitors of PPIs. The result was 2P2Idb, a hand-curated, structural database cataloguing orthosteric inhibitors of PPIs for which the interface had been 3D characterized. From analyzing these known PPI inhibitors, and what structures they had in common, Roche and his colleagues developed a model to predict whether compounds would likely inhibit PPIs. Using this method, 2P2Idb creates an enriched screening library that dramatically increases the hit rate compared to standard libraries. Having proven their success with a small library of 1600 compounds, they are in the process of expanding the library to 10,000 compounds. Once that’s published, “the idea is to make this library available to labs around the world,” Roche says. “We will provide the library free of charge for people to be able to screen PPI targets.”