In Silico Models for Predicting Acute Systemic Toxicity.

In this chapter, we give a brief overview of the regulatory requirements for acute systemic toxicity information in the European Union, and we review structure-based computational models that are available and potentially useful in the assessment of acute systemic toxicity. Emphasis is placed on quantitative structure-activity relationship (QSAR) models implemented by means of a range of software tools. The most recently published literature models for acute systemic toxicity are also discussed, and perspectives for future developments in this field are offered.

Dual SMO/BRAF Inhibition by Flavonolignans from Silybum marianum †.

Silymarin is the standardized extract from the fruits of Silybum marianum (L.) Gaertn., a well-known hepatoprotectant and antioxidant. Recently, bioactive compounds of silymarin, i.e., silybins and their 2,3-dehydro derivatives, have been shown to exert anticancer activities, yet with unclear mechanisms. This study combines in silico and in vitro methods to reveal the potential interactions of optically pure silybins and dehydrosilybins with novel protein targets. The shape and chemical similarity with approved drugs were evaluated in silico, and the potential for interaction with the Hedgehog pathway receptor Smoothened (SMO) and BRAF kinase was confirmed by molecular docking. In vitro studies on SMO and BRAF V600E kinase activity and in BRAF V600E A-375 human melanoma cell lines were further performed to examine their effects on these proteins and cancer cell lines and to corroborate computational predictions. Our in silico results direct to new potential targets of silymarin constituents as dual inhibitors of BRAF and SMO, two major targets in anticancer therapy. The experimental studies confirm that BRAF kinase and SMO may be involved in mechanisms of anticancer activities, demonstrating dose-dependent profiles, with dehydrosilybins showing stronger effects than silybins. The results of this work outline the dual SMO/BRAF effect of flavonolignans from Silybum marianum with potential clinical significance. Our approach can be applied to other natural products to reveal their potential targets and mechanism of action.

Molecular Modeling Approach to Study the PPARγ-Ligand Interactions.

The chapter is focused on methods relevant for predictive toxicology and computer-aided drug design (adverse outcome pathway development, pharmacophore modeling, docking, and 3D QSAR analysis) and applied to study interactions between peroxisome proliferator-activated receptor γ (PPARγ) and its ligands. The methods have been combined to develop an integrated in silico approach allowing both to predict potential PPARγ-mediated hepatotoxicity of receptor's full agonists, thus supporting hazard characterization, and to identify naturally derived antidiabetic triterpenoids potentially acting through PPARγ partial agonism.

In vitro and in silico studies of the membrane permeability of natural flavonoids from Silybum marianum (L.) Gaertn. and their derivatives.

BACKGROUND: In recent years the number of natural products used as pharmaceuticals, components of dietary supplements and cosmetics has increased tremendously requiring more extensive evaluation of their pharmacokinetic properties. PURPOSE: This study aims at combining in vitro and in silico methods to evaluate the gastrointestinal absorption (GIA) of natural flavonolignans from milk thistle (Silybum marianum (L.) Gaertn.) and their derivatives. METHODS: A parallel artificial membrane permeability assay (PAMPA) was used to evaluate the transcellular permeability of the plant main components. A dataset of 269 compounds with measured PAMPA values and specialized software tools for calculating molecular descriptors were utilized to develop a quantitative structure-activity relationship (QSAR) model to predict PAMPA permeability. RESULTS: The PAMPA permeabilities of 7 compounds constituting the main components of the milk thistle were measured and their GIA was evaluated. A freely-available and easy to use QSAR model predicting PAMPA permeability from calculated physico-chemical molecular descriptors was derived and validated on an external dataset of 783 compounds with known GIA. The predicted permeability values correlated well with obtained in vitro results. The QSAR model was further applied to predict the GIA of 31 experimentally untested flavonolignans. CONCLUSIONS: According to both in vitro and in silico results most flavonolignans are highly permeable in the gastrointestinal tract, which is a prerequisite for sufficient bioavailability and use as lead structures in drug development. The combined in vitro/in silico approach can be used for the preliminary evaluation of GIA and to guide further laboratory experiments on pharmacokinetic characterization of bioactive compounds, including natural products.

Molecular determinants of PPARγ partial agonism and related in silico/in vivo studies of natural saponins as potential type 2 diabetes modulators.

The metabolic syndrome, which includes hypertension, type 2 diabetes (T2D) and obesity, has reached an epidemic-like scale. Saponins and sapogenins are considered as valuable natural products for ameliorating this pathology, possibly through the nuclear receptor PPARγ activation. The aims of this study were: to look for in vivo antidiabetic effects of a purified saponins' mixture (PSM) from Astragalus corniculatus Bieb; to reveal by in silico methods the molecular determinants of PPARγ partial agonism, and to investigate the potential PPARγ participation in the PSM effects. In the in vivo experiments spontaneously hypertensive rats (SHRs) with induced T2D were treated with PSM or pioglitazone as a referent PPARγ full agonist, and pathology-relevant biochemical markers were analysed. The results provided details on the PSM modulation of the glucose homeostasis and its potential mechanism. The in silico studies focused on analysis of the protein-ligand interactions in crystal structures of human PPARγ-partial agonist complexes, pharmacophore modelling and molecular docking. They outlined key pharmacophoric features, typical for the PPARγ partial agonists, which were used for pharmacophore-based docking of the main PSM sapogenin. The in silico studies, strongly suggest possible involvement of PPARγ-mediated mechanisms in the in vivo antidiabetic and antioxidant effects of PSM from A. corniculatus.

Natural modulators of nonalcoholic fatty liver disease: Mode of action analysis and in silico ADME-Tox prediction.

Nonalcoholic fatty liver disease (NAFLD) is considered to be the most common chronic liver disease. The discovery of natural product-based NAFLD modulators requires a more comprehensive study of their modes of action (MoAs). In this study we analysed available in the literature data for 26 naturally-derived compounds associated with experimental evidence for NAFLD alleviation and outlined potential biomolecular targets and a network of pharmacological MoAs for 12 compounds with the highest number of experimentally supported MoA key events, modulated by them. Despite the general perception that the therapeutic agents of natural origin are safe, an evaluation of ADME-Tox properties of these compounds has also been performed in order to estimate their suitability as drug candidates. We evaluated how the investigated structures fit to Lipinski's "Rule of five" and predicted their potential Phase I biotransformation pathways and toxicological effects using the ACD/Percepta platform, and the Meteor Nexus and Derek Nexus knowledge-based systems. Our results revealed the potential of the studied compounds as lead structures and outlined those of them that needed further optimisation of their pharmacokinetic profiles. The presented combined MoA/in silico approach could be extrapolated to naturally-derived and pathology-relevant lead structures with other biological activities. It could direct their optimisation by a mechanistically justified in silico evaluation.

ADME/Tox Properties and Biochemical Interactions of Silybin Congeners: In silico Study.

Silymarin, the active constituent of Silybum marianum (milk thistle), and its main component, silybin, are products with well-known hepatoprotective, cytoprotective, antioxidant, and chemopreventative properties. Despite substantial in vitro and in vivo investigations of these flavonolignans, their mechanisms of action and potential toxic effects are not fully defined. In this study we explored important ADME/Tox properties and biochemical interactions of selected flavonolignans using in silico methods. A quantitative structure-activity relationship (QSAR) model based on data from a parallel artificial membrane permeability assay (PAMPA) was used to estimate bioavailability after oral administration. Toxic effects and metabolic transformations were predicted using the knowledge-based expert systems Derek Nexus and Meteor Nexus (Lhasa Ltd). Potential estrogenic activity of the studied silybin congeners was outlined. To address further the stereospecificity of this effect the stereoisomeric forms of silybin were docked into the ligand-binding domain of the human estrogen receptor alpha (ERa) (MOE software, CCG). According to our results both stereoisomers can be accommodated into the ERa active site, but different poses and interactions were observed for silybin A and silybin B.

In Silico Models for Acute Systemic Toxicity.

In this chapter, we give an overview of the regulatory requirements for acute systemic toxicity information in the European Union, and we review the availability of structure-based computational models that are available and potentially useful in the assessment of acute systemic toxicity. The most recently published literature models for acute systemic toxicity are also discussed, and perspectives for future developments in this field are offered.

Molecular modelling study of the PPARγ receptor in relation to the mode of action/adverse outcome pathway framework for liver steatosis.

The comprehensive understanding of the precise mode of action and/or adverse outcome pathway (MoA/AOP) of chemicals has become a key step toward the development of a new generation of predictive toxicology tools. One of the challenges of this process is to test the feasibility of the molecular modelling approaches to explore key molecular initiating events (MIE) within the integrated strategy of MoA/AOP characterisation. The description of MoAs leading to toxicity and liver damage has been the focus of much interest. Growing evidence underlines liver PPARγ ligand-dependent activation as a key MIE in the elicitation of liver steatosis. Synthetic PPARγ full agonists are of special concern, since they may trigger a number of adverse effects not observed with partial agonists. In this study, molecular modelling was performed based on the PPARγ complexes with full agonists extracted from the Protein Data Bank. The receptor binding pocket was analysed, and the specific ligand-receptor interactions were identified for the most active ligands. A pharmacophore model was derived, and the most important pharmacophore features were outlined and characterised in relation to their specific role for PPARγ activation. The results are useful for the characterisation of the chemical space of PPARγ full agonists and could facilitate the development of preliminary filtering rules for the effective virtual ligand screening of compounds with PPARγ full agonistic activity.