Anti-infective and cytotoxic properties of Bupleurum marginatum

Bupleurum marginatum Wall. ex DC (Apiaceae) is a perennial herb widely used in traditional Chinese and Kampo medicine for the treatment of various infectious diseases. The biological activities of B. marginatum have not been fully investigated. This study aims to investigate the antitrypanosomal, antimicrobial and antiviral activities of methanol (ME) and dichloromethane (DCM) extracts of B. marginatum aerial parts and the ability of both extracts to inhibit the growth of different cancer cell lines. Methods Phytochemical characterization of the extracts was performed by LC-MS profiling. The antitrypanosomal activity was evaluated using the resazurin method. The antimicrobial activity was assessed using agar diffusion and microdilution methods, and the minimum inhibitory concentration (MIC) values were determined. The antiviral activity was determined for 6.25, 12.5, and 50 μg/mL doses using a plaque reduction assay. Cytotoxicity was investigated in eight cancer cell lines (Caco-2, CCL-81, CCRF-CEM, COS-7, HL-60, MIA PaCa-2, MCF-7, and PANC-1) using the MTT assay and the caspase 3/7 activity was determined over the range of 62.5–1000 μg/mL. Results Phytochemical analyses resulted in the characterization of 15 components, mainly flavonoids and lignans. The DCM extract showed significant antitrypanosomal activity (IC50: 36.21 μg/mL) and moderate activity against Streptococcus pyogenes (MIC value: 0.25 mg/mL). At a dose of 12.5 μg/mL, the DCM extract inhibited 73.6% of the plaque production by hepatitis A virus. CCRF-CEM cells were the most sensitive to both extracts (IC50: 12.5–22.7 μg/mL). The cytotoxicity was mediated by induction of apoptosis (19-fold increase in the cellular caspase 3/7 level after treatment with the DCM extract at 1 mg/mL). Conclusions ME and DCM extract of B. marginatum showed anti-infective and antiproliferative effects

Curcumin or bisdemethoxycurcumin for nose-to-brain treatment of Alzheimer disease? A bio/chemo-informatics case study

<p>The current study introduces a new idea of utilising several bio/chemoinformatics tools in comparing two bio-similar natural molecules <i>viz.</i> curcumin and bisdemethoxycurcumin (BDMC) in order to select a potential nose-to-brain remedy for Alzheimer disease. The comparison comprised several bio/chemo informatics tools. It encompassed all levels starting from loading the drug in a certain carrier; PLGA nanoparticles, to the biopharmaceutical level investigating the interaction with mucin and inhibition of P-gp blood–brain barrier efflux pumps. Finally, the therapeutic level was investigated by studying the interaction with pharmacological targets such as amyloid peptide plaques and cyclooxygenase2 enzyme responsible for the inflammatory reactions of the studied disease. The comparison revealed the superiority of curcumin over BDMC. Five new analogues were also hypothesised where diethoxybisdemethoxycurcumin was  recommended as a superior molecule. This work introduced the virtual utilisation of bio/chemo informatics tools as a reliable and economic alternative to the exhausting and resources-consuming wet-lab experimentation.</p

Comparative metabolic profiling of olive leaf extracts from twelve different cultivars collected in both fruiting and flowering seasons

Abstract Olea europaea is an economically significant crop native to Mediterranean countries. Its leaves exhibit several biological properties associated to their chemical composition. The aqueous ethanolic extracts of olive leaves from twelve different cultivars were analyzed by high performance liquid chromatography coupled to photodiode array and electrospray ionization mass spectrometry (HPLC/PDA/ESI–MS/MS). A total of 49 phytochemicals were identified in both positive and negative ionization modes. The identified compounds belonged to four classes of secondary metabolites including secoiridoids, flavonoids, pentacyclic triterpenoids and various phenolic compounds. Seasonal variation in chemical composition among the studied cultivars was apparent in autumn and spring. Secologanoside, oleuropein, hydroxy-oleuropein, demethyl oleuropein, gallocatechin, luteolin-O-hexoside, diosmetin, oleanolic acid and maslinic acid were detected in all cultivars in both seasons. Oleuropein-O-deoxyhexoside was tentatively identified for the first time in olive leaf extracts; detected only in the Spanish cultivar Picual (PIC) collected in spring. Also, dihydroxy-oxooleanenoic acid and hydroxy-oxooleanenoic acid, two bioactive pentacyclic triterpenes, were identified. Principle component analysis (PCA) showed good discrimination among the studied cultivars in terms of their botanical origin. This study is considered the first study for non-targeted metabolic profiling of different olive leaf cultivars cultivated in Egypt

New Meroterpenoid Derivatives from the Pomegranate-Derived Endophytic Fungus <i>Talaromyces purpureogenus</i>

In this study, we report the isolation of two new meroterpenoids, miniolutelide D (1) and miniolutelide E (13-epi-miniolutelide C) (2), along with two meroterpenoidal analogues (3 and 4) and two phenolic compounds (5 and 6) from the endophytic fungus Talaromyces purpureogenus derived from Punica granatum fruits. Their structures were elucidated using extensive MS, 1D, and 2D NMR spectroscopic analyses as well as by comparing with data in the literature. The absolute configurations of 1 and 2 were determined using TDDFT-ECD calculations. Antimicrobial activity was evaluated. Compound 5 displayed significant activity against methicillin-resistant Staphylococcus aureus strain ATCC 700699 and moderate activity against S. aureus strain ATCC 29213

Validation of botanical origins and geographical sources of some Saudi honeys using ultraviolet spectroscopy and chemometric analysis

This study aims at distinguishing honey based on botanical and geographical sources. Different floral honey samples were collected from diverse geographical locations of Saudi Arabia. UV spectroscopy in combination with chemometric analysis including Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), and Soft Independent Modeling of Class Analogy (SIMCA) were used to classify honey samples. HCA and PCA presented the initial clustering pattern to differentiate between botanical as well as geographical sources. The SIMCA model clearly separated the Ziziphus sp. and other monofloral honey samples based on different locations and botanical sources. The results successfully discriminated the honey samples of different botanical and geographical sources validating the segregation observed using few physicochemical parameters that are regularly used for discrimination