Medicinal plants have historically proven their value as a source of molecules with therapeutic potential, and nowadays still represent an important pool for the identification of novel drug leads. In the past decades, pharmaceutical industry focused mainly on libraries of synthetic compounds as drug discovery source. They are comparably easy to produce and resupply, and demonstrate good compatibility with established high throughput screening (HTS) platforms. However, at the same time there has been a declining trend in the number of new drugs reaching the market, raising renewed scientific interest in drug discovery from natural sources, despite of its known challenges. In this survey, a brief outline of historical development is provided together with a comprehensive overview of used approaches and recent developments relevant to plant-derived natural product drug discovery. Associated challenges and major strengths of natural product-based drug discovery are critically discussed. A snapshot of the advanced plant-derived natural products that are currently in actively recruiting clinical trials is also presented. Importantly, the transition of a natural compound from a "screening hit" through a "drug lead" to a "marketed drug" is associated with increasingly challenging demands for compound amount, which often cannot be met by re-isolation from the respective plant sources. In this regard, existing alternatives for resupply are also discussed, including different biotechnology approaches and total organic synthesis. While the intrinsic complexity of natural product-based drug discovery necessitates highly integrated interdisciplinary approaches, the reviewed scientific developments, recent technological advances, and research trends clearly indicate that natural products will be among the most important sources of new drugs also in the future.

Agonists of the nuclear receptor PPARγ are therapeutically used to combat hyperglycaemia associated with the metabolic syndrome and type 2 diabetes. In spite of being effective in normalization of blood glucose levels, the currently used PPARγ agonists from the thiazolidinedione type have serious side effects, making the discovery of novel ligands highly relevant. Natural products have proven historically to be a promising pool of structures for drug discovery, and a significant research effort has recently been undertaken to explore the PPARγ-activating potential of a wide range of natural products originating from traditionally used medicinal plants or dietary sources. The majority of identified compounds are selective PPARγ modulators (SPPARMs), transactivating the expression of PPARγ-dependent reporter genes as partial agonists. Those natural PPARγ ligands have different binding modes to the receptor in comparison to the full thiazolidinedione agonists, and on some occasions activate in addition PPARα (e.g. genistein, biochanin A, sargaquinoic acid, sargahydroquinoic acid, resveratrol, amorphastilbol) or the PPARγ-dimer partner retinoid X receptor (RXR; e.g. the neolignans magnolol and honokiol). A number of in vivo studies suggest that some of the natural product activators of PPARγ (e.g. honokiol, amorfrutin 1, amorfrutin B, amorphastilbol) improve metabolic parameters in diabetic animal models, partly with reduced side effects in comparison to full thiazolidinedione agonists. The bioactivity pattern as well as the dietary use of several of the identified active compounds and plant extracts warrants future research regarding their therapeutic potential and the possibility to modulate PPARγ activation by dietary interventions or food supplements.

Peroxisome proliferator-activated receptor gamma (PPARγ) agonists are clinically used to counteract hyperglycemia. However, so far experienced unwanted side effects, such as weight gain, promote the search for new PPARγ activators. We used a combination of in silico, in vitro, cell-based and in vivo models to identify and validate natural products as promising leads for partial novel PPARγ agonists. The natural product honokiol from the traditional Chinese herbal drug Magnolia bark was in silico predicted to bind into the PPARγ ligand binding pocket as dimer. Honokiol indeed directly bound to purified PPARγ ligand-binding domain (LBD) and acted as partial agonist in a PPARγ-mediated luciferase reporter assay. Honokiol was then directly compared to the clinically used full agonist pioglitazone with regard to stimulation of glucose uptake in adipocytes as well as adipogenic differentiation in 3T3-L1 pre-adipocytes and mouse embryonic fibroblasts. While honokiol stimulated basal glucose uptake to a similar extent as pioglitazone, it did not induce adipogenesis in contrast to pioglitazone. In diabetic KKAy mice oral application of honokiol prevented hyperglycemia and suppressed weight gain. We identified honokiol as a partial non-adipogenic PPARγ agonist in vitro which prevented hyperglycemia and weight gain in vivo. This observed activity profile suggests honokiol as promising new pharmaceutical lead or dietary supplement to combat metabolic disease, and provides a molecular explanation for the use of Magnolia in traditional medicine.

The identification of targets whose interaction is likely to result in the successful treatment of a disease is of growing interest for natural product scientists. In the current study we performed an exemplary application of a virtual parallel screening approach to identify potential targets for 16 secondary metabolites isolated and identified from the aerial parts of the medicinal plant Ruta graveolens L. Low energy conformers of the isolated constituents were simultaneously screened against a set of 2208 pharmacophore models generated in-house for the in silico prediction of putative biological targets, i. e., target fishing. Based on the predicted ligand-target interactions, we focused on three biological targets, namely acetylcholinesterase (AChE), the human rhinovirus (HRV) coat protein and the cannabinoid receptor type-2 (CB₂). For a critical evaluation of the applied parallel screening approach, virtual hits and non-hits were assayed on the respective targets. For AChE the highest scoring virtual hit, arborinine, showed the best inhibitory in vitro activity on AChE (IC₅₀ 34.7 μM). Determination of the anti-HRV-2 effect revealed 6,7,8-trimethoxycoumarin and arborinine to be the most active antiviral constituents with IC₅₀ values of 11.98 μM and 3.19 μM, respectively. Of these, arborinine was predicted virtually. Of all the molecules subjected to parallel screening, one virtual CB₂ ligand was obtained, i. e., rutamarin. Interestingly, in experimental studies only this compound showed a selective activity to the CB₂ receptor (Ki of 7.4 μM) by using a radioligand displacement assay. The applied parallel screening paradigm with constituents of R. graveolens on three different proteins has shown promise as an in silico tool for rational target fishing and pharmacological profiling of extracts and single chemical entities in natural product research. AChE:acetylcholinesterase CD₂:cannabinoid receptor type-2 CC₅₀:50 % cytotoxic concentration CPE:cytopathic effect 3D:three dimensional GNT:galanthamine HRV:human rhinovirus PDB:protein databank VS:virtual screening