In Silico Toxicological Screening of Natural Products

Safety assessment of natural products in Malaysia: current practices, challenges, and new strategies

The belief that natural products are inherently safe is a primary reason for consumers to choose traditional medicines and herbal supplements for health maintenance and disease prevention. Unfortunately, some natural products on the market have been found to contain toxic compounds, such as heavy metals and microbes, as well as banned ingredients such as aristolochic acids. It shows that the existing regulatory system is inadequate and highlights the importance of thorough safety evaluations. In Malaysia, the National Pharmaceutical Regulatory Agency is responsible for the regulatory control of medicinal products and cosmetics, including natural products. For registration purpose, the safety of natural products is primarily determined through the review of documents, including monographs, research articles and scientific reports. One of the main factors hampering safety evaluations of natural products is the lack of toxicological data from animal studies. However, international regulatory agencies such as the European Food Safety Authority and the United States Food and Drug Administration are beginning to accept data obtained using alternative strategies such as non-animal predictive toxicological tools. Our paper discusses the use of state-of-the-art techniques, including chemometrics, in silico modelling and omics technologies and their applications to the safety assessments of natural products.

Natural product remedies for COVID-19: A focus on safety

Infection by the novel coronavirus SARS-CoV-2 causing the coronavirus disease (COVID-19), is currently a global pandemic with more than two million deaths to date. Though a number of vaccines have recently been approved against the virus, availability remains a big challenge, and also acceptance by most people has become a big debate. This review discusses possible/proposed natural product remedies and some major conventional treatment options used to manage the infection and, safety concerns on the use of unproven or unapproved health products against COVID-19. An extensive literature review indicated that the influx of unproven and unapproved health products in the global market are on the rise, leading to various forms of self- medication. To this effect, there have been warnings by the United States Food and Drug Administration and the World Health Organisation against the use of such products. Conventional drugs such as remdesivir, chloroquine/hydroxychloroquine and dexamethasone are the major proposed drugs that are currently undergoing clinical trials for the management of this disease. Efforts are being made globally in the search for possible therapeutics which may be the best way to eradicating this disease. Some countries have approved the use of natural products in the management of COVID-19, despite little or no clinical evidence on their efficacy and safety. Natural products may hold a great potential in the fight against COVID-19 but without detailed clinical trials, their potency against the virus and their safe use cannot be established. To attain this goal, extensive research followed by clinical studies are needed. Collaborative efforts between researchers, clinicians, governments and traditional medicinal practitioners in the search and development of safe and effective therapeutics from natural products for the treatment of COVID-19 could be a potential option.

In silico study for prediction of novel bioactivities of the endophytic fungal alkaloid, mycoleptodiscin B for human targets

Mycoleptodiscin B is a natural product extracted from the endophytic fungus Mycoleptodiscus sp. found in Sri Lanka and Panama with experimentally unexplored activities for human targets. In this study, a computational methodology was applied to determine druggable targets of mycoleptodiscin B. According to the computational toxicity and pharmacokinetics assessment, mycoleptodiscin B was proven to be a suitable drug candidate. Druggable targets for this compound, aromatase, acidic plasma glycoprotein and androgen receptor, were predicted using reverse docking. A two-step validation of those targets was performed using conventional molecular docking and molecular dynamic (MD) simulations, resulting in aromatase being determined as the potential therapeutic target. Based on molecular mechanics/Generalized Born Surface Area (GBSA) free energies and ligand stability inside the active site cavity during its 120 ns MD run, it can be concluded that mycoleptodiscin B is a potent aromatase inhibitor and could be subjected to further in vitro and in vivo experiments in the drug development pipeline. Consequently, natural product chemists can quickly identify the hidden medicinal properties of their miracle compounds using the computational approach applied in this research.

A scientometric visualization analysis for global toxicology and pharmacology research of natural products from 1962 to 2018

BACKGROUND

A growing number of studies have been focused on the medicinal potential of natural products since 1962, while few scholars have analyzed the existing documents comprehensively.

PURPOSE

Aiming to visualize the researches on toxicology and pharmacology of natural products (TPNP) published between 1962 and 2018, as well as to reveal their spatiotemporal patterns, a scientometric analysis with 3210 relevant documents collected from Web of Science was conducted in this study.

RESULTS

The most prominent contributors of TPNP research are mainly from the USA, China, Brazil, India and Germany. The knowledge domains of TPNP research focus mainly on the topics of (1) traditional Chinese medicine, (2) richardia grandiflora, (3) chemical conversion, (4) new generation, (5) modern medicine, (6) intelligent mixture, (7) hplc-based activity. Most countries have recognized the pharmaceutical potential of natural products, and have paid more attention to the pharmacological and toxicological characteristics of natural products in the past decade. Future TPNP research tends to focus more on complex analysis of mechanisms for diseases treatment, such as toxicology and pharmacology.

CONCLUSION

This research has firstly demonstrated a comprehensive knowledge map for the existing toxicological and pharmacological researches of natural products, which offered essential instructions on medical application of natural products to future research.

Prediction of toxicity of secondary metabolites

The prediction of toxicological endpoints has gained broad acceptance; it is widely applied in early stages of drug discovery as well as for impurities obtained in the production of generic or equivalent products. In this work, we describe methodologies for the prediction of toxicological endpoints compounds, with a particular focus on secondary metabolites. Case studies include toxicity prediction of natural compound databases with anti-diabetic, anti-malaria and anti-HIV properties.

Cheminformatics Explorations of Natural Products

The chemistry of natural products is fascinating and has continuously attracted the attention of the scientific community for many reasons including, but not limited to, biosynthesis pathways, chemical diversity, the source of bioactive compounds and their marked impact on drug discovery. There is a broad range of experimental and computational techniques (molecular modeling and cheminformatics) that have evolved over the years and have assisted the investigation of natural products. Herein, we discuss cheminformatics strategies to explore the chemistry and applications of natural products. Since the potential synergisms between cheminformatics and natural products are vast, we will focus on three major aspects: (1) exploration of the chemical space of natural products to identify bioactive compounds, with emphasis on drug discovery; (2) assessment of the toxicity profile of natural products; and (3) diversity analysis of natural product collections and the design of chemical collections inspired by natural sources.

In silico genotoxicity and carcinogenicity prediction for food-relevant secondary plant metabolites

Humans are exposed to thousands of different secondary plant metabolites which may have beneficial health effects, but numerous compounds may also have toxic potential. In the present study we have examined the genotoxic and carcinogenic potential of 609 food-relevant phytochemicals by using computer models for toxicity prediction. We developed a scoring method and combined the results of different models to increase the predictive power. A combination of the VEGA models SARpy, KNN, ISS, and CAESAR, and of the LAZAR model "Salmonella typhimurium" for genotoxicity prediction performed better than the single models regarding specificity and accuracy. Statistical evaluation of the combined model for carcinogenicity prediction was not possible due to the low number of substances suitable for model validation. The in silico results of the present exercise will be useful for priority setting purposes regarding future risk assessment of secondary plant metabolites. Based on our analysis, (-)-asimilobine, aloin, annoretine, chrysothrone, coptisine, elymoclavine, and thalicminine were predicted to be genotoxic with high probability and may therefore be selected for subsequent experimental genotoxicity testing. Moreover, the class of pyrrolizidine alkaloids is suggested to be a high priority subject for further studies as these substances have been predicted to be carcinogenic with high probability.

The potential role of in silico approaches to identify novel bioactive molecules from natural resources

In recent years, integration of in silico approaches to natural product (NP) research reawakened the declined interest in NP-based drug discovery efforts. In particular, advancements in cheminformatics enabled comparison of NP databases with contemporary small-molecule libraries in terms of molecular properties and chemical space localizations. Virtual screening and target fishing approaches were successful in recognizing the untold macromolecular targets for NPs to exploit the unmet therapeutic needs. Developments in molecular docking and scoring methods along with molecular dynamics enabled to predict the target-ligand interactions more accurately taking into consideration the remarkable structural complexity of NPs. Hence, innovative in silico strategies have contributed valuably to the NP research in drug discovery processes as reviewed herein. [Formula: see text].

Predictive computational toxicology to support drug safety assessment

Use of predictive technologies is an important aspect of many efforts in today's research, development, and regulatory landscapes. Computational methods as predictive tools for supporting drug safety assessments is of widespread interest as the field of in silico assessments rapidly changes with emerging technologies and the large amount of existing data available for modeling. There are challenges associated with application of in silico analyses for drug toxicity predictions and need for strategies and harmonization to enable an acceptable in silico evaluation for prediction of specific toxicity assay outcomes. This chapter will provide an overview focused on computational tools using structure-activity relationships and will highlight initiatives for use of computational assessments and realistic applications for predictive modeling in evaluating potential toxicities of drug-related molecules.

Review of current and "omics" methods for assessing the toxicity (genotoxicity, teratogenicity and nephrotoxicity) of herbal medicines and mushrooms

ETHNOPHARMACOLOGICAL RELEVANCE

The increasing use of traditional herbal medicines around the world requires more scientific evidence for their putative harmlessness. To this end, a plethora of methods exist, more or less satisfying. In this post-genome era, recent reviews are however scarce, not only on the use of new "omics" methods (transcriptomics, proteomics, metabonomics) for genotoxicity, teratogenicity, and nephrotoxicity assessment, but also on conventional ones.

METHODS

The present work aims (i) to review conventional methods used to assess genotoxicity, teratogenicity and nephrotoxicity of medicinal plants and mushrooms; (ii) to report recent progress in the use of "omics" technologies in this field; (iii) to underline advantages and limitations of promising methods; and lastly (iv) to suggest ways whereby the genotoxicity, teratogenicity, and nephrotoxicity assessment of traditional herbal medicines could be more predictive.

RESULTS

Literature and safety reports show that structural alerts, in silico and classical in vitro and in vivo predictive methods are often used. The current trend to develop "omics" technologies to assess genotoxicity, teratogenicity and nephrotoxicity is promising but most often relies on methods that are still not standardized and validated.

CONCLUSION

Hence, it is critical that toxicologists in industry, regulatory agencies and academic institutions develop a consensus, based on rigorous methods, about the reliability and interpretation of endpoints. It will also be important to regulate the integration of conventional methods for toxicity assessments with new "omics" technologies.

Assessment of herbal medicinal products: challenges, and opportunities to increase the knowledge base for safety assessment

Although herbal medicinal products (HMP) have been perceived by the public as relatively low risk, there has been more recognition of the potential risks associated with this type of product as the use of HMPs increases. Potential harm can occur via inherent toxicity of herbs, as well as from contamination, adulteration, plant misidentification, and interactions with other herbal products or pharmaceutical drugs. Regulatory safety assessment for HMPs relies on both the assessment of cases of adverse reactions and the review of published toxicity information. However, the conduct of such an integrated investigation has many challenges in terms of the quantity and quality of information. Adverse reactions are under-reported, product quality may be less than ideal, herbs have a complex composition and there is lack of information on the toxicity of medicinal herbs or their constituents. Nevertheless, opportunities exist to capitalise on newer information to increase the current body of scientific evidence. Novel sources of information are reviewed, such as the use of poison control data to augment adverse reaction information from national pharmacovigilance databases, and the use of more recent toxicological assessment techniques such as predictive toxicology and omics. The integration of all available information can reduce the uncertainty in decision making with respect to herbal medicinal products. The example of Aristolochia and aristolochic acids is used to highlight the challenges related to safety assessment, and the opportunities that exist to more accurately elucidate the toxicity of herbal medicines.

Metabolites in safety testing (MIST): considerations of mechanisms of toxicity with dose, abundance, and duration of treatment

In previous papers, we have offered a strategic framework regarding metabolites of drugs in humans and the need to assess these in laboratory animal species (also termed Metabolites in Safety Testing or MIST; Smith and Obach, Chem. Res. Toxicol. (2006) 19, 1570-1579). Three main tenets of this framework were founded in (i) comparisons of absolute exposures (as circulating concentrations or total body burden), (ii) the nature of the toxicity mechanism (i.e., reversible interaction at specific targets versus covalent binding to multiple macromolecules), and (iii) the biological matrix in which the metabolite was observed (circulatory vs excretory). In the present review, this framework is expanded to include a fourth tenet: considerations for the duration of exposure. Basic concepts of pharmacology are utilized to rationalize the relationship between exposure (to parent drug or metabolite) and various effects ranging from desired therapeutic effects through to severe toxicities. Practical considerations of human ADME (absorption-distribution-metabolism-excretion) data, to determine which metabolites should be further evaluated for safety, are discussed. An analysis of recently published human ADME studies shows that the number of drug metabolites considered to be important for MIST can be excessively high if a simple percentage-of-parent-drug criterion is used without consideration of the aforementioned four tenets. Concern over unique human metabolites has diminished over the years as experience has shown that metabolites of drugs in humans will almost always be observed in laboratory animals, although the proportions may vary. Even if a metabolite represents a high proportion of the dose in humans and a low proportion in animals, absolute abundances in animals frequently exceed that in humans because the doses used in animal toxicology studies are much greater than therapeutic doses in humans. The review also updates the enzymatic basis for the differences between species and how these relate to MIST considerations.