Multitargeted molecular docking and dynamics simulation studies of flavonoids and volatile components from the peel of Citrus sinensis L. (Osbeck) against specific tumor protein markers

Citrus sinensis (L.) Osbeck (Rutaceae), commonly known as the sweet orange, is a popular and widely consumed fruit with several medicinal properties. The present study aimed to perform the in silico screening of 18 flavonoids and eight volatile components from the peel of C. sinensis against apoptotic and inflammatory proteins, metalloprotease, and tumor suppressor markers. Flavonoids obtained higher probabilities than volatile components against selected anti-cancer drug targets. Hence, the data from the binding energies against the essential apoptotic and cell proliferation proteins substantiate that they may be promising compounds in developing effective candidates to block cell growth, proliferation, and induced cell death by activating the apoptotic pathway. Further, the binding stability of the selected targets and the corresponding molecules were analyzed by 100 ns molecular dynamics (MD) simulations. Chlorogenic acid has the most binding affinity against the important anti-cancer targets iNOS, MMP-9, and p53. The congruent binding mode to different drug targets focused on cancer shown by chlorogenic acid suggests that it may be a compound with significant therapeutic potential. Moreover, the binding energy predictions indicated that the compound had stable electrostatic and van der Waal energies. Thus, our data reinforce the medicinal importance of flavonoids from C. sinensis and expand the need for more studies, seeking to optimize results and amplify the impacts of further in vitro and in vivo studies. Communicated by Ramaswamy H. Sarma.

Computational Studies Applied to Linalool and Citronellal Derivatives Against Alzheimer's and Parkinson's Disorders: A Review with Experimental Approach

Alzheimer's and Parkinson's are neurodegenerative disorders that affect a great number of people around the world, seriously compromising the quality of life of individuals, due to motor and cognitive damage. In these diseases, pharmacological treatment is used only to alleviate symptoms. This emphasizes the need to discover alternative molecules for use in prevention. Using Molecular Docking, this review aimed to evaluate the anti-Alzheimer's and anti-Parkinson's activity of linalool and citronellal, as well as their derivatives. Before performing Molecular Docking simulations, the compounds' pharmacokinetic characteristics were evaluated. For Molecular Docking, 7 chemical compounds derived from citronellal, and 10 compounds derived from linalool, and molecular targets involved in Alzheimer's and Parkinson's pathophysiology were selected. According to the Lipinski rules, the compounds under study presented good oral absorption and bioavailability. For toxicity, some tissue irritability was observed. For Parkinson-related targets, the citronellal and linalool derived compounds revealed excellent energetic affinity for α-Synuclein, Adenosine Receptors, Monoamine Oxidase (MAO), and Dopamine D1 receptor proteins. For Alzheimer disease targets, only linalool and its derivatives presented promise against BACE enzyme activity. The compounds studied presented high probability of modulatory activity against the disease targets under study, and are potential candidates for future drugs.

Predicting Endocrine Disruption Using Conformal Prediction - A Prioritization Strategy to Identify Hazardous Chemicals with Confidence

Receptor-mediated molecular initiating events (MIEs) and their relevance in endocrine activity (EA) have been highlighted in literature. More than 15 receptors have been associated with neurodevelopmental adversity and metabolic disruption. MIEs describe chemical interactions with defined biological outcomes, a relationship that could be described with quantitative structure-activity relationship (QSAR) models. QSAR uncertainty can be assessed using the conformal prediction (CP) framework, which provides similarity (i.e., nonconformity) scores relative to the defined classes per prediction. CP calibration can indirectly mitigate data imbalance during model development, and the nonconformity scores serve as intrinsic measures of chemical applicability domain assessment during screening. The focus of this work was to propose an in silico predictive strategy for EA. First, 23 QSAR models for MIEs associated with EA were developed using high-throughput data for 14 receptors. To handle the data imbalance, five protocols were compared, and CP provided the most balanced class definition. Second, the developed QSAR models were applied to a large data set (∼55,000 chemicals), comprising chemicals representative of potential risk for human exposure. Using CP, it was possible to assess the uncertainty of the screening results and identify model strengths and out of domain chemicals. Last, two clustering methods, t-distributed stochastic neighbor embedding and Tanimoto similarity, were used to identify compounds with potential EA using known endocrine disruptors as reference. The cluster overlap between methods produced 23 chemicals with suspected or demonstrated EA potential. The presented models could be utilized for first-tier screening and identification of compounds with potential biological activity across the studied MIEs.

Herbicide Exposure and Toxicity to Aquatic Primary Producers

The aim of the present review was to give an overview of the current state of science concerning herbicide exposure and toxicity to aquatic primary producers. To this end we assessed the open literature, revealing the widespread presence of (mixtures of) herbicides, inevitably leading to the exposure of non-target primary producers. Yet, herbicide concentrations show strong temporal and spatial variations. Concerning herbicide toxicity, it was concluded that the most sensitive as well as the least sensitive species differed per herbicide and that the observed effect concentrations for some herbicides were rather independent from the exposure time. More extensive ecotoxicity testing is required, especially considering macrophytes and marine herbicide toxicity. Hence, it was concluded that the largest knowledge gap concerns the effects of sediment-associated herbicides on primary producers in the marine/estuarine environment. Generally, there is no actual risk of waterborne herbicides to aquatic primary producers. Still, median concentrations of atrazine and especially of diuron measured in China, the USA and Europe represented moderate risks for primary producers. Maximum concentrations due to misuse and accidents may even cause the exceedance of almost 60% of the effect concentrations plotted in SSDs. Using bioassays to determine the effect of contaminated water and sediment and to identify the herbicides of concern is a promising addition to chemical analysis, especially for the photosynthesis-inhibiting herbicides using photosynthesis as endpoint in the bioassays. This review concluded that to come to a reliable herbicide hazard and risk assessment, an extensive catch-up must be made concerning macrophytes, the marine environment and especially sediment as overlooked and understudied environmental compartments.

Classification of baseline toxicants for QSAR predictions to replace fish acute toxicity studies

Fish acute toxicity studies are required for environmental hazard and risk assessment of chemicals by national and international legislations such as REACH, the regulations of plant protection products and biocidal products, or the GHS (globally harmonised system) for classification and labelling of chemicals. Alternative methods like QSARs (quantitative structure-activity relationships) can replace many ecotoxicity tests. However, complete substitution of in vivo animal tests by in silico methods may not be realistic. For the so-called baseline toxicants, it is possible to predict the fish acute toxicity with sufficient accuracy from log K_ow and, hence, valid QSARs can replace in vivo testing. In contrast, excess toxicants and chemicals not reliably classified as baseline toxicants require further in silico, in vitro or in vivo assessments. Thus, the critical task is to discriminate between baseline and excess toxicants. For fish acute toxicity, we derived a scheme based on structural alerts and physicochemical property thresholds to classify chemicals as either baseline toxicants (=predictable by QSARs) or as potential excess toxicants (=not predictable by baseline QSARs). The step-wise approach identifies baseline toxicants (true negatives) in a precautionary way to avoid false negative predictions. Therefore, a certain fraction of false positives can be tolerated, i.e. baseline toxicants without specific effects that may be tested instead of predicted. Application of the classification scheme to a new heterogeneous dataset for diverse fish species results in 40% baseline toxicants, 24% excess toxicants and 36% compounds not classified. Thus, we can conclude that replacing about half of the fish acute toxicity tests by QSAR predictions is realistic to be achieved in the short-term. The long-term goals are classification criteria also for further groups of toxicants and to replace as many in vivo fish acute toxicity tests as possible with valid QSAR predictions.

Assessing herbal products with health claims

Herbs, herbal extracts, or phytochemicals are broadly used as foods, drugs, and as traditional medicines. These are well regulated in Europe, with thorough controls on both safety and efficacy or validity of health claims. However, the distinction between medicines and foods with health claims is not always clear. In addition, there are several cases of herbal products that claim benefits that are not scientifically demonstrated. This review details the European Union (EU) legislative framework that regulates the approval and marketing of herbal products bearing health claims as well as the scientific evidence that is needed to support such claims. To illustrate the latter, we focus on phytoecdysteroid (PE)-containing preparations, generally sold to sportsmen and bodybuilders. We review the limited published scientific evidence that supports claims for these products in humans. In addition, we model the in silico binding between different PEs and human nuclear receptors and discuss the implications of these putative bindings in terms of the mechanism of action of this family of compounds. We call for additional research to validate the safety and health-promoting properties of PEs and other herbal compounds, for the benefit of all consumers.

Integrated testing strategies for safety assessments

Despite the fact that toxicology uses many stand-alone tests, a systematic combination of several information sources very often is required: Examples include: when not all possible outcomes of interest (e.g., modes of action), classes of test substances (applicability domains), or severity classes of effect are covered in a single test; when the positive test result is rare (low prevalence leading to excessive false-positive results); when the gold standard test is too costly or uses too many animals, creating a need for prioritization by screening. Similarly, tests are combined when the human predictivity of a single test is not satisfactory or when existing data and evidence from various tests will be integrated. Increasingly, kinetic information also will be integrated to make an in vivo extrapolation from in vitro data. Integrated Testing Strategies (ITS) offer the solution to these problems. ITS have been discussed for more than a decade, and some attempts have been made in test guidance for regulations. Despite their obvious potential for revamping regulatory toxicology, however, we still have little guidance on the composition, validation, and adaptation of ITS for different purposes. Similarly, Weight of Evidence and Evidence-based Toxicology approaches require different pieces of evidence and test data to be weighed and combined. ITS also represent the logical way of combining pathway-based tests, as suggested in Toxicology for the 21st Century. This paper describes the state of the art of ITS and makes suggestions as to the definition, systematic combination, and quality assurance of ITS.

Physiological and molecular effect assessment versus physico-chemistry based mode of action schemes: Daphnia magna exposed to narcotics and polar narcotics

Structural analogues are assumed to elicit toxicity via similar predominant modes of action (MOAs). Currently, MOA categorization of chemicals in environmental risk assessment is mainly based on the physicochemical properties of potential toxicants. It is often not known whether such classification schemes are also supported by mechanistic biological data. In this study, the toxic effects of two groups of structural analogues (alcohols and anilines) with predefined MOA (narcotics and polar narcotics) were investigated at different levels of biological organization (gene transcription, energy reserves, and growth). Chemical similarity was not indicative of a comparable degree of toxicity and a similar biological response. Categorization of the test chemicals based on the different biological responses (growth, energy use, and gene transcription) did not result in a classification of the predefined narcotics versus the predefined polar narcotics. Moreover, gene transcription based clustering profiles were indicative of the observed effects at higher level of biological organization. Furthermore, a small set of classifier genes could be identified that was discriminative for the clustering pattern. These classifier genes covaried with the organismal and physiological responses. Compared to the physico-chemistry based MOA classification, integrated biological multilevel effect assessment can provide the necessary MOA information that is crucial in high-quality environmental risk assessment. Our findings support the view that transcriptomics tools hold considerable promise to be used in biological response based mechanistic profiling of potential (eco)toxicants.

Toxicity ranking and toxic mode of action evaluation of commonly used agricultural adjuvants on the basis of bacterial gene expression profiles

The omnipresent group of pesticide adjuvants are often referred to as “inert” ingredients, a rather misleading term since consumers associate this term with “safe”. The upcoming new EU regulation concerning the introduction of plant protection products on the market (EC1107/2009) includes for the first time the demand for information on the possible negative effects of not only the active ingredients but also the used adjuvants. This new regulation requires basic toxicological information that allows decisions on the use/ban or preference of use of available adjuvants. In this study we obtained toxicological relevant information through a multiple endpoint reporter assay for a broad selection of commonly used adjuvants including several solvents (e.g. isophorone) and non-ionic surfactants (e.g. ethoxylated alcohols). The used assay allows the toxicity screening in a mechanistic way, with direct measurement of specific toxicological responses (e.g. oxidative stress, DNA damage, membrane damage and general cell lesions). The results show that the selected solvents are less toxic than the surfactants, suggesting that solvents may have a preference of use, but further research on more compounds is needed to confirm this observation. The gene expression profiles of the selected surfactants reveal that a phenol (ethoxylated tristyrylphenol) and an organosilicone surfactant (ethoxylated trisiloxane) show little or no inductions at EC₂₀ concentrations, making them preferred surfactants for use in different applications. The organosilicone surfactant shows little or no toxicity and good adjuvant properties. However, this study also illustrates possible genotoxicity (induction of the bacterial SOS response) for several surfactants (POEA, AE, tri-EO, EO FA and EO NP) and one solvent (gamma-butyrolactone). Although the number of compounds that were evaluated is rather limited (13), the results show that the used reporter assay is a promising tool to rank commonly used agricultural adjuvants based on toxicity and toxic mode of action data.

Integrated Testing Strategies and the Prediction of Toxic Hazard

Over the past 20-30 years there has been a move towards reducing the use of animals in toxicity testing for industrial chemicals, pharmaceuticals, personal care and household products, for economic, scientific and animal welfare reasons. The need for alternatives has been emphasised by the EU REACH regulation, which requires the evaluation of tens of thousands of new and existing chemicals, and also within the pharmaceutical industry owing to the increasing rate at which drugs are being withdrawn from the market due to adverse effects not detected during preclinical testing. Significant effort is being placed into the development of non-animal test procedures using existing data, bioinformatics, in chemico, in silico and in vitro approaches and ethical human studies. Information from these diverse sources needs to be used intelligently and selectively leading to the development of what have become known as Integrated Testing Strategies (ITS). In this chapter factors that need to be considered in the development, evaluation, acceptance and use of ITS will be discussed.