Monoterpene Alkaloids from Incarvillea delavayi Bureau et Franchet and Their Inhibition against LPS Induced NO Production in BV2 Cells

Three new monoterpene alkaloids, delavatines C-E (1-3), along with five known ones (4-8), were separated from the whole plants of Incarvillea delavayi. All compounds were deduced by interpretation of comprehensive NMR spectral data and X-Ray single crystal diffraction, in combination with a quantum chemical calculation of NMR chemical shift coupled with an advanced statistical procedure DP4+. Compounds 1-8 were assessed NO suppressive effect in LPS-stimulated BV2 microglia cells. Compounds 2, 3, 6, and 8 exhibited significant inhibition against NO production in LPS-induced BV2 cells with IC₅₀ values of 25.62, 17.29, 19.94 and 23.88 μM, stronger than or comparable to the positive control (AG) with IC₅₀ value of 26.13 μM.

Emerging biosensors in detection of natural products

Natural products (NPs) are a valuable source in the food, pharmaceutical, agricultural, environmental, and many other industrial sectors. Their beneficial properties along with their potential toxicities make the detection, determination or quantification of NPs essential for their application. The advanced instrumental methods require time-consuming sample preparation and analysis. In contrast, biosensors allow rapid detection of NPs, especially in complex media, and are the preferred choice of detection when speed and high throughput are intended. Here, we review diverse biosensors reported for the detection of NPs. The emerging approaches for improving the efficiency of biosensors, such as microfluidics, nanotechnology, and magnetic beads, are also discussed. The simultaneous use of two detection techniques is suggested as a robust strategy for precise detection of a specific NP with structural complexity in complicated matrices. The parallel detection of a variety of NPs structures or biological activities in a mixture of extract in a single detection phase is among the anticipated future advancements in this field which can be achieved using multisystem biosensors applying multiple flow cells, sensing elements, and detection mechanisms on miniaturized folded chips.

An integrated shotgun proteomics and bioinformatics approach for analysis of brain proteins from MCAO model using serial affinity chromatograph with four active ingredients from Shengmai preparations as ligands

Identification and validation of disease-relevant target proteins for natural products is an essential component of modern pharmaceutical research. In the present study, an integrated shotgun proteomics and bioinformatics approach was established to profile the interaction of active small molecules derived from ShengMai preparations (SMXZF) with hundreds of endogenously expressed proteins from middle cerebral artery occlusion (MCAO) model. Affinity-based proteomic strategies for isolation and identification of targets for the bioactive components is a classic, but still powerful approach. The proteins bound by SMXZF of the brain tissue proteins from MCAO model via serial affinity chromatograph were analyzed by nano liquid chromatography tandem mass spectrometry (nanoLC-MS/MS) and all MS/MS spectra were then automatically searched by the SEQUEST program. A total of 154 proteins had been identified, with the molecular weight ranging from 21,369.6 to 332,393.21 and the pI from 4.32 to 10.88. Bioinformatic analysis was also implemented to better understand the identified proteins. In the gene ontology (GO) annotation, all the identified proteins were classified into 39, 18 and 12 groups according to biological process, cellular component and molecular function, respectively. KEGG pathways analysis of the identified proteins was conducted with 46 corresponding pathways found. In addition, the gene network was also constructed to analyze the relationship of these genes each other. Further validation of some targets were performed in MCAO model by Western blotting. The results indeed supported the notion that proteins MAPK/ERK1/2, CaMKII and VIM were involved in the disease development of MCAO and played an essential role in the protective effect of SMXZF. This study highlights the effectiveness and reliability of this integrated shotgun proteomics and bioinformatics approach, which is a promising paradigm for target identification and elucidating the mechanism of natural products in future research.

(+)-2-(1-Hydroxyl-4-oxocyclohexyl) ethyl caffeate suppresses solar UV-induced skin carcinogenesis by targeting PI3K, ERK1/2, and p38

For decades, skin cancer incidence has increased, mainly because of oncogenic signaling pathways activated by solar ultraviolet (UV) irradiation (i.e., sun exposure). Solar UV induces multiple signaling pathways that are critical in the development of skin cancer, and therefore the development of compounds capable of targeting multiple molecules for chemoprevention of skin carcinogenesis is urgently needed. Herein, we examined the chemopreventive effects and the molecular mechanism of (+)-2-(1-hydroxyl-4-oxocyclohexyl) ethyl caffeate (HOEC), isolated from Incarvillea mairei var. grandiflora (Wehrhahn) Grierson. HOEC strongly inhibited neoplastic transformation of JB6 Cl41 cells without toxicity. PI3K, ERK1/2, and p38 kinase activities were suppressed by direct binding with HOEC in vitro. Our in silico docking data showed that HOEC binds at the ATP-binding site of each kinase. The inhibition of solar UV-induced PI3K, ERK1/2, and p38 kinase activities resulted in suppression of their downstream signaling pathways and AP1 and NF-κB transactivation in JB6 cells. Furthermore, topical application of HOEC reduced skin cancer incidence and tumor volume in SKH-1 hairless mice chronically exposed to solar UV. In summary, our results show that HOEC exerts inhibitory effects on multiple kinase targets and their downstream pathways activated by solar UV in vitro and in vivo. These findings suggest that HOEC is a potent chemopreventive compound against skin carcinogenesis caused by solar UV exposure.

Synthesis, preliminary bioevaluation and computational analysis of caffeic acid analogues

A series of caffeic acid amides were designed, synthesized and evaluated for anti-inflammatory activity. Most of them exhibited promising anti-inflammatory activity against nitric oxide (NO) generation in murine macrophage RAW264.7 cells. A 3D pharmacophore model was created based on the biological results for further structural optimization. Moreover, predication of the potential targets was also carried out by the PharmMapper server. These amide analogues represent a promising class of anti-inflammatory scaffold for further exploration and target identification.