Targeting the chromatin binding of exportin-1 disrupts NFAT and T cell activation.

Exportin-1 (XPO1/CRM1) plays a central role in the nuclear-to-cytoplasmic transport of hundreds of proteins and contributes to other cellular processes, such as centrosome duplication. Small molecules targeting XPO1 induce cytotoxicity, and selinexor was approved by the Food and Drug Administration in 2019 as a cancer chemotherapy for relapsed multiple myeloma. Here, we describe a cell-type-dependent chromatin-binding function for XPO1 that is essential for the chromatin occupancy of NFAT transcription factors and thus the appropriate activation of T cells. Additionally, we establish a class of XPO1-targeting small molecules capable of disrupting the chromatin binding of XPO1 without perturbing nuclear export or inducing cytotoxicity. This work defines a broad transcription regulatory role for XPO1 that is essential for T cell activation as well as a new class of XPO1 modulators to enable therapeutic targeting of XPO1 beyond oncology including in T cell-driven autoimmune disorders.

Solution structure of an ultra-stable single-chain insulin analog connects protein dynamics to a novel mechanism of receptor binding.

Domain-minimized insulin receptors (IRs) have enabled crystallographic analysis of insulin-bound "micro-receptors." In such structures, the C-terminal segment of the insulin B chain inserts between conserved IR domains, unmasking an invariant receptor-binding surface that spans both insulin A and B chains. This "open" conformation not only rationalizes the inactivity of single-chain insulin (SCI) analogs (in which the A and B chains are directly linked), but also suggests that connecting (C) domains of sufficient length will bind the IR. Here, we report the high-resolution solution structure and dynamics of such an active SCI. The hormone's closed-to-open transition is foreshadowed by segmental flexibility in the native state as probed by heteronuclear NMR spectroscopy and multiple conformer simulations of crystallographic protomers as described in the companion article. We propose a model of the SCI's IR-bound state based on molecular-dynamics simulations of a micro-receptor complex. In this model, a loop defined by the SCI's B and C domains encircles the C-terminal segment of the IR α-subunit. This binding mode predicts a conformational transition between an ultra-stable closed state (in the free hormone) and an active open state (on receptor binding). Optimization of this switch within an ultra-stable SCI promises to circumvent insulin's complex global cold chain. The analog's biphasic activity, which serendipitously resembles current premixed formulations of soluble insulin and microcrystalline suspension, may be of particular utility in the developing world.

An ultra-stable single-chain insulin analog resists thermal inactivation and exhibits biological signaling duration equivalent to the native protein.

Thermal degradation of insulin complicates its delivery and use. Previous efforts to engineer ultra-stable analogs were confounded by prolonged cellular signaling in vivo, of unclear safety and complicating mealtime therapy. We therefore sought an ultra-stable analog whose potency and duration of action on intravenous bolus injection in diabetic rats are indistinguishable from wild-type (WT) insulin. Here, we describe the structure, function, and stability of such an analog, a 57-residue single-chain insulin (SCI) with multiple acidic substitutions. Cell-based studies revealed native-like signaling properties with negligible mitogenic activity. Its crystal structure, determined as a novel zinc-free hexamer at 2.8 Å, revealed a native insulin fold with incomplete or absent electron density in the C domain; complementary NMR studies are described in the accompanying article. The stability of the analog (ΔGU 5.0(±0.1) kcal/mol at 25 °C) was greater than that of WT insulin (3.3(±0.1) kcal/mol). On gentle agitation, the SCI retained full activity for >140 days at 45 °C and >48 h at 75 °C. These findings indicate that marked resistance to thermal inactivation in vitro is compatible with native duration of activity in vivo Further, whereas WT insulin forms large and heterogeneous aggregates above the standard 0.6 mm pharmaceutical strength, perturbing the pharmacokinetic properties of concentrated formulations, dynamic light scattering, and size-exclusion chromatography revealed only limited SCI self-assembly and aggregation in the concentration range 1-7 mm Such a combination of favorable biophysical and biological properties suggests that SCIs could provide a global therapeutic platform without a cold chain.

Connecting Rodent and Human Pharmacokinetic Models for the Design and Translation of Glucose-Responsive Insulin.

Despite considerable progress, development of glucose-responsive insulins (GRIs) still largely depends on empirical knowledge and tedious experimentation-especially on rodents. To assist the rational design and clinical translation of the therapeutic, we present a Pharmacokinetic Algorithm Mapping GRI Efficacies in Rodents and Humans (PAMERAH) built upon our previous human model. PAMERAH constitutes a framework for predicting the therapeutic efficacy of a GRI candidate from its user-specified mechanism of action, kinetics, and dosage, which we show is accurate when checked against data from experiments and literature. Results from simulated glucose clamps also agree quantitatively with recent GRI publications. We demonstrate that the model can be used to explore the vast number of permutations constituting the GRI parameter space and thereby identify the optimal design ranges that yield desired performance. A design guide aside, PAMERAH more importantly can facilitate GRI's clinical translation by connecting each candidate's efficacies in rats, mice, and humans. The resultant mapping helps to find GRIs that appear promising in rodents but underperform in humans (i.e., false positives). Conversely, it also allows for the discovery of optimal human GRI dynamics not captured by experiments on a rodent population (false negatives). We condense such information onto a "translatability grid" as a straightforward, visual guide for GRI development.