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Synthesis and Physico-Chemical Properties of 2-SF5-(Aza)Indoles, A New Family of SF5-Heterocycles
No full textStructural diversity in heterocyclic chemistry is key to unlock new properties and modes of action. In this regard, heterocycles embedding emerging fluorinated substituents hold great promises. Herein is described a strategy to access 2-SF5- (aza)indoles for the first time. The sequence relies on the radical addition of SF5Cl to the alkynyl p-system of 2-ethynyl anilines followed by a cyclization reaction. A telescoped sequence is proposed making this strategy very appealing and reproducible on gram scale. Downstream functionalizations are also demonstrated, allowing an easy diversification of N- and C3-positions. Ames test, pKa, logP and DSC measurements of several fluorinated 2-Rfindoles are also disclosed. These studies highlight the strategic advantages that a C2-pentafluorosulfanylated motif impart to a privileged scaffold such as indole
One Is the Coldest Number: How Group Size and Body Weight Affect Thermal Preference in Weaned Pigs (3 to 15 kg)
No full textHousing pigs within their thermal comfort zone positively impacts productivity and performance. However, fundamental information on behavioral thermoregulatory responses of individual and group-housed pigs is meager. As a gregarious species, pigs prefer to be near one another, touching and often huddling. As pigs huddle together, they decrease their heat loss to the environment by decreasing exposed surface area and increasing mass. Additionally, pigs gain weight rapidly as they age. As an individual grows, their ability to withstand lower temperatures increases. We hypothesized that group size would alter pig thermal preference and that thermal preference would change based upon body weight. Thirty-six groups of pigs (n = 2 pigs/group) were tested in a factorial design based on group size (1, 2, or 4) and weight category (small: 5.20 ± 1.15 kg; medium: 8.79 ± 1.30 kg; and large: 13.95 ± 1.26 kg) in both sexes. Treatment groups were placed inside a chamber with a controlled thermal gradient (4.6 m × 0.9 m × 0.9 m; L × W × H) that ranged in temperature from 18 to 30 °C. Pigs habituated to the gradient for 24 h. The following 24 h testing period was continuously video recorded and each pig’s location during inactivity (~70% daily budget) within the thermal apparatus was recorded every 10 min via instantaneous scan sampling. Data were analyzed using a GLM and log10 + 0.001 transformed for normality. Tukey tests and Bonferroni-corrected custom tests were used for post hoc comparisons. Peak temperature preference was determined by the maximum amount of time spent at a specific temperature. Both group size (p = 0.001) and weight category (p 0.05). Overall, heavier pigs and larger groups preferred cooler temperatures
Rational prediction of human dose for gene therapy based on translational dose-response studies
No full textEstablishing dose response relationships is foundational in drug development. To improve confidence in a development program, understanding dose response in animals and how that translates to early clinical development studies is critical. Traditional approaches to predict clinical doses that achieve minimal biological activity and maintain wide safety margins may not apply to gene therapy (GT) because of differences in biological mechanisms of drug disposition and pharmacological activity when compared with more established drug modalities
The Chemical Biology-Medicinal Chemistry continuum: EFMC's vision
No full textAbstract: The European Federation for Medicinal chemistry and Chemical biology (EFMC) is a federation of learned societies. It groups organizations of European scientists working in a dynamic field spanning chemical biology and medicinal chemistry. New ideas, tools and technologies emerging from a wide array of scientific disciplines continuously energize this rapidly evolving area. Medicinal chemistry is the design, synthesis and optimization of biologically active molecules, and aims at discovering new drug candidates. This description largely overlaps with the scope of chemical biology, which is now a mature field of science and for which a more precise definition of what it englobes, in the frame of EFMC, is timely. This article discusses chemical biology as currently understood by EFMC, including all activities dealing with the design and synthesis of biologically active chemical tools, and their use to probe, characterize or influence biological systems
Licogliflozin versus placebo in women with polycystic ovary syndrome: A randomized, double-blind, phase 2 trial
No full textPolycystic ovary syndrome (PCOS) is characterized by hyperandrogenism and insulin resistance. The dual sodium-glucose co-transporter 1/2 inhibitor (SGLT1/2i) licogliflozin (LIK066) ameliorates hyperinsulinism in patients with diabetes and obesity. This study examines the effect of licogliflozin on androgens in women with PCOS. In a multicentre, randomized, placebo-controlled, double-blind, 2-week trial, patients with PCOS received licogliflozin 50 mg or placebo three times a day (TID). Changes in free testosterone (FT), other androgens and variables of insulin resistance were analysed. Concentration of FT did not change (TRLIK066:TRPCB [FT]: 0.88; 90% CI: 0.70-1.11; P =.353). Licogliflozin reduced androstendione (A4) by 19% (TRLIK066:TRPCB [A4]: 0.81; 90% CI: 0.68-0.99; P =.089) and dehydroepiandrosteron sulphate (DHEAS) by 24% (TRLIK066:TRPCB [DHEAS]: 0.76; 90% CI: 0.65-0.89; P =.008). Hyperinsulinaemia was reduced by 70% by licogliflozin (highest insulin concentration [MAXI]; TRLIK066:TRPCB [MAXI]: 0·26; 90% CI:0.20-0.34; P <.001 and area under the curve insulin [AUCI]; TRLIK066:TRPCB [AUCI]: 0.32; 90% CI: 0.25-0.41; P <.001). Diarrhoea and nausea occurred as common adverse events. Dual inhibition of SGLT1/2 ameliorates hyperinsulinaemia and hyperandrogenaemia in women with PCOS. Licogliflozin may represent a promising novel treatment option for PCOS
Discovery of Umibecestat (CNP520): A Potent, Selective and Efficacious β-Secretase (BACE1) Inhibitor for the Prevention of Alzheimer’s Disease
No full textStarting from lead compound 6, 5-amino-1,4-oxazine BACE1 inhibitors were optimised in order to improve potency, brain penetration and metabolic stability. Insertion of a Me and a CF3 group at the 6-position of the 5-amino-1,4-oxazine, led to 8 (NB-360) an inhibitor with a pKa of 7.1, a very low P-gp efflux ratio and excellent pharmacological profile enabling high CNS penetration and exposure. Fur color changes observed with NB-360 in efficacy studies in preclinical animal models triggered further optimization of the series. Herein, we describe the steps leading to the discovery of 3-chloro-5-trifluoromethyl-pyridine-2-carboxylic acid [6-((3R,6R)-5-amino-3,6-dimethyl-6-trifluoromethyl-3,6-dihydro-2H-[1,4]oxazin-3-yl)-5-fluoro-pyridin-2-yl]amide 15 (CNP520, umibecestat), an inhibitor with superior BACE1/BACE2 selectivity and pharmacokinetics. CNP520 reduced significantly Aβ levels in mice and rats in acute and chronic treatment regimen without any side effects and thus qualified for AD prevention studies in the clinic
Pharmacokinetics of capmatinib in participants with hepatic impairment: A phase 1, open-label, single-dose, parallel-group study.
No full textCapmatinib, a mesenchymal-epithelial transition factor tyrosine kinase inhibitor, is metabolized by cytochrome P450 (CYP) 3A4 and aldehyde oxidase. In individuals with hepatic impairment, alterations in hepatobiliary excretion and metabolism could lead to higher capmatinib exposure. We compared the pharmacokinetics of a single oral dose of capmatinib 200 mg administered to participants with varying degrees of hepatic impairment vs. matched controls with normal hepatic function
PKC-phosphorylation of Liprin-α3 triggers phase separation and controls presynaptic active zone structure.
No full textThe active zone of a presynaptic nerve terminal defines sites for neurotransmitter release. Its protein machinery may be organized through liquid-liquid phase separation, a mechanism for the formation of membrane-less subcellular compartments. Here, we show that the active zone protein Liprin-α3 rapidly and reversibly undergoes phase separation in transfected HEK293T cells. Condensate formation is triggered by Liprin-α3 PKC-phosphorylation at serine-760, and RIM and Munc13 are co-recruited into membrane-attached condensates. Phospho-specific antibodies establish phosphorylation of Liprin-α3 serine-760 in transfected cells and mouse brain tissue. In primary hippocampal neurons of newly generated Liprin-α2/α3 double knockout mice, synaptic levels of RIM and Munc13 are reduced and the pool of releasable vesicles is decreased. Re-expression of Liprin-α3 restored these presynaptic defects, while mutating the Liprin-α3 phosphorylation site to abolish phase condensation prevented this rescue. Finally, PKC activation in these neurons acutely increased RIM, Munc13 and neurotransmitter release, which depended on the presence of phosphorylatable Liprin-α3. Our findings indicate that PKC-mediated phosphorylation of Liprin-α3 triggers its phase separation and modulates active zone structure and function
Dynamic association of human Ebp1 with the ribosome.
No full textRibosomes are the macromolecular machines at the heart of protein synthesis; however, their function can be modulated by a variety of additional protein factors that directly interact with them. Here, we report the cryo-EM structure of human Ebp1 (p48 isoform) bound to the human 80S ribosome at 3.3 Å resolution. Ebp1 binds in the vicinity of the peptide exit tunnel on the 80S ribosome, and this binding is enhanced upon puromycin-mediated translational inhibition. The association of Ebp1 with the 80S ribosome centers around its interaction with ribosomal proteins eL19 and uL23 and the 28S rRNA. Further analysis of the Ebp1-ribosome complex suggests that Ebp1 can rotate around its insert domain, which may enable it to assume a wide range of conformations while maintaining its interaction with the ribosome. Structurally, Ebp1 shares homology with the methionine aminopeptidase 2 family of enzymes; therefore, this inherent flexibility may also be conserved
Collaborative Profile-QSAR: A Natural Platform for Building Collaborative Models among Competing Companies
No full textMassively multitask bioactivity models that transfer learning between thousands of assays have been shown to work dramatically better than separate models trained on each individual assay. In particular, the applicability domain for a given model can expand from compounds similar to those tested in that specific assay to those tested across the full complement of contributing assays. If many large companies would share their assay data and train models on the superset, predictions should be better than what each company can do alone. However, a company's compounds, targets, and activities are among their most guarded trade secrets. Strategies have been proposed to share just the individual collaborators' models, without exposing any of the training data. Profile-QSAR (pQSAR) is a two-level, multitask, stacked model. It uses profiles of level-1 predictions from single-task models for thousands of assays as compound descriptors for level-2 models. This work describes its simple and natural adaptation to safe collaboration by model sharing. Broad model sharing has not yet been implemented across multiple large companies, so there are numerous unanswered questions. Novartis was formed from several mergers and acquisitions. In principle, this should allow an internal simulation of model sharing. In practice, the lack of metadata about the origins of compounds and assays made this difficult. Nevertheless, we have attempted to simulate this process and propose some findings: multitask pQSAR is always an improvement over single-task models; collaborative multitask modeling did not improve predictions on internal compounds; collaboration did improve predictions for external compounds but far less than the purely internal multitask modeling for internal compounds; collaborative models for external compounds increasingly improve as overlap between compound collections increases; combining profiles from inside and outside the company is not best, with internal predictions better using only the inside profile and external using only the outside profile, but a consensus of models using all three profiles is best on external compounds and a good compromise on internal compounds. We anticipate similar results from other model-sharing approaches. Indeed, since collaborative pQSAR through model sharing is mathematically identical to pQSAR using actual shared data, we believe our conclusions should apply to collaborative modeling by any current method even including the unlikely scenario of directly sharing all chemical structures and assay data