Probing PAC1 receptor activation across species with an engineered sensor.

Class-B1 G-protein-coupled receptors (GPCRs) are an important family of clinically relevant drug targets that remain difficult to investigate via high-throughput screening and in animal models. Here, we engineered PAClight1P78A, a novel genetically encoded sensor based on a class-B1 GPCR (the human PAC1 receptor, hmPAC1R) endowed with high dynamic range (ΔF/F0 = 1100%), excellent ligand selectivity, and rapid activation kinetics (τON = 1.15 s). To showcase the utility of this tool for in vitro applications, we thoroughly characterized and compared its expression, brightness and performance between PAClight1P78A-transfected and stably expressing cells. Demonstrating its use in animal models, we show robust expression and fluorescence responses upon exogenous ligand application ex vivo and in vivo in mice, as well as in living zebrafish larvae. Thus, the new GPCR-based sensor can be used for a wide range of applications across the life sciences empowering both basic research and drug development efforts.

Rapid flow-based synthesis of post-translationally modified peptides and proteins: a case study on MYC's transactivation domain.

Protein-protein interactions of c-Myc (MYC) are often regulated by post-translational modifications (PTMs), such as phosphorylation, and crosstalk thereof. Studying these interactions requires proteins with unique PTM patterns, which are challenging to obtain by recombinant methods. Standard peptide synthesis and native chemical ligation can produce such modified proteins, but are time-consuming and therefore typically limited to the study of individual PTMs. Herein, we report the development of flow-based methods for the rapid synthesis of phosphorylated MYC sequences (up to 84 AA), and demonstrate the versatility of this approach for the incorporation of other PTMs (N ε-methylation, sulfation, acetylation, glycosylation) and combinations thereof. Peptides containing up to seven PTMs and phosphorylation at up to five sites were successfully prepared and isolated in high yield and purity. We further produced ten PTM-decorated analogues of the MYC Transactivation Domain (TAD) to screen for binding to the tumor suppressor protein, Bin1, using heteronuclear NMR and native mass spectrometry. We determined the effects of phosphorylation and glycosylation on the strength of the MYC:Bin1 interaction, and reveal an influence of MYC sequence length on binding. Our platform for the rapid synthesis of MYC sequences up to 84 AA with distinct PTM patterns thus enables the systematic study of PTM function at a molecular level, and offers a convenient way for expedited screening of constructs.

Merging Flow Synthesis and Enzymatic Maturation to Expand the Chemical Space of Lasso Peptides.

Many peptidic natural products, such as lasso peptides, cyclic peptides, and cyclotides, are conformationally constrained and show biological stability, making them attractive scaffolds for drug development. Although many peptides can be synthesized and modified through chemical methods, knot-like lasso peptides such as microcin J25 (MccJ25) and their analogues remain elusive. As the chemical space of MccJ25 analogues accessible through purely biological methods is also limited, we proposed a hybrid approach: flow-based chemical synthesis of non-natural precursor peptides, followed by in vitro transformation with recombinant maturation enzymes, to yield a more diverse array of lasso peptides. Herein, we established the rapid, flow-based synthesis of chemically modified MccJ25 precursor peptides (57 amino acids). Heterologous expression of enzymes McjB and McjC was extensively optimized to improve yields and facilitate the synthesis of multiple analogues of MccJ25, including the incorporation of non-canonical tyrosine and histidine derivatives into the lasso scaffold. Finally, using our chemoenzymatic strategy, we produced a biologically active analogue containing three d-amino acids in the loop region and incorporated backbone N-methylations. Our method provides rapid access to chemically modified lasso peptides that could be used to investigate structure-activity relationships, epitope grafting, and the improvement of therapeutic properties.

How hydrophobicity, side chains, and salt affect the dimensions of disordered proteins.

Despite the generally accepted role of the hydrophobic effect as the driving force for folding, many intrinsically disordered proteins (IDPs), including those with hydrophobic content typical of foldable proteins, behave nearly as self-avoiding random walks (SARWs) under physiological conditions. Here, we tested how temperature and ionic conditions influence the dimensions of the N-terminal domain of pertactin (PNt), an IDP with an amino acid composition typical of folded proteins. While PNt contracts somewhat with temperature, it nevertheless remains expanded over 10-58°C, with a Flory exponent, ν, >0.50. Both low and high ionic strength also produce contraction in PNt, but this contraction is mitigated by reducing charge segregation. With 46% glycine and low hydrophobicity, the reduced form of snow flea anti-freeze protein (red-sfAFP) is unaffected by temperature and ionic strength and persists as a near-SARW, ν ~ 0.54, arguing that the thermal contraction of PNt is due to stronger interactions between hydrophobic side chains. Additionally, red-sfAFP is a proxy for the polypeptide backbone, which has been thought to collapse in water. Increasing the glycine segregation in red-sfAFP had minimal effect on ν. Water remained a good solvent even with 21 consecutive glycine residues (ν > 0.5), and red-sfAFP variants lacked stable backbone hydrogen bonds according to hydrogen exchange. Similarly, changing glycine segregation has little impact on ν in other glycine-rich proteins. These findings underscore the generality that many disordered states can be expanded and unstructured, and that the hydrophobic effect alone is insufficient to drive significant chain collapse for typical protein sequences.

A Tumor-Homing Peptide Platform Enhances Drug Solubility, Improves Blood-Brain Barrier Permeability and Targets Glioblastoma.

BACKGROUND: Glioblastoma (GBM) is the most common and deadliest malignant primary brain tumor, contributing significant morbidity and mortality among patients. As current standard-of-care demonstrates limited success, the development of new efficacious GBM therapeutics is urgently needed. Major challenges in advancing GBM chemotherapy include poor bioavailability, lack of tumor selectivity leading to undesired side effects, poor permeability across the blood-brain barrier (BBB), and extensive intratumoral heterogeneity. METHODS: We have previously identified a small, soluble peptide (BTP-7) that is able to cross the BBB and target the human GBM extracellular matrix (ECM). Here, we covalently attached BTP-7 to an insoluble anti-cancer drug, camptothecin (CPT). RESULTS: We demonstrate that conjugation of BTP-7 to CPT improves drug solubility in aqueous solution, retains drug efficacy against patient-derived GBM stem cells (GSC), enhances BBB permeability, and enables therapeutic targeting to intracranial GBM, leading to higher toxicity in GBM cells compared to normal brain tissues, and ultimately prolongs survival in mice bearing intracranial patient-derived GBM xenograft. CONCLUSION: BTP-7 is a new modality that opens the door to possibilities for GBM-targeted therapeutic approaches.

Flow-based Methods in Chemical Peptide and Protein Synthesis.

Flow chemistry has emerged as a powerful method for on-demand chemical synthesis and modification of peptides and proteins. Herein, we discuss the characteristics of flow chemistry and how they are applied to various aspects of peptide chemistry. We highlight recent advances in automated flow-based peptide synthesis, which extend the length of peptides routinely accessible to single-domain proteins and allow for the collection of time-resolved synthesis data. Applications of this data for the prediction of synthesis outcome and the potential for the development of more sustainable synthesis methods are also discussed. Finally, we will review solutionphase approaches, including flow-based ligation strategies and peptide cyclization. Throughout this review, the current challenges and potential future developments are highlighted.

Targeting glioblastoma using a novel peptide specific to a deglycosylated isoform of brevican.

Glioblastoma multiforme (GBM) is the most common and deadliest form of brain tumor and remains amongst the most difficult cancers to treat. Brevican (Bcan), a central nervous system (CNS)-specific extracellular matrix protein, is upregulated in high-grade glioma cells, including GBM. A Bcan isoform lacking most glycosylation, dg-Bcan, is found only in GBM tissues. Here, dg-Bcan is explored as a molecular target for GBM. In this study, we screened a d-peptide library to identify a small 8-amino acid dg-Bcan-Targeting Peptide (BTP) candidate, called BTP-7 that binds dg-Bcan with high affinity and specificity. BTP-7 is preferentially internalized by dg-Bcan-expressing patient-derived GBM cells. To demonstrate GBM targeting, we radiolabeled BTP-7 with 18F, a radioisotope of fluorine, and found increased radiotracer accumulation in intracranial GBM established in mice using positron emission tomography (PET) imaging. dg-Bcan is an attractive molecular target for GBM, and BTP-7 represents a promising lead candidate for further development into novel imaging agents and targeted therapeutics.

Identification of N-Terminally Diversified GLP-1R Agonists Using Saturation Mutagenesis and Chemical Design.

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 ß-cells that, when activated by its agonist glucagon-like peptide 1 (GLP-1) after a meal, stimulates insulin secretion and ß-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 noncanonical 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.

Deep Learning for Prediction and Optimization of Fast-Flow Peptide Synthesis.

The chemical synthesis of polypeptides involves stepwise formation of amide bonds on an immobilized solid support. The high yields required for efficient incorporation of each individual amino acid in the growing chain are often impacted by sequence-dependent events such as aggregation. Here, we apply deep learning over ultraviolet-visible (UV-vis) analytical data collected from 35 427 individual fluorenylmethyloxycarbonyl (Fmoc) deprotection reactions performed with an automated fast-flow peptide synthesizer. The integral, height, and width of these time-resolved UV-vis deprotection traces indirectly allow for analysis of the iterative amide coupling cycles on resin. The computational model maps structural representations of amino acids and peptide sequences to experimental synthesis parameters and predicts the outcome of deprotection reactions with less than 6% error. Our deep-learning approach enables experimentally aware computational design for prediction of Fmoc deprotection efficiency and minimization of aggregation events, building the foundation for real-time optimization of peptide synthesis in flow.

Ultra-large chemical libraries for the discovery of high-affinity peptide binders.

High-diversity genetically-encoded combinatorial libraries (108-1013 members) are a rich source of peptide-based binding molecules, identified by affinity selection. Synthetic libraries can access broader chemical space, but typically examine only ~ 106 compounds by screening. Here we show that in-solution affinity selection can be interfaced with nano-liquid chromatography-tandem mass spectrometry peptide sequencing to identify binders from fully randomized synthetic libraries of 108 members-a 100-fold gain in diversity over standard practice. To validate this approach, we show that binders to a monoclonal antibody are identified in proportion to library diversity, as diversity is increased from 106-108. These results are then applied to the discovery of p53-like binders to MDM2, and to a family of 3-19 nM-affinity, α/ß-peptide-based binders to 14-3-3. An X-ray structure of one of these binders in complex with 14-3-3σ is determined, illustrating the role of ß-amino acids in facilitating a key binding contact.

Optical Control of Cytokine Production Using Photoswitchable Galactosylceramides.

α-Galactosylceramides are glycosphingolipids that show promise in cancer immunotherapy. After presentation by CD1d, they activate natural killer T cells (NKT), which results in the production of a variety of pro-inflammatory and immunomodulatory cytokines. Herein, we report the synthesis and biological evaluation of photochromic derivatives of KRN-7000, the activity of which can be modulated with light. Based on established structure-activity relationships, we designed photoswitchable analogues of this glycolipid that control the production of pro-inflammatory cytokines, such as IFN-γ. The azobenzene derivative α-GalACer-4 proved to be more potent than KRN-7000 itself when activated with 370 nm light. Photolipids of this type could improve our mechanistic understanding of cytokine production and could open new directions in photoimmunotherapy.