Design, Synthesis, and Biological Evaluation of an Orally Bioavailable, Potent, and Selective ROCK2 Inhibitor for Psoriasis Treatment

Psoriasis, a prevalent chronic skin disorder, remains a significant therapeutic obstacle. This study centers on rho-associated coiled-coil-containing kinase2 (ROCK2) as an advantageous target for treating psoriasis and identifies five potent and selective ROCK2 inhibitors (A31-35). Notably, A32-35 outperform KD025 in ROCK2/ROCK1 selectivity by up to 216-fold. Among these candidates, A31 emerged as an exceedingly promising molecule, showcasing remarkable inhibitory potency (IC50 = 3.7 ± 0.8 nM), 19-fold ROCK2/ROCK1 selectivity, and favorable pharmacokinetics. Insights from the binding mode study further underscored the pivotal role of interactions with Phe103 on the P-loop in determining the selectivity between ROCK1 and ROCK2. In an imiquimod-induced psoriasis-like mouse model, oral administration of A31 notably ameliorated symptoms by targeting the IL-23/Th17 axis. Based on these compelling findings, A31 was selected as a highly promising compound for further investigation as a potential treatment for psoriasis.

Alpiniamides E-G from the Saline Lake-Derived Streptomyces sp. QHA48 and Their Lipid Accumulation Inhibitory Activity

Alpiniamides E-G, three previously unreported linear polyketide derivatives, along with two known compounds, were isolated from Streptomyces sp. QHA48, which was isolated from the saline lakes of Qinghai-Tibet Plateau. The structures of these compounds were determined through analysis of their spectroscopic data, as well as density functional theory prediction of NMR chemical shifts, application of the DP4+ algorithm and electronic circular dichroism (ECD) calculations. In a cell-based lipid-lowering assay, all five alpiniamides exhibited significant inhibition of lipid accumulation in HepG2 cells without inducing cytotoxic effects at a concentration of 27 μM.

Establishing sensitivity requirements for environmental analyses from project data quality objectives

This article proposes a simple strategy for establishing sensitivity requirements (quantitation limits) for environmental chemical analyses when the primary data quality objective is to determine if a contaminant of concern is greater or less than an action level (e.g., an environmental "cleanup goal," regulatory limit, or risk-based decision limit). The approach assumes that the contaminant concentrations are normally distributed with constant variance (i.e., the variance is not significantly dependent upon concentration near the action level). When the total or "field" portion of the measurement uncertainty can be estimated, the relative uncertainty at the laboratory's quantitation limit can be used to determine requirements for analytical sensitivity. If only the laboratory component of the total uncertainty is known, the approach can be used to identify analytical methods or laboratories that will not satisfy objectives for sensitivity (e.g., when selecting methodology during project planning).