Judith M. Rollinger

Discovery and resupply of pharmacologically active plant-derived natural products: A review.

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.

Energy/Temperature Diagram and Compression Behavior of the Polymorphs of d-Mannitol

Three modifications of D-mannitol were produced and investigated: mod. I (mp 166.5 degrees C, heat of fusion 53.5 kJ mol(-1)), mod. II (mp 166 degrees C, heat of fusion 52.1 kJ mol(-1)), and mod. III (mp incongruent 150-158 degrees C, heat of transition, III to I 0.2 kJ mol(-1)). The measured densities are 1.490 +/- 0.000 g cm(-3) [95% confidence interval (CI)] for mod. I, 1.468 +/- 0.002 g cm(-3) (95% CI) for mod. II, and 1.499 +/- 0.004 g cm(-3) (95% CI) for mod. III. It was possible to relate the different modifications given in the literature to one of the three pure crystal forms or to mixtures of two or all three modifications. The thermodynamic relationship among the crystal forms is represented in a semi-schematic energy/temperature diagram. From these data we can conclude that mod. III is thermodynamically stable at absolute zero. It is enantiotropically related to mod. I and mod. II. FTIR and Raman spectra, differential scanning calorimetry curves, and X-ray powder patterns of these crystal forms are depicted for doubtless assignment in the future. The water uptake of the three modifications at 92% relative humidity and 25 degrees C is less than 1%. The differences of the heat capacities and the heats of solution between mod. II and III are not significant, whereas mod. I shows small significant differences compared with the other modifications. In addition, compaction studies of these crystal forms were performed by means of an instrumented hydraulic press. The results show that mod. III should have the best tableting behavior under these conditions.

Natural product agonists of peroxisome proliferator-activated receptor gamma (PPARγ): a review.

Graphical abstract

In silico target fishing for rationalized ligand discovery exemplified on constituents of Ruta graveolens

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 (CB (2)). 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 (IC (50) 34.7 muM). Determination of the anti-HRV-2 effect revealed 6,7,8-trimethoxycoumarin and arborinine to be the most active antiviral constituents with IC (50) values of 11.98 muM and 3.19 muM, respectively. Of these, arborinine was predicted virtually. Of all the molecules subjected to parallel screening, one virtual CB (2) ligand was obtained, i. e., rutamarin. Interestingly, in experimental studies only this compound showed a selective activity to the CB (2) receptor ( Ki of 7.4 muM) 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.

Virtual screening for the discovery of bioactive natural products

In this survey the impact of the virtual screening concept is discussed in the field of drug discovery from nature. Confronted by a steadily increasing number of secondary metabolites and a growing number of molecular targets relevant in the therapy of human disorders, the huge amount of information needs to be handled. Virtual screening filtering experiments already showed great promise for dealing with large libraries of potential bioactive molecules. It can be utilized for browsing databases for molecules fitting either an established pharmacophore model or a three dimensional (3D) structure of a macromolecular target. However, for the discovery of natural lead candidates the application of this in silico tool has so far almost been neglected. There are several reasons for that. One concerns the scarce availability of natural product (NP) 3D databases in contrast to synthetic libraries; another reason is the problematic compatibility of NPs with modern robotized high throughput screening (HTS) technologies. Further arguments deal with the incalculable availability of pure natural compounds and their often too complex chemistry. Thus research in this field is time-consuming, highly complex, expensive and ineffective. Nevertheless, naturally derived compounds are among the most favorable source of drug candidates. A more rational and economic search for new lead structures from nature must therefore be a priority in order to overcome these problems. Here we demonstrate some basic principles, requirements and limitations of virtual screening strategies and support their applicability in NP research with already performed studies. A sensible exploitation of the molecular diversity of secondary metabolites however asks for virtual screening concepts that are interfaced with well-established strategies from classical pharmacognosy that are used in an effort to maximize their efficacy in drug discovery. Such integrated virtual screening workflows are outlined here and shall help to motivate NP researchers to dare a step towards this powerful in silico tool.

Antiviral potential and molecular insight into neuraminidase inhibiting diarylheptanoids from Alpinia katsumadai.

At present, neuraminidase (NA) inhibitors are the mainstay of pharmacological strategies to fight against global pandemic influenza. In the search for new antiviral drug leads from nature, the seed extract of Alpinia katsumadai has been phytochemically investigated. Among the six isolated constituents, four diarylheptanoids showed in vitro NA inhibitory activities in low micromolar ranges against human influenza virus A/PR/8/34 of subtype H1N1. The most promising constituent, katsumadain A (4; IC(50) = 1.05 +/- 0.42 microM), also inhibited the NA of four H1N1 swine influenza viruses, with IC(50) values between 0.9 and 1.64 muM, and showed antiviral effects in plaque reduction assays. Considering the flexible loop regions of NA, extensive molecular dynamics (MD) simulations were performed to study the putative binding mechanism of the T-shaped diarylheptanoid 4. Docking results showed well-established interactions between the protein and the core of this novel NA-inhibiting natural scaffold, excellent surface complementarity to the simulated binding pocket, and concordance with experimentally derived SAR data.

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.

Computer-Aided Discovery, Validation, and Mechanistic Characterization of Novel Neolignan Activators of Peroxisome Proliferator-Activated Receptor gamma

Peroxisome proliferator-activated receptor gamma (PPARγ) agonists are used for the treatment of type 2 diabetes and metabolic syndrome. However, the currently used PPARγ agonists display serious side effects, which has led to a great interest in the discovery of novel ligands with favorable properties. The aim of our study was to identify new PPARγ agonists by a PPARγ pharmacophore–based virtual screening of 3D natural product libraries. This in silico approach led to the identification of several neolignans predicted to bind the receptor ligand binding domain (LBD). To confirm this prediction, the neolignans dieugenol, tetrahydrodieugenol, and magnolol were isolated from the respective natural source or synthesized and subsequently tested for PPARγ receptor binding. The neolignans bound to the PPARγ LBD with EC50 values in the nanomolar range, exhibiting a binding pattern highly similar to the clinically used agonist pioglitazone. In intact cells, dieugenol and tetrahydrodieugenol selectively activated human PPARγ-mediated, but not human PPARα- or -β/δ-mediated luciferase reporter expression, with a pattern suggesting partial PPARγ agonism. The coactivator recruitment study also demonstrated partial agonism of the tested neolignans. Dieugenol, tetrahydrodieugenol, and magnolol but not the structurally related eugenol induced 3T3-L1 preadipocyte differentiation, confirming effectiveness in a cell model with endogenous PPARγ expression. In conclusion, we identified neolignans as novel ligands for PPARγ, which exhibited interesting activation profiles, recommending them as potential pharmaceutical leads or dietary supplements.

Honokiol: A non-adipogenic PPARγ agonist from nature☆

Background 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. Methods 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. Results 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. Conclusion We identified honokiol as a partial non-adipogenic PPARγ agonist in vitro which prevented hyperglycemia and weight gain in vivo. General significance 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.

Structure-based virtual screening for the discovery of natural inhibitors for human rhinovirus coat protein.

Inhibitors of the human rhinovirus (HRV) coat protein are promising candidates to treat and prevent a number of upper respiratory diseases. The aim of this study was to find antiviral compounds from nature, focusing on the HRV coat protein. Through computational structure-based screening of an in-house 3D database containing 9676 individual plant metabolites from ancient herbal medicines, combined with knowledge from traditional use, we selected sesquiterpene coumarins from the gum resin asafetida as promising natural products. Chromatographic separation steps resulted in the isolation of microlobidene (1), farnesiferol C (2), farnesiferol B (3), and kellerin (4). Determination of the inhibition of the HRV-induced cytopathic effect for serotypes 1A, 2, 14, and 16 revealed a dose-dependent and selective antirhinoviral activity against serotype 2 for asafetida (IC50 = 11.0 microg/mL) and its virtually predicted constituents 2 (IC50 = 2.5 microM) and 3 (IC50 = 2.6 microM). Modeling studies helped to rationalize the retrieved results.