Identification of plumericin as a potent new inhibitor of the NF-κB pathway with anti-inflammatory activity in vitro and in vivo.

BACKGROUND AND PURPOSE: The transcription factor NF-κB orchestrates many pro-inflammatory signals and its inhibition is considered a promising strategy to combat inflammation. Here we report the characterization of the natural product plumericin as a highly potent inhibitor of the NF-κB pathway with a novel chemical scaffold, which was isolated via a bioactivity-guided approach, from extracts of Himatanthus sucuuba, an Amazonian plant traditionally used to treat inflammation-related disorders. EXPERIMENTAL APPROACH: A NF-κB luciferase reporter gene assay was used to identify NF-κB pathway inhibitors from H. sucuuba extracts. Monitoring of TNF-α-induced expression of the adhesion molecules VCAM-1, ICAM-1 and E-selectin by flow cytometry was used to confirm NF-κB inhibition in endothelial cells, and thioglycollate-induced peritonitis in mice to confirm effects in vivo. Western blotting and transfection experiments were used to investigate the mechanism of action of plumericin. KEY RESULTS: Plumericin inhibited NF-κB-mediated transactivation of a luciferase reporter gene (IC50 1 µM), abolished TNF-α-induced expression of the adhesion molecules VCAM-1, ICAM-1 and E-selectin in endothelial cells and suppressed thioglycollate-induced peritonitis in mice. Plumericin exerted its NF-κB pathway inhibitory effect by blocking IκB phosphorylation and degradation. Plumericin also inhibited NF-κB activation induced by transfection with the constitutively active catalytic subunit of the IκB kinase (IKK-ß), suggesting IKK involvement in the inhibitory action of this natural product. CONCLUSION AND IMPLICATIONS: Plumericin is a potent inhibitor of NF-κB pathways with a new chemical scaffold. It could be further explored as a novel anti-inflammatory lead compound.

Natural products in structure-assisted design of molecular cancer therapeutics.

Since the late 1990's, novel insights into molecular biology and carcinogenesis enabled the rational design of mechanism-based anticancer therapeutics. The large number of natural product (NP)-derived drugs currently under clinical evaluation and the recent approval of temsirolimus (Torisel) as a first mTOR protein kinase inhibitor indicate that NPs have to be considered not only as a seminal source of cytotoxic, but also as a source of molecularly targeted agents. Whereas molecular modeling is well established as an important and successful method to discover and rationalize bioactivities in medicinal chemistry research, its application has also proven to be also a powerful tool in the field of NPs. This review highlights the impact of computer-assisted approaches on NPs as molecularly targeted anticancer drugs. Examples of applications are provided focusing on innovative targets such as protein kinases, tumour vasculature, epigenetic modulators, heat shock protein (Hsp) 90, and direct apoptosis enhancers.

Strategies for efficient lead structure discovery from natural products.

This investigation aims to evaluate strategies for an efficient selection of bioactive compounds from the multitude and biodiversity of the plant kingdom. Statistics prove natural products (NPs) as a source leading most consistently to successful development of new drugs. However, there are several reasons why the interest in finding bioactive NPs has generally declined at several major pharmaceutical companies. Their substantial argument is that the research in this field is time-consuming, highly complex and ineffective. A more rational and economic search for new lead structures from nature must therefore be a priority in order to overcome these problems. In this paper, different strategies are described to exploit the molecular diversity of bioactive secondary metabolites, namely classical pharmacognostic approaches and computational methods. The latter include various data mining tools, like virtual screening filtering experiments using pharmacophore models, docking studies, and neural networks, which help to establish a relationship between chemical structure and biological activity. The strengths and weaknesses of these methods will be shown in this review. Focusing on selected targets within the arachidonic acid cascade (phospholipase A(2), 5-lipoxygenase, cyclooxygenase-1 and -2), several studies of successful discoveries in the field of anti-inflammatory NPs were scrutinized for the applied strategies. Both the compilation of relevant published data and recent studies supported by our own research clearly demonstrate the benefits of the synergistic effect of a hybridization of these strategies for an effective drug discovery from natural ingredients.

Integrated in silico tools for exploiting the natural products' bioactivity.

Whereas computational methods for molecular design are well established in medicinal chemistry research, their application in the field of natural products is still not exhaustively explored. This article gives a short introduction into both the potential for the application of computer-assisted approaches, such as pharmacophore modelling, virtual screening, docking, and neural networking to efficiently access the bioactive metabolites, and the requirements and limitations related to this specific field. The challenge is which selection criteria and/or multiple filtering tools to apply for a target-oriented isolation of potentially bioactive secondary metabolites. Application examples are provided where in silico tools and classical methods used by natural product scientists are used in an effort to maximize their efficacy in drug discovery. Thus, integrated computer-assisted strategies may help to process the huge amount of available structural and biological information in a reasonably short time for a straightforward search of bioactive natural products.

Application of the in combo screening approach for the discovery of non-alkaloid acetylcholinesterase inhibitors from Cichorium intybus.

Because of the direct correlation of cholinergic deficit and the severity of dementia, Alzheimer's disease is preferentially treated with acetylcholinesterase (AChE) inhibitors to supplement the acetylcholine level. In this study we focused on non-alkaloid AChE inhibitors from natural sources in order to discover new lead structures. In the course of in vitro extract screening of Tyrolean plants using an enzyme assay with Ellman's reagent, the dichloromethane extract of chicory roots (Cichorium intybus L.) showed a pronounced inhibitory effect on AChE. At a concentration of 1 mg extract/ml an inhibition of 70% was measured. Based on a 3D multi-conformational molecular-structure database consisting of secondary metabolites from C. intybus known from the relevant literature, virtual screening filtering experiments were conducted using both a feature-based pharmacophore model and a docking procedure. Some low molecular weight sesquiterpenoids exhibited distinct interactions with the pharmacophore model. In order to verify the applicability of this computer-aided strategy, an activity-guided fractionation of the chicory root extract was performed, which resulted in the isolation of two sesquiterpene lactones, 8-deoxylactucin and lactucopicrin, showing significant and dose-dependent inhibitory activity on AChE (IC(50) of 308.1 microM [CI(95) 243.9 - 405.3 microM] and 150.3 microM [CI(95) 100.8 - 188.1 microM], respectively). The two isolates were correctly predicted within the virtual screening process which corroborates the potential of the computer-assisted in combo screening approach for the discovery of the anti-cholinesterase compounds from C. intybus.