Daniela Schuster

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.

Why Drugs Fail - A Study on Side Effects in New Chemical Entities

Over 90% of the market withdrawals were caused by drug toxicity. Hepatotoxicity and cardiovascular toxicity proved to be the major causes for two out of three market withdrawals in the respective time period. In clinical phases I-III 43% of drug development project terminations were due to insufficient efficacy of the investigated compound. The second important issue, which caused one third of the projects to be closed, was toxicity. ADME parameters and economic and other reasons played a minor role. The results of our study indicate that compared with previous studies on this subject, no major improvements have been achieved in the last decade.

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.

Parallel screening: a novel concept in pharmacophore modeling and virtual screening.

Parallel screening comprises a novel in silico method to predict the potential biological activities of a compound by screening it with a multitude of pharmacophore models. Our aim is to provide a fast, large-scale system that allows for virtual activity profiling. In this proof of principle study, carried out with the software tools LigandScout and Catalyst, we present a model work for the application of parallel pharmacophore-based virtual screening on a set of 50 structure-based pharmacophore models built for various viral targets and 100 antiviral compounds. The latter were screened against all pharmacophore models in order to determine if their biological targets could be correctly predicted via an enrichment of corresponding pharmacophores matching these ligands. The results demonstrate that the desired enrichment, that is, successful virtual activity profiling, was achieved for approximately 90% of all input molecules. We discuss descriptors for output validation, as well as various aspects influencing the analysis of the obtained activity profiles, and the effect of the utilized search modus for screening.

Pharmacophore Modeling and in Silico Screening for New P450 19 (Aromatase) Inhibitors

Cytochrome P450 19 (P450 19, aromatase) constitutes a successful target for the treatment of breast cancer. This study analyzes chemical features common to P450 19 inhibitors to develop ligand-based, selective pharmacophore models for this enzyme. The HipHop and HypoRefine algorithms implemented in the Catalyst software package were employed to create both common feature and quantitative models. The common feature model for P450 19 includes two ring aromatic features in its core and two hydrogen bond acceptors at the ends. The models were used as database search queries to identify active compounds from the NCI database.

Why is 11β-hydroxysteroid dehydrogenase type 1 facing the endoplasmic reticulum lumen?: Physiological relevance of the membrane topology of 11β-HSD1

11Beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1) is essential for the local activation of glucocorticoid receptors (GR). Unlike unliganded cytoplasmic GR, 11beta-HSD1 is an endoplasmic reticulum (ER)-membrane protein with lumenal orientation. Cortisone might gain direct access to 11beta-HSD1 by free diffusion across membranes, indirectly via intracellular binding proteins or, alternatively, by insertion into membranes. Membranous cortisol, formed by 11beta-HSD1 at the ER-lumenal side, might then activate cytoplasmic GR or bind to ER-lumenal secretory proteins. Compartmentalization of 11beta-HSD1 is important for its regulation by hexose-6-phosphate dehydrogenase (H6PDH), which regenerates cofactor NADPH in the ER lumen and stimulates oxoreductase activity. ER-lumenal orientation of 11beta-HSD1 is also essential for the metabolism of the alternative substrate 7-ketocholesterol (7KC), a major cholesterol oxidation product found in atherosclerotic plaques and taken up from processed cholesterol-rich food. An 11beta-HSD1 mutant adopting cytoplasmic orientation efficiently catalyzed the oxoreduction of cortisone but not 7KC, indicating access to cortisone from both sides of the ER-membrane but to 7KC only from the lumenal side. These aspects may be relevant for understanding the physiological role of 11beta-HSD1 and for developing therapeutic interventions to control glucocorticoid reactivation.

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.

Pharmacophore modeling and parallel screening for PPAR ligands

We describe the generation and validation of pharmacophore models for PPARs, as well as a large scale validation of the parallel screening approach by screening PPAR ligands against a large database of structure-based models. A large test set of 357 PPAR ligands was screened against 48 PPAR models to determine the best models for agonists of PPAR-α, PPAR-δ, and PPAR-γ. Afterwards, a parallel screen was performed using the 357 PPAR ligands and 47 structure-based models for PPARs, which were integrated into a 1537 models comprising in-house pharmacophore database, to assess the enrichment of PPAR ligands within the PPAR hypotheses. For these purposes, we categorized the 1537 database models into 181 protein targets and developed a score that ranks the retrieved targets for each ligand. Thus, we tried to find out if the concept of parallel screening is able to predict the correct pharmacological target for a set of compounds. The PPAR target was ranked first more often than any other target. This confirms the ability of parallel screening to forecast the pharmacological active target for a set of compounds.

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.