Identification of Psychoactive Metabolites from Cannabis sativa, Its Smoke, and Other Phytocannabinoids Using Machine Learning and Multivariate Methods

An emerging trend in Novel Psychoactive Substances (NPSs): designer THC

Since its discovery as one of the main components of cannabis and its affinity towards the cannabinoid receptor CB1, serving as a means to exert its psychoactivity, Δ9-tetrahydrocannabinol (Δ9-THC) has inspired medicinal chemists throughout history to create more potent derivatives. Initially, the goal was to synthesize chemical probes for investigating the molecular mechanisms behind the pharmacology of Δ9-THC and finding potential medical applications. The unintended consequence of this noble intent has been the proliferation of these compounds for recreational use. This review comprehensively covers the most exhaustive number of THC-like cannabinoids circulating on the recreational market. It provides information on the chemistry, synthesis, pharmacology, analytical assessment, and experiences related to the psychoactive effects reported by recreational users on online forums. Some of these compounds can be found in natural cannabis, albeit in trace amounts, while others are entirely artificial. Moreover, to circumvent legal issues, many manufacturers resort to semi-synthetic processes starting from legal products extracted from hemp, such as cannabidiol (CBD). Despite the aim to encompass all known THC-like molecules, new species emerge on the drug users' pipeline each month. Beyond posing a significantly high public health risk due to unpredictable and unknown side effects, scientific research consistently lags behind the rapidly evolving recreational market.

Cannabis: a multifaceted plant with endless potentials

Cannabis sativa, also known as "hemp" or "weed," is a versatile plant with various uses in medicine, agriculture, food, and cosmetics. This review attempts to evaluate the available literature on the ecology, chemical composition, phytochemistry, pharmacology, traditional uses, industrial uses, and toxicology of Cannabis sativa. So far, 566 chemical compounds have been isolated from Cannabis, including 125 cannabinoids and 198 non-cannabinoids. The psychoactive and physiologically active part of the plant is a cannabinoid, mostly found in the flowers, but also present in smaller amounts in the leaves, stems, and seeds. Of all phytochemicals, terpenes form the largest composition in the plant. Pharmacological evidence reveals that the plants contain cannabinoids which exhibit potential as antioxidants, antibacterial agents, anticancer agents, and anti-inflammatory agents. Furthermore, the compounds in the plants have reported applications in the food and cosmetic industries. Significantly, Cannabis cultivation has a minimal negative impact on the environment in terms of cultivation. Most of the studies focused on the chemical make-up, phytochemistry, and pharmacological effects, but not much is known about the toxic effects. Overall, the Cannabis plant has enormous potential for biological and industrial uses, as well as traditional and other medicinal uses. However, further research is necessary to fully understand and explore the uses and beneficial properties of Cannabis sativa.

The Cannabis sativa genetics and therapeutics relationship network: automatically associating cannabis-related genes to therapeutic properties through chemicals from cannabis literature

BACKGROUND

Understanding the genome of Cannabis sativa holds significant scientific value due to the multi-faceted therapeutic nature of the plant. Links from cannabis gene to therapeutic property are important to establish gene targets for the optimization of specific therapeutic properties through selective breeding of cannabis strains. Our work establishes a resource for quickly obtaining a complete set of therapeutic properties and genes associated with any known cannabis chemical constituent, as well as relevant literature.

METHODS

State-of-the-art natural language processing (NLP) was used to automatically extract information from many cannabis-related publications, thus producing an undirected multipartite weighted-edge paragraph co-occurrence relationship network composed of two relationship types, gene-chemical and chemical property. We also developed an interactive application to visualize sub-graphs of manageable size.

RESULTS

Two hundred thirty-four cannabis constituent chemicals, 352 therapeutic properties, and 124 genes from the Cannabis sativa genome form a multipartite network graph which transforms 29,817 cannabis-related research documents from PubMed Central into an easy to visualize and explore network format.

CONCLUSION

Use of our network replaces time-consuming and labor intensive manual extraction of information from the large amount of available cannabis literature. This streamlined information retrieval process will enhance the activities of cannabis breeders, cannabis researchers, organic biochemists, pharmaceutical researchers and scientists in many other disciplines.

Computer Science Technology in Natural Products Research: A Review of Its Applications and Implications

Computational approaches to drug development are rapidly growing in popularity and have been used to produce significant results. Recent developments in information science have expanded databases and chemical informatics knowledge relating to natural products. Natural products have long been well-studied, and a large number of unique structures and remarkable active substances have been reported. Analyzing accumulated natural product knowledge using emerging computational science techniques is expected to yield more new discoveries. In this article, we discuss the current state of natural product research using machine learning. The basic concepts and frameworks of machine learning are summarized. Natural product research that utilizes machine learning is described in terms of the exploration of active compounds, automatic compound design, and application to spectral data. In addition, efforts to develop drugs for intractable diseases will be addressed. Lastly, we discuss key considerations for applying machine learning in this field. This paper aims to promote progress in natural product research by presenting the current state of computational science and chemoinformatics approaches in terms of its applications, strengths, limitations, and implications for the field.

Cannabinoids Drugs and Oral Health-From Recreational Side-Effects to Medicinal Purposes: A Systematic Review

Background: marijuana, the common name for cannabis sativa preparations, is one of the most consumed drug all over the world, both at therapeutical and recreational levels. With the legalization of medical uses of cannabis in many countries, and even its recreational use in most of these, the prevalence of marijuana use has markedly risen over the last decade. At the same time, there is also a higher prevalence in the health concerns related to cannabis use and abuse. Thus, it is mandatory for oral healthcare operators to know and deal with the consequences and effects of cannabis use on oral cavity health. This review will briefly summarize the components of cannabis and the endocannabinoid system, as well as the cellular and molecular mechanisms of biological cannabis action in human cells and biologic activities on tissues. We will also look into oropharyngeal tissue expression of cannabinoid receptors, together with a putative association of cannabis to several oral diseases. Therefore, this review will elaborate the basic biology and physiology of cannabinoids in human oral tissues with the aim of providing a better comprehension of the effects of its use and abuse on oral health, in order to include cannabinoid usage into dental patient health records as well as good medicinal practice. Methods: the paper selection was performed by PubMed/Medline and EMBASE electronic databases, and reported according to the PRISMA guidelines. The scientific products were included for qualitative analysis. Results: the paper search screened a total of 276 papers. After the initial screening and the eligibility assessment, a total of 32 articles were considered for the qualitative analysis. Conclusions: today, cannabis consumption has been correlated to a higher risk of gingival and periodontal disease, oral infection and cancer of the oral cavity, while the physico-chemical activity has not been completely clarified. Further investigations are necessary to evaluate a therapeutic efficacy of this class of drugs for the promising treatment of several different diseases of the salivary glands and oral diseases.