Intranasal Delivery of a Methyllanthionine-Stabilized Galanin Receptor-2-Selective Agonist Reduces Acute Food Intake

The regulatory (neuro)peptide galanin is widely distributed in the central and peripheral nervous systems, where it mediates its effects via three G protein-coupled receptors (GAL1-3R). Galanin has a vast diversity of biological functions, including modulation of feeding behavior. However, the clinical application of natural galanin is not practicable due to its rapid in vivo breakdown by peptidases and lack of receptor subtype specificity. Much effort has been put into the development of receptor-selective agonists and antagonists, and while receptor selectivity has been attained to some degree, most ligands show overlapping affinity. Therefore, we aimed to develop a novel ligand with specificity to a single galanin receptor subtype and increased stability. To achieve this, a lanthionine amino acid was enzymatically introduced into a galanin-related peptide. The residue’s subsequent cyclization created a conformational constraint which increased the peptide’s receptor specificity and proteolytic resistance. Further exchange of certain other amino acids resulted in a novel methyllanthionine-stabilized galanin receptor agonist, a G1pE-T3N-S6A-G12A-methyllanthionine[13–16]-galanin-(1–17) variant, termed M89b. M89b has exclusive specificity for GAL2R and a prolonged half-life in serum. Intranasal application of M89b to unfasted rats significantly reduced acute 24 h food intake inducing a drop in body weight. Combined administration of M89b and M871, a selective GAL2R antagonist, abolished the anorexigenic effect of M89b, indicating that the effect of M89b on food intake is indeed mediated by GAL2R. This is the first demonstration of in vivo activity of an intranasally administered lanthipeptide. Consequently, M89b is a promising candidate for clinical application as a galanin-related peptide-based therapeutic.

ERpred: a web server for the prediction of subtype-specific estrogen receptor antagonists

Estrogen receptors alpha and beta (ERα and ERβ) are responsible for breast cancer metastasis through their involvement of clinical outcomes. Estradiol and hormone replacement therapy targets both ERs, but this often leads to an increased risk of breast and endometrial cancers as well as thromboembolism. A major challenge is posed for the development of compounds possessing ER subtype specificity. Herein, we present a large-scale classification structure-activity relationship (CSAR) study of inhibitors from the ChEMBL database which consisted of an initial set of 11,618 compounds for ERα and 7,810 compounds for ERβ. The IC50 was selected as the bioactivity unit for further investigation and after the data curation process, this led to a final data set of 1,593 and 1,281 compounds for ERα and ERβ, respectively. We employed the random forest (RF) algorithm for model building and of the 12 fingerprint types, models built using the PubChem fingerprint was the most robust (Ac of 94.65% and 92.25% and Matthews correlation coefficient (MCC) of 89% and 76% for ERα and ERβ, respectively) and therefore selected for feature interpretation. Results indicated the importance of features pertaining to aromatic rings, nitrogen-containing functional groups and aliphatic hydrocarbons. Finally, the model was deployed as the publicly available web server called ERpred at http://codes.bio/erpred where users can submit SMILES notation as the input query for prediction of the bioactivity against ERα and ERβ.

Dysregulated Interferon Response Underlying Severe COVID-19

Innate immune interferons (IFNs), including type I and III IFNs, constitute critical antiviral mechanisms. Recent studies reveal that IFN dysregulation is key to determine COVID-19 pathogenesis. Effective IFN stimulation or prophylactic administration of IFNs at the early stage prior to severe COVID-19 may elicit an autonomous antiviral state, restrict the virus infection, and prevent COVID-19 progression. Inborn genetic flaws and autoreactive antibodies that block IFN response have been significantly associated with about 14% of patients with life-threatening COVID-19 pneumonia. In most severe COVID-19 patients without genetic errors in IFN-relevant gene loci, IFN dysregulation is progressively worsened and associated with the situation of pro-inflammation and immunopathy, which is prone to autoimmunity. In addition, the high correlation of severe COVID-19 with seniority, males, and individuals with pre-existing comorbidities will be plausibly explained by the coincidence of IFN aberrance in these situations. Collectively, current studies call for a better understanding of the IFN response regarding the spatiotemporal determination and subtype-specificity against SARS-CoV-2 infections, which are warranted to devise IFN-related prophylactics and therapies.

Long-read isoform sequencing reveals survival-associated splicing in breast cancer

SummaryTumors display widespread transcriptome alterations, but the full repertoire of isoform-level alternative splicing in cancer is not known. We developed a long-read RNA sequencing and analytical platform that identifies and annotates full-length isoforms, and infers tumor-specific splicing events. Application of this platform to breast cancer samples vastly expands the known isoform landscape of breast cancer, identifying thousands of previously unannotated isoforms of which ~30% impact protein coding exons and are predicted to alter protein localization and function, including of the breast cancer-associated genes ESR1 and ERBB2. We performed extensive cross-validation with -omics data sets to support transcription and translation of novel isoforms. We identified 3,059 breast tumor-specific splicing events, including 35 that are significantly associated with patient survival. Together, our results demonstrate the complexity, cancer subtype-specificity, and clinical relevance of novel isoforms in breast cancer that are only annotatable by LR-seq, and provide a rich resource of immuno-oncology therapeutic targets.

Analysis of common glucocorticoid response genes in childhood acute lymphoblastic leukemia in vivo identifies cell cycle but not apoptosis genes

Glucocorticoids (GCs) are an essential component of acute lymphoblastic leukemia (ALL) therapy. To identify genes mediating the anti-leukemic GC effects in vivo, we performed gene expression profiling of lymphoblasts from 46 children during the first 6-24h of systemic GC mono-therapy. Differential gene expression analysis across all patients revealed a considerable number of GC-regulated genes (190 induced, 179 repressed at 24h). However, when 4 leukemia subtypes (T-ALL, ETV6-RUNX1+, hyperdiploid, other preB-ALLs) were analyzed individually only 17 genes were regulated in all of them showing subtype-specificity of the transcriptional response. Cell cycle-related genes were down-regulated in the majority of patients, while no common changes in apoptosis genes could be identified. Surprisingly, none of the cell cycle or apoptosis genes correlated well with the reduction of peripheral blasts used as parameter for treatment response. These data suggest that (a) GC effects on cell cycle are independent of the cell death response and (b) GC-induced cell death cannot be explained by a single transcriptional pathway conserved in all subtypes. To unravel more complex, potentially novel pathways, we employed machine learning algorithms using an iterative elastic net approach, which identified gene expression signatures that correlated with the clinical response.

Peptide Binding Sites of Connexin Proteins

Intercellular gap junction (GJ) contacts formed by the coupling of connexin (Cx) hemichannels (HCs) embedded into the plasma membranes of neighboring cells play significant role in the development, signaling and malfunctions of mammalian tissues. Understanding and targeting GJ functions, however, calls for finding valid Cx subtype-specific inhibitors. We conjecture the lack of information about binding interactions between the GJ interface forming extracellular EL1 and EL2 loops and peptide mimetics designed to specifically inhibit Cx43HC coupling to Cx43GJ. Here, we explore active spots at the GJ interface using known peptide inhibitors that mimic various segments of EL1 and EL2. Binding interactions of these peptide inhibitors and the non-peptide inhibitor quinine has been modelled in combination with the use of blind docking molecular mechanics (MM). The neuron-specific Cx36HC and astrocyte-specific Cx43HC subtypes were modelled with a template derived from the high-resolution structure of Cx26GJ. GJ-coupled and free Cx36HC and Cx43HC models were obtained by dissection of GJs (GJ-coupled) followed by 50 ns molecular dynamics (free). Molecular mechanics (MM) calculations were performed by the docking of inhibitors, explicitly the designed Cx43 EL1 or EL2 loop sequence mimetics (GAP26, P5 or P180–195, GAP27, Peptide5, respectively) and the Cx36 subtype-specific quinine into the model structures. In order to explore specific binding interactions between inhibitors and CxHC subtypes, MM/Generalized Born Surface Area (MM/GBSA) ΔGbind values for representative conformers of peptide mimetics and quinine were evaluated by mapping the binding surface of Cx36HC and Cx43HC for all inhibitors. Quinine specifically contacts Cx36 EL1 residues V54-C55-N56-T57-L58, P60 and N63. Blocking the vestibule by the side of Cx36HC entry, quinine explicitly interacts with the non-conserved V54, L58, N63 residues of Cx36 EL1. In addition, our work challenges the predicted specificity of peptide mimetics, showing that the docking site of peptides is unrelated to the location of the sequence they mimic. Binding features, such as unaffected EL2 residues and the lack of Cx43 subtype-specificity of peptide mimetics, suggest critical roles for peptide stringency and dimension, possibly pertaining to the Cx subtype-specificity of peptide inhibitors.

Structure and selectivity engineering of the M1 muscarinic receptor toxin complex

Muscarinic toxins (MTs) are natural toxins produced by mamba snakes that primarily bind to muscarinic acetylcholine receptors (MAChRs) and modulate their function. Despite their similar primary and tertiary structures, MTs show distinct binding selectivity toward different MAChRs. The molecular details of how MTs distinguish MAChRs are not well understood. Here, we present the crystal structure of M1AChR in complex with MT7, a subtype-selective anti-M1AChR snake venom toxin. The structure reveals the molecular basis of the extreme subtype specificity of MT7 for M1AChR and the mechanism by which it regulates receptor function. Through in vitro engineering of MT7 finger regions that was guided by the structure, we have converted the selectivity from M1AChR toward M2AChR, suggesting that the three-finger fold is a promising scaffold for developing G protein–coupled receptor modulators.