SPPL2a (Signal Peptide Peptidase Like 2a) is an intramembrane aspartyl protease engaged in the function of B-cells and dendritic cells. Despite being an attractive target for modulation of the immune system, selective SPPL2a inhibitors are barely described in the literature. Recently, we have disclosed a selective, small molecular weight agent SPL-707 which confirmed that pharmacological inhibition of SPPL2a leads to the accumulation of its substrate CD74/p8 and as a consequence to a reduction in the number of B-cells as well as myeloid dendritic cells in mice. In this paper we describe the discovery of novel hydroxyethylamine based SPPL2a inhibitors. Starting from a rather lipophilic screening hit, several iterative optimization cycles allowed for its transformation into a highly potent and selective compound 15 (SPL-410) which inhibited in vivo CD74/p8 fragment processing in mice at 10 mg/kg oral dose.
MAP-activated protein kinase 2 (MK2) plays an important role in the regulation of innate immune response as well as in cell survival upon DNA damage. Despite its potential for the treatment of inflammation and cancer, to date no MK2 low molecular weight inhibitors have reached the clinic, mainly due to inadequate absorption, distribution, metabolism, and excretion (ADME) properties. We describe here an approach based on specifically placed fluorine within a recently described pyrrole-based MK2 inhibitor scaffold for manipulation of its physicochemical and ADME properties. While preserving target potency, the novel fluoro-derivatives showed greatly improved permeability as well as enhanced solubility and reduced clearance leading to significantly increased oral exposure.
Synthesis of novel 3-chloro-4-fluoro-7,8-dihydro-6Hisoquinolin-5-one and its derivatives using sequential ortho-formylation/ortho-allylation reactions of 2-chloro-3-fluoropyridine and ring-closing metathesis is described.
<p>Three dimensional modeling is a rapidly developing field in geological scientific and commercial applications. The combination of modeling and uncertainty analysis aides in understanding and quantitatively assessing complex subsurface structures. In recent years, many methods have been developed to facilitate this combined analysis, usually either through an extension of existing desktop applications or by making use of Jupyter notebooks as frontends. We evaluate here if modern web browser technology, linked to high-performance cloud services, can also be used for these types of analyses.</p><p>For this purpose, we developed a web application as proof-of-concept with the aim to visualize three dimensional geological models provided by a server. The implementation enables the modification of input parameters with assigned probability distributions. This step enables the generation of randomized realizations of models and the quantification and visualization of propagated uncertainties. The software is implemented using HTML Web Components on the client side and a Python server, providing a RESTful API to the open source geological modeling tool &#8220;GemPy&#8221;. Encapsulating the main components in custom elements, in combination with a minimalistic state management approach and a template parser, allows for high modularity. This enables rapid extendibility of the functionality of the components depending on the user&#8217;s needs and an easy integration into existing web platforms.</p><p>Our implementation shows that it is possible to extend and simplify modeling processes by creating an expandable web-based platform for probabilistic modeling, with the aim to increase the usability and to facilitate access to this functionality for a wide range of scientific analyses. The ability to compute models rapidly and with any given device in a web browser makes it flexible to use, and more accessible to a broader range of users.</p>
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