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RNA hydrolysis presents problems in manufacturing, long-term storage, world-wide delivery, and in vivo stability of messenger RNA (mRNA)-based vaccines and therapeutics. A largely unexplored strategy to reduce mRNA hydrolysis is to redesign RNAs to form double-stranded regions, which are protected from in-line cleavage and enzymatic degradation, while coding for the same proteins. The amount of stabilization that this strategy can deliver and the most effective algorithmic approach to achieve stabilization remain poorly understood. Here, we present simple calculations for estimating RNA stability against hydrolysis, and a model that links the average unpaired probability of an mRNA, or AUP, to its overall hydrolysis rate. To characterize the stabilization achievable through structure design, we compare AUP optimization by conventional mRNA design methods to results from more computationally sophisticated algorithms and crowdsourcing through the OpenVaccine challenge on the Eterna platform. These computational tests were carried out on both model mRNAs and COVID-19 mRNA vaccine candidates. We find that rational design on Eterna and the more sophisticated algorithms lead to constructs with low AUP, which we term ‘superfolder’ mRNAs. These designs exhibit wide diversity of sequence and structure features that may be desirable for translation, biophysical size, and immunogenicity, and their folding is robust to temperature, choice of flanking untranslated regions, and changes in target protein sequence, as illustrated by rapid redesign of superfolder mRNAs for B.1.351, P.1, and B.1.1.7 variants of the prefusion-stabilized SARS-CoV-2 spike protein. Increases in in vitro mRNA half-life by at least two-fold appear immediately achievable.Significance statementMessenger RNA (mRNA) medicines that encode and promote translation of a target protein have shown promising use as vaccines in the current SARS-CoV-2 pandemic as well as infectious diseases due to their speed of design and manufacturing. However, these molecules are intrinsically prone to hydrolysis, leading to poor stability in aqueous buffer and major challenges in distribution. Here, we present a principled biophysical model for predicting RNA degradation, and demonstrate that the stability of any mRNA can be increased at least two-fold over conventional design techniques. Furthermore, the predicted stabilization is robust to post-design modifications. This conceptual framework and accompanying algorithm can be immediately deployed to guide re-design of mRNA vaccines and therapeutics to increase in vitro stability.

The glucagon-like peptide 1 receptor (GLP-1R) is a class B G-protein coupled receptor (GPCR) and diabetes drug target expressed mainly in pancreatic β-cells that, when activated by its agonist glucagon-like peptide 1 (GLP-1) after a meal, stimulates insulin secretion and β-cell survival and proliferation. The N-terminal region of GLP-1 interacts with membrane-proximal residues of GLP-1R, stabilizing its active conformation to trigger intracellular signaling. The best-studied agonist peptides, GLP-1 and exendin-4, share sequence homology at their N-terminal region; however, modifications that can be tolerated here are not fully understood. In this work a functional screen of GLP-1 variants with randomized N-terminal domains reveals new GLP-1R agonists and uncovers a pattern whereby a negative charge is preferred at the third position in various sequence contexts. We further tested this sequence-structure-activity principle by synthesizing peptide analogues where this position was mutated to both canonical and non-canonical amino acids. We discovered a highly active GLP-1 analogue in which the native glutamate residue three positions from the N-terminus was replaced with the sulfo-containing amino acid cysteic acid (GLP-1-CYA). The receptor binding and downstream signaling properties elicited by GLP-1-CYA were similar to the wild type GLP-1 peptide. Computational modeling identified a likely mode of interaction of the negatively charged side chain in GLP-1-CYA with an arginine on GLP-1R. This work highlights a strategy of combinatorial peptide screening coupled with chemical exploration that could be used to generate novel agonists for other receptors with peptide ligands.

Leukemia inhibitory factor (LIF), a cytokine secreted by stromal myofibroblasts and tumor cells, has recently been highlighted to promote tumor progression in pancreatic and other cancers through KRAS-driven cell signaling. We engineered a high affinity soluble human LIF receptor (LIFR) decoy that sequesters human LIF and inhibits its signaling as a therapeutic strategy. This engineered ‘ligand trap’, fused to an antibody Fc-domain, has ~50-fold increased affinity (~20 pM) and improved LIF inhibition compared to wild-type LIFR-Fc, potently blocks LIF-mediated effects in pancreatic cancer cells, and slows the growth of pancreatic cancer xenograft tumors. These results, and the lack of apparent toxicity observed in animal models, further highlights ligand traps as a promising therapeutic strategy for cancer treatment., Hunter et al. engineer a high affinity, soluble variant of leukemia inhibitory factor receptor (LIFR) to serve as a ligand trap for the LIF cytokine. They further demonstrate that this engineered LIFR exhibits improved affinity relative to the wild-type receptor, leading to better disruption of LIF signaling in cancer cells, and highlighting promise of such ligand traps as therapeutic strategy for cancer treatment.

V-domain immunoglobulin (Ig) suppressor of T cell activation (VISTA) is an immune checkpoint that maintains peripheral T cell quiescence and inhibits anti-tumor immune responses. VISTA functions by dampening the interaction between myeloid cells and T cells, orthogonal to PD-1 and other checkpoints of the tumor-T cell signaling axis. Here, we report the use of yeast surface display to engineer an anti-VISTA antibody that binds with high affinity to mouse, human, and cynomolgus monkey VISTA. Our anti-VISTA antibody (SG7) inhibits VISTA function and blocks purported interactions with both PSGL-1 and VSIG3 proteins. SG7 binds a unique epitope on the surface of VISTA, which partially overlaps with other clinically relevant antibodies. As a monotherapy, and to a greater extent as a combination with anti-PD1, SG7 slows tumor growth in multiple syngeneic mouse models. SG7 is a promising clinical candidate that can be tested in fully immunocompetent mouse models and its binding epitope can be used for future campaigns to develop species cross-reactive inhibitors of VISTA.

Interleukin-6 (IL-6) family cytokines signal through multimeric receptor complexes, providing unique opportunities to create novel ligand-based therapeutics. The cardiotrophin-like cytokine factor 1 (CLCF1) ligand has been shown to play a role in cancer, osteoporosis, and atherosclerosis. Once bound to ciliary neurotrophic factor receptor (CNTFR), CLCF1 mediates interactions to coreceptors glycoprotein 130 (gp130) and leukemia inhibitory factor receptor (LIFR). By increasing CNTFR-mediated binding to these coreceptors we generated a receptor superagonist which surpassed the potency of natural CNTFR ligands in neuronal signaling. Through additional mutations, we generated a receptor antagonist with increased binding to CNTFR but lack of binding to the coreceptors that inhibited tumor progression in murine xenograft models of nonsmall cell lung cancer. These studies further validate the CLCF1-CNTFR signaling axis as a therapeutic target and highlight an approach of engineering cytokine activity through a small number of mutations.

RNA hydrolysis presents problems in manufacturing, long-term storage, world-wide delivery and in vivo stability of messenger RNA (mRNA)-based vaccines and therapeutics. A largely unexplored strategy to reduce mRNA hydrolysis is to redesign RNAs to form double-stranded regions, which are protected from in-line cleavage and enzymatic degradation, while coding for the same proteins. The amount of stabilization that this strategy can deliver and the most effective algorithmic approach to achieve stabilization remain poorly understood. Here, we present simple calculations for estimating RNA stability against hydrolysis, and a model that links the average unpaired probability of an mRNA, or AUP, to its overall hydrolysis rate. To characterize the stabilization achievable through structure design, we compare AUP optimization by conventional mRNA design methods to results from more computationally sophisticated algorithms and crowdsourcing through the OpenVaccine challenge on the Eterna platform. We find that rational design on Eterna and the more sophisticated algorithms lead to constructs with low AUP, which we term 'superfolder' mRNAs. These designs exhibit a wide diversity of sequence and structure features that may be desirable for translation, biophysical size, and immunogenicity. Furthermore, their folding is robust to temperature, computer modeling method, choice of flanking untranslated regions, and changes in target protein sequence, as illustrated by rapid redesign of superfolder mRNAs for B.1.351, P.1 and B.1.1.7 variants of the prefusion-stabilized SARS-CoV-2 spike protein. Increases in in vitro mRNA half-life by at least two-fold appear immediately achievable.

Dysregulated activity of the protease matriptase is a key contributor to aggressive tumor growth, cancer metastasis, and osteoarthritis. Methods for the detection and quantification of matriptase activity and inhibition would be useful tools. To address this need, we developed a matriptase-sensitive protein biosensor based on a dimerization-dependent red fluorescent protein (ddRFP) reporter system. In this platform, two adjoining protein domains, connected by a protease-labile linker, produce fluorescence when assembled and are nonfluorescent when the linker is cleaved by matriptase. A panel of ddRFP-based matriptase biosensor designs was created that contained different linker lengths between the protein domains. These constructs were characterized for linker-specific cleavage, matriptase activity, and matriptase selectivity; a biosensor containing a RSKLRVGGH linker (termed B4) was expressed at high yields and displayed both high catalytic efficiency and matriptase specificity. This biosensor detects matriptase inhibition by soluble and yeast cell surface expressed inhibitor domains with up to a 5-fold dynamic range and also detects matriptase activity expressed by human cancer cell lines. In addition to matriptase, we highlight a strategy that can be used to create effective biosensors for quantifying activity and inhibition of other proteases of interest. [Image: see text]

V-domain Ig Suppressor of T cell Activation (VISTA) is an immune checkpoint protein that inhibits the T - cell response against cancer. Similar to PD-1 and CTLA-4, antibodies that block VISTA signaling can release the brakes of the immune system and promote tumor clearance. VISTA has an Ig-like fold, but little is known about its structure and mechanism of action. Here, we report a 1.85 Å crystal structure of the human VISTA extracellular domain and highlight structural features that make VISTA unique among B7 family members. Through fine-epitope mapping, we also identify solvent-exposed residues that underlie binding to a clinically relevant anti-VISTA antibody. This antibody-binding region is also shown to interact with V-set and Ig domain-containing 3 (VSIG3), the recently proposed functional binding partner of VISTA. The structure and functional epitope determined here will help guide future drug development efforts against this important checkpoint target.

Dysregulated matriptase activity has been established as a key contributor to cancer progression through its activation of growth factors, including the hepatocyte growth factor (HGF). Despite its critical role and prevalence in many human cancers, limitations to developing an effective matriptase inhibitor include weak binding affinity, poor selectivity, and short circulating half-life. We applied rational and combinatorial approaches to engineer a potent inhibitor based on the hepatocyte growth factor activator inhibitor type-1 (HAI-1), a natural matriptase inhibitor. The first Kunitz domain (KD1) of HAI-1 has been well established as a minimal matriptase-binding and inhibition domain, whereas the second Kunitz domain (KD2) is inactive and involved in negative regulation. Here, we replaced the inactive KD2 domain of HAI-1 with an engineered chimeric variant of KD2/KD1 domains and fused the resulting construct to an antibody Fc domain to increase valency and circulating serum half-life. The final protein variant contains four stoichiometric binding sites that we showed were needed to effectively inhibit matriptase with a K(i) of 70 ± 5 pm, an increase of 120-fold compared with the natural HAI-1 inhibitor, to our knowledge making it one of the most potent matriptase inhibitors identified to date. Furthermore, the engineered inhibitor demonstrates a protease selectivity profile similar to that of wildtype KD1 but distinct from that of HAI-1. It also inhibits activation of the natural pro-HGF substrate and matriptase expressed on cancer cells with at least an order of magnitude greater efficacy than KD1.