Computational systems pharmacology analysis of cannabidiol: a combination of chemogenomics-knowledgebase network analysis and integrated in silico modeling and simulation

Unraveling the Mechanisms of Cannabidiol's Pharmacological Actions: A Comprehensive Research Overview

Cannabis sativa has long been used for neurological and psychological healing. Recently, cannabidiol (CBD) extracted from cannabis sativa has gained prominence in the medical field due to its non-psychotropic therapeutic effects on the central and peripheral nervous systems. CBD, also acting as a potent antioxidant, displays diverse clinical properties such as anticancer, antiinflammatory, antidepressant, antioxidant, antiemetic, anxiolytic, antiepileptic, and antipsychotic effects. In this review, we summarized the structural activity relationship of CBD with different receptors by both experimental and computational techniques and investigated the mechanism of interaction between related receptors and CBD. The discovery of structural activity relationship between CBD and target receptors would provide a direction to optimize the scaffold of CBD and its derivatives, which would give potential medical applications on CBD-based therapies in various illnesses.

Altering biomolecular condensates as a potential mechanism that mediates cannabidiol effect on glioblastoma

Glioblastoma (GBM) is an extremely aggressive primary brain tumor with poor prognosis, short survival time post-diagnosis and high recurrence. Currently, no cure for GBM exists. The identification of an effective therapeutic modality for GBM remains a high priority amongst medical professionals and researches. In recent studies, inhalant cannabidiol (CBD) has demonstrated promise in effectively inhibiting GBM tumor growth. However, exactly how CBD treatment affects the physiology of these tumor cells remains unclear. Stress granules (SG) (a sub-class of biomolecular condensates (BMC)) are dynamic, membrane-less intracellular microstructures which contain proteins and nucleic acids. The formation and signaling of SGs and BMCs plays a significant role in regulating malignancies. This study investigates whether inhaled CBD may play an intervening role towards SGs in GBM tumor cells. Integrated bioinformatics approaches were preformed to gain further insights. This includes use of Immunohistochemistry and flow cytometry to measure SGs, as well as expression and phosphorylation of eukaryotic initiation factor-2α (eIF2α). The findings of this study reveal that CBD receptors (and co-regulated genes) have the potential to play an important biological role in the formation of BMCs within GBM. In this experiment, CBD treatment significantly increased the volume of TIAR-1. This increase directly correlated with elevation in both eIF2α expression and p-eIF2α in CBD treated tissues in comparison to the placebo group (p < 0.05). These results suggest that inhalant CBD significantly up-regulated SGs in GBM, and thus support a theory of targeting BMCs as a potential therapeutic substrate for treating GBM.

Uncovering the Oxidative Stress Mechanisms and Targets in Alzheimer's Disease by Integrating Phenotypic Screening Data and Polypharmacology Networks

Background

The oxidative stress hypothesis is challenging the dominant position of amyloid-β (Aβ) in the field of understanding the mechanisms of Alzheimer's disease (AD), a complicated and untreatable neurodegenerative disease.

Objective

The goal of the present study was to uncover the oxidative stress mechanisms causing AD, as well as the potential therapeutic targets and neuroprotective drugs against oxidative stress mechanisms.

Methods

In this study, a systematic workflow combining pharmacological experiments and computational prediction was proposed. 222 drugs and natural products were collected first and then tested on SH-SY5Y cells to obtain phenotypic screening data on neuroprotection. The preliminary screening data were integrated with drug-target interactions (DTIs) and multi-scale biomedical data, which were analyzed with statistical tests and gene set enrichment analysis. A polypharmacology network was further constructed for investigation.

Results

340 DTIs were matched in multiple databases, and 222 cell viability ratios were calculated for experimental compounds. We identified significant potential therapeutic targets based on oxidative stress mechanisms for AD, including NR3C1, SHBG, ESR1, PGR, and AVPR1A, which might be closely related to neuroprotective effects and pathogenesis. 50% of the top 14 enriched pathways were found to correlate with AD, such as arachidonic acid metabolism and neuroactive ligand-receptor interaction. Several approved drugs in this research were also found to exert neuroprotective effects against oxidative stress mechanisms, including beclometasone, methylprednisolone, and conivaptan.

Conclusion

Our results indicated that NR3C1, SHBG, ESR1, PGR, and AVPR1A were promising therapeutic targets and several drugs may be repurposed from the perspective of oxidative stress and AD.

The effect of cannabidiol on seizure features and quality of life in drug-resistant frontal lobe epilepsy patients: a triple-blind controlled trial

Background

Treatment-resistant epileptic seizures are associated with reduced quality of life (QoL). As polypharmacy with routine antiseizure medications has many side effects, novel add-on treatments are necessary. Recent research showed the efficacy of add-on therapy by cannabidiol (CBD) on refractory epilepsy. We attempted to extend data on the efficacy and safety profile of CBD in patients with frontal lobe treatment-resistant epilepsy.

Methods

A total of 27 patients were recruited into two CBD (n = 12) and placebo (n = 15) groups. The CBD group received a highly purified liposomal preparation of the drug in addition to routine antiseizure medications. The placebo group only received antiseizure medications. This experiment followed a triple-blinding protocol. Outcome measures were seizure frequency, the Chalfont seizure severity scale (CSSS), and the quality of life questionnaire score (QOLIE-31) assessed at baseline, 4 weeks, and 8 weeks.

Results

At 4 weeks, results indicated that a higher fraction of patients in the CBD group (66.67%) showed improvement in seizure, compared to the placebo group (20.00%). Before-after comparison revealed that CBD, unlike routine ADEs, was effective in reducing the occurrence of seizures at the study's final timepoint [mean difference 45.58, 95% CI (8.987 to 82.18), p = 0.009]. Seizure severity was not affected by study groups or time intervals (repeated-measures ANOVA p > 0.05). Post-hoc tests found that the QoLI-31 score was improved at 8 weeks compared to baseline [mean diff. -5.031, 95% CI (-9.729 to -0.3328), p = 0.032]. The difference in cases who experienced enhanced QoL was meaningful between the CBD and placebo groups at 8 weeks [RR: 2.160, 95% CI (1.148 to 4.741), p = 0.018] but not at 4 weeks (p = 0.653). A positive finding for QoL improvement was associated with a positive finding for seizure frequency reduction [r = 0.638, 95% CI (0.296 to 0.835), p = 0.001]. Interestingly, limiting the correlation analysis to cases receiving CBD indicated that QoL improvement was not linked with seizure parameters such as severity and frequency (p > 0.05).

Conclusion

The present study suggests the benefit of a purified and highly efficient preparation of CBD for seizure frequency reduction and improvement of QoL in refractory frontal lobe epilepsy. Further study with longer follow-ups and larger sample size is advised.

Clinical trial registration

https://www.irct.ir/trial/56790, identifier: IRCT20210608051515N1.

Gastrodin programs an Arg-1+ microglial phenotype in hippocampus to ameliorate depression- and anxiety-like behaviors via the Nrf2 pathway in mice

BACKGROUND

Regulating the microglial phenotype is an attractive strategy for treating diseases of the central nervous system such as depression and anxiety. Gastrodin can quickly cross the blood-brain barrier and mitigate microglia-mediated inflammation, which widely used to treat a variety of central nervous system diseases associated with microglial dysfunction. However, the molecular mechanism by which gastrodin regulates the functional phenotype of microglia remains unclear.

PURPOSE

Since the transcription factor "nuclear factor erythroid 2-related factor 2″ (Nrf2) is associated with the anti-inflammatory effects of gastrodin, we hypothesized that gastrodin induces Nrf2 expression in microglia and thereby programs an anti-inflammatory phenotype.

STUDY DESIGN

Male C57BL/6 mice, treated or not with gastrodin, were given lipopolysaccharide (LPS) at 0.25 mg/kg/d for 10 days to induce chronic neuroinflammation. The effects of gastrodin on microglial phenotypes, neuroinflammation and depression- and anxiety-like behaviors were evaluated. In another experiment, animals were treated with Nrf2 inhibitor ML385 throughout the 13-day gastrodin intervention period.

METHODS

The effects of gastrodin on depression- and anxiety-like behaviors were evaluated through the sucrose preference test, forced swimming test, open field test and elevated plus-maze test; as well as its effects on morphology and molecular and functional phenotypes of hippocampal microglia through immunohistochemistry, real-time PCR and enzyme-linked immunosorbent assays.

RESULTS

Chronic exposure to LPS caused hippocampal microglia to secrete inflammatory cytokines, their somata to enlarge, and their dendrites to lose branches. These changes were associated with depression- and anxiety-like behaviors. Gastrodin blocked these LPS-induced alterations and promoted an Arg-1+ microglial phenotype that protected neurons from injury. The effects of gastrodin were associated with Nrf2 activation, whereas blockade of Nrf2 antagonized gastrodin.

CONCLUSION

These results suggest that gastrodin acts via Nrf2 to promote an Arg-1+ microglial phenotype, which buffers the harmful effects of LPS-induced neuroinflammation. Gastrodin may be a promising drug against central nervous system diseases that involve microglial dysfunction.

Role of the endocannabinoid system in fragile X syndrome: potential mechanisms for benefit from cannabidiol treatment

Multiple lines of evidence suggest a central role for the endocannabinoid system (ECS) in the neuronal development and cognitive function and in the pathogenesis of fragile X syndrome (FXS). This review describes the ECS, its role in the central nervous system, how it is dysregulated in FXS, and the potential role of cannabidiol as a treatment for FXS. FXS is caused by deficiency or absence of the fragile X messenger ribonucleoprotein 1 (FMR1) protein, FMRP, typically due to the presence of >200 cytosine, guanine, guanine sequence repeats leading to methylation of the FMR1 gene promoter. The absence of FMRP, following FMR1 gene-silencing, disrupts ECS signaling, which has been implicated in FXS pathogenesis. The ECS facilitates synaptic homeostasis and plasticity through the cannabinoid receptor 1, CB₁, on presynaptic terminals, resulting in feedback inhibition of neuronal signaling. ECS-mediated feedback inhibition and synaptic plasticity are thought to be disrupted in FXS, leading to overstimulation, desensitization, and internalization of presynaptic CB₁ receptors. Cannabidiol may help restore synaptic homeostasis by acting as a negative allosteric modulator of CB₁, thereby attenuating the receptor overstimulation, desensitization, and internalization. Moreover, cannabidiol affects DNA methylation, serotonin 5HT_1A signal transduction, gamma-aminobutyric acid receptor signaling, and dopamine D₂ and D₃ receptor signaling, which may contribute to beneficial effects in patients with FXS. Consistent with these proposed mechanisms of action of cannabidiol in FXS, in the CONNECT-FX trial the transdermal cannabidiol gel, ZYN002, was associated with improvements in measures of social avoidance, irritability, and social interaction, particularly in patients who are most affected, showing ≥90% methylation of the FMR1 gene.

Cannabidiol prevents methamphetamine-induced neurotoxicity by modulating dopamine receptor D1-mediated calcium-dependent phosphorylation of methyl-CpG-binding protein 2

In the past decade, methamphetamine (METH) abuse has sharply increased in the United States, East Asia, and Southeast Asia. METH abuse not only leads to serious drug dependence, but also produces irreversible neurotoxicity. Currently, there are no approved pharmacotherapies for the treatment of METH use disorders. Cannabidiol (CBD), a major non-psychoactive (and non-addictive) cannabinoid from the cannabis plant, shows neuroprotective, antioxidative, and anti-inflammatory properties under METH exposure. At present, however, the mechanisms underlying these properties remain unclear, which continues to hinder research on its therapeutic potential. In the current study, computational simulations showed that CBD and METH may directly bind to the dopamine receptor D1 (DRD1) via two overlapping binding sites. Moreover, CBD may compete with METH for the PHE-313 binding site. We also found that METH robustly induced apoptosis with activation of the caspase-8/caspase-3 cascade in-vitro and in-vivo, while CBD pretreatment prevented these changes. Furthermore, METH increased the expression of DRD1, phosphorylation of Methyl-CpG-binding protein 2 (MeCP2) at serine 421 (Ser421), and level of intracellular Ca2+in-vitro and in-vivo, but these effects were blocked by CBD pretreatment. The DRD1 antagonist SCH23390 significantly prevented METH-induced apoptosis, MeCP2 phosphorylation, and Ca2+ overload in-vitro. In contrast, the DRD1 agonist SKF81297 markedly increased apoptosis, MeCP2 phosphorylation, and Ca2+ overload, which were blocked by CBD pretreatment in-vitro. These results indicate that CBD prevents METH-induced neurotoxicity by modulating DRD1-mediated phosphorylation of MeCP2 and Ca2+ signaling. This study suggests that CBD pretreatment may resist the effects of METH on DRD1 by competitive binding.

Practical Considerations for the Use of Cannabis in Cancer Pain Management—What a Medical Oncologist Should Know

Pain is a highly debilitating emotional and sensory experience that significantly affects quality of life (QoL). Numerous chronic conditions, including cancer, are associated with chronic pain. In the setting of malignancy, pain can be a consequence of the tumor itself or of life-saving interventions, including surgery, chemotherapy, and radiotherapy. Despite significant pharmacological advances and awareness campaigns, pain remains undertreated in one-third of patients. To date, opioids have been the mainstay of cancer pain management. The problematic side effects and unsatisfactory pain relief of opioids have revived patients’ and physicians’ interest in finding new solutions, including cannabis and cannabinoids. The medical use of cannabis has been prohibited for decades, and it remains in Schedule 1 of the Misuse of Drugs Regulations. Currently, the legal context for its usage has become more permissive. Various preclinical and observational studies have aimed to prove that cannabinoids could be effective in cancer pain management. However, their clinical utility must be further supported by high-quality clinical trials.

Cannabidiol inhibits methamphetamine-induced dopamine release via modulation of the DRD1-MeCP2-BDNF-TrkB signaling pathway

RATIONALE

Adaptive alteration of dopamine (DA) system in mesocorticolimbic circuits is an extremely intricate and dynamic process, which contributes to maintaining methamphetamine (METH)-related disorders. There are no approved pharmacotherapies for METH-related disorders. Cannabidiol (CBD), a major non-psychoactive constituent of cannabis, has received attention for its therapeutic potential in treating METH-related disorders. However, the major research obstacles of CBD are the yet to be clarified mechanisms behind its therapeutic potential. Recent evidence showed that DA system may be active target of CBD. CBD could be a promising dopaminergic medication for METH-related disorders.

OBJECTIVES

We investigated the role of the DA receptor D1 (DRD1)-methyl-CpG-binding protein 2 (MeCP2)-brain-derived neurotrophic factor (BDNF)-tyrosine receptor kinase B (TrkB) signaling pathway in DA release induced by METH. Investigating the intervention effects of CBD on the DRD1-MeCP2-BDNF-TrkB signaling pathway could help clarify the underlying mechanisms and therapeutic potential of CBD in METH-related disorders.

RESULTS

METH (400 μM) significantly increased DA release from primary neurons in vitro, which was blocked by CBD (1 μM) pretreatment. METH (400 μM) significantly increased the expression levels of DRD1, BDNF, and TrkB, but decreased the expression of MeCP2 in the neurons, whereas CBD (1 μM) pretreatment notably inhibited the protein changes induced by METH. In addition, DRD1 antagonist SCH23390 (10 μM) inhibited the DA release and protein change induced by METH in vitro. However, DRD1 agonist SKF81297 (10 μM) induced DA release and protein change in vitro, which was also blocked by CBD (1 μM) pretreatment. METH (2 mg/kg) significantly increased the DA level in the nucleus accumbens (NAc) of rats with activation of the DRD1-MeCP2-BDNF-TrkB signaling pathway, but these changes were blocked by CBD (40 or 80 mg/kg) pretreatment.

CONCLUSIONS

This study indicates that METH induces DA release via the DRD1-MeCP2-BDNF-TrkB signaling pathway. Furthermore, CBD significantly inhibits DA release induced by METH through modulation of this pathway.

Artificial Intelligent Deep Learning Molecular Generative Modeling of Scaffold-Focused and Cannabinoid CB2 Target-Specific Small-Molecule Sublibraries

Design and generation of high-quality target- and scaffold-specific small molecules is an important strategy for the discovery of unique and potent bioactive drug molecules. To achieve this goal, authors have developed the deep-learning molecule generation model (DeepMGM) and applied it for the de novo molecular generation of scaffold-focused small-molecule libraries. In this study, a recurrent neural network (RNN) using long short-term memory (LSTM) units was trained with drug-like molecules to result in a general model (g-DeepMGM). Sampling practices on indole and purine scaffolds illustrate the feasibility of creating scaffold-focused chemical libraries based on machine intelligence. Subsequently, a target-specific model (t-DeepMGM) for cannabinoid receptor 2 (CB2) was constructed following the transfer learning process of known CB2 ligands. Sampling outcomes can present similar properties to the reported active molecules. Finally, a discriminator was trained and attached to the DeepMGM to result in an in silico molecular design-test circle. Medicinal chemistry synthesis and biological validation was performed to further investigate the generation outcome, showing that XIE9137 was identified as a potential allosteric modulator of CB2. This study demonstrates how recent progress in deep learning intelligence can benefit drug discovery, especially in de novo molecular design and chemical library generation.

Shaoyao decoction attenuates DSS-induced ulcerative colitis, macrophage and NLRP3 inflammasome activation through the MKP1/NF-κB pathway

BACKGROUND

Shaoyao decoction (SYD), a traditional Chinese medicine prescription that originated in the Jin-Yuan Dynasty, has shown effects in treating ulcerative colitis. However, the underlying mechanism is unclear. We combined network pharmacology with molecular biology technology to detect the mechanism underlying the effect of SYD on ulcerative colitis. We combined network pharmacology with molecular biology technology to detected the further mechanism in SYD effect on ulcerative colitis.

PURPOSE

In this study, we investigated the mechanism by which SYD exerts a protective effect against ulcerative colitis in vivo and in vitro.

STUDY DESIGN AND METHODS

We focused on two aspects of the mechanism by which SYD relieves ulcerative colitis, regulation of the MAPK cascade and the NF-κB signaling pathway, through analysis of the "active ingredient-target-disease" network followed by GO enrichment and KEGG pathway analysis according to network pharmacology. Mice with ulcerative colitis underwent 5% dextran sulfate sodium (DSS), and the RAW 264.7 cell model was used to identify important targets.

RESULTS

We found that after 5% DSS treatment, the inflammation indexes and the expression of NLRP3-related proteins were increased concomitant with the loss of mucins and occludin. Treatment with SYD (2.25 g/kg, BW) significantly improved the expression of mucins and occludin after DSS at the protein and transcriptional levels. Furthermore, SYD treatment significantly reduced NF-κB P65 and P38 expression, thus exerting a great antinecrotic effect, as revealed by TUNEL staining and Western blotting. The beneficial effects of SYD were almost canceled by NSC 95397 (an inhibitor of mitogen-activated protein kinase phosphatase-1 (MKP1)) after DSS treatment in vivo or LPS treatment in vitro. In addition, treatment with SYD reduced caspase-1 activity and rescued the release of ASC and GSDMD, thus inhibiting the assembly of NLRP3 and maintaining the integrity of the intestinal barrier. We also conducted in vitro experiments in the LPS-induced RAW 264.7 cell model and found that cells incubated with 1 mg/ml SYD for 24 h possessed the highest cell viability. Next, we incubated 1 mg/ml SYD for 24 h after treatment with 1 µg/ml LPS for 6 h. We showed that 1 mg/ml SYD displayed anti-inflammatory and anti-necrotic effects through the NLRP3, NF-κB P65 and P38 pathways, and the effects of SYD were also inhibited by 10 nM NSC 95397.

CONCLUSION

These results demonstrate that SYD has protective effects against ulcerative colitis and alleviates pyroptosis by inhibiting the MKP1/NF-κB/NLRP3 pathway.

Phytocannabinoids and schizophrenia: Focus on adolescence as a critical window of enhanced vulnerability and opportunity for treatment

The recent shift in socio-political debates and growing liberalization of Cannabis use across the globe has raised concern regarding its impact on vulnerable populations such as adolescents. Concurrent with declining perception of Cannabis harms, more adolescents are using it daily in several countries and consuming marijuana strains with high content of psychotropic delta (9)-tetrahydrocannabinol (THC). These dual, related trends seem to facilitate the development of compromised social and cognitive performance at adulthood, which are described in preclinical and human studies. Cannabis exerts its effects via altering signalling within the endocannabinoid system (ECS), which modulates the stress circuitry during the neurodevelopment. In this context early interventions appear to circumvent the emergence of adult neurodevelopmental deficits. Accordingly, Cannabis sativa second-most abundant compound, cannabidiol (CBD), emerges as a potential therapeutic agent to treat neuropsychiatric disorders. We first focus on human and preclinical studies on the long-term effects induced by adolescent THC exposure as a "critical window" of enhanced neurophysiological vulnerability, which could be involved in the pathophysiology of schizophrenia and related primary psychotic disorders. Then, we focus on adolescence as a "window of opportunity" for early pharmacological treatment, as novel risk reduction strategy for neurodevelopmental disorders. Thus, we review current preclinical and clinical evidence regarding the efficacy of CBD in terms of positive, negative and cognitive symptoms treatment, safety profile, and molecular targets.

A Network Pharmacology Approach to Identify Potential Molecular Targets for Cannabidiol's Anti-Inflammatory Activity

Introduction: Published preclinical and clinical studies support the anti-inflammatory activity of CBD, but the molecular targets (e.g., genes and proteins) that are involved in its mechanisms of action remain unclear. Herein, a network-based pharmacology analysis was performed to aid in the identification of potential molecular targets for CBD's anti-inflammatory activity. Materials and Methods: Target genes and proteins were obtained from several online databases, including Swiss target prediction, Online Mendelian Inheritance in Man, and the DrugBank database. A compound-target-disease network was constructed with Cytoscape tool, and a network of protein-protein interactions was established with the Search Tool for the Retrieval of Interacting Genes/Proteins database. Lead proteins identified from the compound-target-disease network were further studied for their interactions with CBD by computational docking. In addition, biological pathways involved in CBD's anti-inflammatory activity were identified with the Gene Ontology enrichment and the Kyoto Encyclopedia of Genes and Genomes analysis. Results: A panel of proteins, including cellular tumor antigen p53, NF-kappa-B essential modulator, tumor necrosis factor (TNF) receptor, transcription factor p65, NF-kappa-B p105, NF-kappa-B inhibitor alpha, inhibitor of nuclear factor kappa-B kinase subunit alpha, and epidermal growth factor receptor, were identified as lead targets involved in CBD's anti-inflammatory activity. This finding was further supported by molecular docking, which showed interactions between the lead proteins and CBD. In addition, several signaling pathways, including TNF, toll-like receptor, mitogen-activated protein kinases, nuclear factor kappa-light-chain-enhancer of activated B cells, and nucleotide-binding oligomerization domain-like receptors, were identified as key regulators in the mediation of CBD's anti-inflammatory activity. Conclusion: A network-based pharmacology analysis identified potential molecular targets and signaling pathways for CBD's anti-inflammatory activity. Findings from this study add to the growing body of data supporting the utilization of CBD as a promising anti-inflammatory natural product.

The Underlying Molecular Mechanisms Involved in Traditional Chinese Medicine Smilax china L. for the Treatment of Pelvic Inflammatory Disease

Smilax china L. (SCL) is extensively used in the treatment of pelvic inflammatory disease (PID). This study aimed to clarify the potential active ingredients of SCL and mechanisms on PID. SCL was widely distributed in Japan, South Korea, and China, which was traditionally considered heat-clearing, detoxicating, and dampness-eliminating medicine. Systems pharmacology revealed that 32 compounds in SCL may interact with 19 targets for immunoenhancement, antiapoptosis, anti-inflammation, and antioxidant activity of the PID model. Molecular docking revealed that isorhamnetin, moracin M, rutin, and oxyresveratrol may have higher binding potential with prostaglandin-endoperoxide synthase 2 (PTGS2), mitogen-activated protein kinase 1 (MAPK1), siderocalin (LCN2), tumor necrosis factor (TNF), and matrix metalloprotein-9 (MMP9), respectively. Molecular dynamics simulation showed that the binding modes of moracin M-MAPK1, rutin-TNF, and oxyresveratrol-MMP9 complexes were more stable, evidenced by relatively smaller fluctuations in root mean square deviation values. Conclusively, SCL may treat PID by inhibiting inflammatory factors, antitissue fibrosis, and microbial growth.

Could Cannabidiol Be a Treatment for Coronavirus Disease-19-Related Anxiety Disorders?

Coronavirus disease-19 (COVID-19)-related anxiety and post-traumatic stress symptoms (PTSS) or post-traumatic stress disorder (PTSD) are likely to be a significant long-term issue emerging from the current pandemic. We hypothesize that cannabidiol (CBD), a chemical isolated from Cannabis sativa with reported anxiolytic properties, could be a therapeutic option for the treatment of COVID-19-related anxiety disorders. In the global over-the-counter CBD market, anxiety, stress, depression, and sleep disorders are consistently the top reasons people use CBD. In small randomized controlled clinical trials, CBD (300-800 mg) reduces anxiety in healthy volunteers, patients with social anxiety disorder, those at clinical high risk of psychosis, in patients with Parkinson's disease, and in individuals with heroin use disorder. Observational studies and case reports support these findings, extending to patients with anxiety and sleep disorders, Crohn's disease, depression, and in PTSD. Larger ongoing trials in this area continue to add to this evidence base with relevant patient cohorts, sample sizes, and clinical end-points. Pre-clinical studies reveal the molecular targets of CBD in these indications as the cannabinoid receptor type 1 and cannabinoid receptor type 2 (mainly in fear memory processing), serotonin 1A receptor (mainly in anxiolysis) and peroxisome proliferator-activated receptor gamma (mainly in the underpinning anti-inflammatory/antioxidant effects). Observational and pre-clinical data also support CBD's therapeutic value in improving sleep (increased sleep duration/quality and reduction in nightmares) and depression, which are often comorbid with anxiety. Together these features of CBD make it an attractive novel therapeutic option in COVID-related PTSS that merits investigation and testing through appropriately designed randomized controlled trials.

Critical Review on the Chemical Aspects of Cannabidiol (CBD) and Harmonization of Computational Bioactivity Data

Cannabidiol (CBD) is a non-psychotropic phytocannabinoid which represents one of the constituents of the "phytocomplex" of Cannabis sativa. This natural compound is attracting growing interest since when CBD-based remedies and commercial products were marketed. This review aims to exhaustively address the extractive and analytical approaches that have been developed for the isolation and quantification of CBD. Recent updates on cutting-edge technologies were critically examined in terms of yield, sensitivity, flexibility and performances in general, and are reviewed alongside original representative results. As an add-on to currently available contributions in the literature, the evolution of the novel, efficient synthetic approaches for the preparation of CBD, a procedure which is appealing for the pharmaceutical industry, is also discussed. Moreover, with the increasing interest on the therapeutic potential of CBD and the limited understanding of the undergoing biochemical pathways, the reader will be updated about recent in silico studies on the molecular interactions of CBD towards several different targets attempting to fill this gap. Computational data retrieved from the literature have been integrated with novel in silico experiments, critically discussed to provide a comprehensive and updated overview on the undebatable potential of CBD and its therapeutic profile.

Is Cannabidiol During Neurodevelopment a Promising Therapy for Schizophrenia and Autism Spectrum Disorders?

Schizophrenia and autism spectrum disorders (ASD) are psychiatric neurodevelopmental disorders that cause high levels of functional disabilities. Also, the currently available therapies for these disorders are limited. Therefore, the search for treatments that could be beneficial for the altered course of the neurodevelopment associated with these disorders is paramount. Preclinical and clinical evidence points to cannabidiol (CBD) as a promising strategy. In this review, we discuss clinical and preclinical studies on schizophrenia and ASD investigating the behavioral, molecular, and functional effects of chronic treatment with CBD (and with cannabidivarin for ASD) during neurodevelopment. In summary, the results point to CBD's beneficial potential for the progression of these disorders supporting further investigations to strengthen its use.

Generative chemistry: drug discovery with deep learning generative models

The de novo design of molecular structures using deep learning generative models introduces an encouraging solution to drug discovery in the face of the continuously increased cost of new drug development. From the generation of original texts, images, and videos, to the scratching of novel molecular structures the creativity of deep learning generative models exhibits the height machine intelligence can achieve. The purpose of this paper is to review the latest advances in generative chemistry which relies on generative modeling to expedite the drug discovery process. This review starts with a brief history of artificial intelligence in drug discovery to outline this emerging paradigm. Commonly used chemical databases, molecular representations, and tools in cheminformatics and machine learning are covered as the infrastructure for generative chemistry. The detailed discussions on utilizing cutting-edge generative architectures, including recurrent neural network, variational autoencoder, adversarial autoencoder, and generative adversarial network for compound generation are focused. Challenges and future perspectives follow.

Cannabidiol for Pain Treatment: Focus on Pharmacology and Mechanism of Action

Cannabis has a long history of medical use. Although there are many cannabinoids present in cannabis, Δ9tetrahydrocannabinol (Δ9-THC) and cannabidiol (CBD) are the two components found in the highest concentrations. CBD itself does not produce typical behavioral cannabimimetic effects and was thought not to be responsible for psychotropic effects of cannabis. Numerous anecdotal findings testify to the therapeutic effects of CBD, which in some cases were further supported by research findings. However, data regarding CBD’s mechanism of action and therapeutic potential are abundant and omnifarious. Therefore, we review the basic research regarding molecular mechanism of CBD’s action with particular focus on its analgesic potential. Moreover, this article describes the detailed analgesic and anti-inflammatory effects of CBD in various models, including neuropathic pain, inflammatory pain, osteoarthritis and others. The dose and route of the administration-dependent effect of CBD, on the reduction in pain, hyperalgesia or allodynia, as well as the production of pro and anti-inflammatory cytokines, were described depending on the disease model. The clinical applications of CBD-containing drugs are also mentioned. The data presented herein unravel what is known about CBD’s pharmacodynamics and analgesic effects to provide the reader with current state-of-art knowledge regarding CBD’s action and future perspectives for research.

Covalent allosteric modulation: An emerging strategy for GPCRs drug discovery

Designing covalent allosteric modulators brings new opportunities to the field of drug discovery towards G-protein-coupled receptors (GPCRs). Targeting an allosteric binding pocket can allow a modulator to have protein subtype selectivity and low drug resistance. Utilizing covalent warheads further enables the modulator to increase the binding potency and extend the duration of action. This review starts with GPCR allosteric modulation to discuss the structural biology of allosteric binding pockets, the different types of allosteric modulators, as well as the advantages of employing allosteric modulation. This is followed by a discussion on covalent modulators to clarify how covalent ligands can benefit the receptor modulation and to illustrate moieties that can commonly be used as covalent warheads. Finally, case studies are presented on designing class A, B, and C GPCR covalent allosteric modulators to demonstrate successful stories on combining allosteric modulation and covalent binding. Limitations and future perspectives are also covered.

Effects of α-Mangostin Derivatives on the Alzheimer's Disease Model of Rats and Their Mechanism: A Combination of Experimental Study and Computational Systems Pharmacology Analysis

α-Mangostin (α-M) is a natural xanthone from the pericarp of fruit Garcinia mangostana and possesses versatile biological activities. α-M has a therapeutic potential to treat Alzheimer's disease (AD) because of its anti-inflammatory, antioxidative, and neuroprotective activities. However, the use of α-M for AD treatment is limited due to its cytotoxic activities and relatively low potency. Modifications of its chemical structure were needed to reduce its cytotoxicity and improve its therapeutic potential against AD. For this purpose, 16 α-M carbamate derivatives were synthesized. An animal model of AD was established, and the effects of AMG-1 on the spatial learning ability and memory ability were evaluated using behavioral tests. The effect on neuropathology was tested by histopathological evaluation, Nissl staining, and silver staining. Computational systems pharmacology analysis using the chemogenomics knowledgebase was applied for network studies. Compound-target, target-pathway, and target-disease networks were constructed, integrating both in silico analysis and reported experimental data. The results show that AMG-1 can demonstrate its therapeutic effects in a one-molecule, multiple-targets manner to remarkably ameliorate neurological changes and reverse behavioral deficits in AD model rats. The improved cognitive function and alleviated neuronal injury can be observed. The ability of AMG-1 to scavenge β-amyloid in the hippocampus was validated in AD model rats.

Altered dopamine D3 receptor gene expression in MAM model of schizophrenia is reversed by peripubertal cannabidiol treatment

Gestational methylazoxymethanol acetate (MAM) treatment produces offspring with adult phenotype relevant to schizophrenia, including positive- and negative-like symptoms, cognitive deficits, dopaminergic dysfunction, structural and functional abnormalities. Here we show that adult rats prenatally treated with MAM at gestational day 17 display significant increase in dopamine D3 receptor (D3) mRNA expression in prefrontal cortex (PFC), hippocampus and nucleus accumbens, accompanied by increased expression of dopamine D2 receptor (D2) mRNA exclusively in the PFC. Furthermore, a significant change in the blood perfusion at the level of the circle of Willis and hippocampus, paralleled by the enlargement of lateral ventricles, was also detected by magnetic resonance imaging (MRI) techniques. Peripubertal treatment with the non-euphoric phytocannabinoid cannabidiol (30 mg/kg) from postnatal day (PND) 19 to PND 39 was able to reverse in MAM exposed rats: i) the up-regulation of the dopamine D3 receptor mRNA (only partially prevented by haloperidol 0.6 mg/kg/day); and ii) the regional blood flow changes in MAM exposed rats. Molecular modelling predicted that cannabidiol could bind preferentially to dopamine D3 receptor, where it may act as a partial agonist according to conformation of ionic-lock, which is highly conserved in GPCRs. In summary, our results demonstrate that the mRNA expression of both dopamine D2 and D3 receptors is altered in the MAM model; however only the transcript levels of D3 are affected by cannabidiol treatment, likely suggesting that this gene might not only contribute to the schizophrenia symptoms but also represent an unexplored target for the antipsychotic activity of cannabidiol.

Molecular dynamics simulations on RORγt: insights into its functional agonism and inverse agonism

The retinoic acid receptor-related orphan receptor (ROR) γt receptor is a member of nuclear receptors, which is indispensable for the expression of pro-inflammatory cytokine IL-17. RORγt has been established as a drug target to design and discover novel treatments for multiple inflammatory and immunological diseases. It is important to elucidate the molecular mechanisms of how RORγt is activated by an agonist, and how the transcription function of RORγt is interrupted by an inverse agonist. In this study we performed molecular dynamics simulations on four different RORγt systems, i.e., the apo protein, protein bound with agonist, protein bound with inverse agonist in the orthosteric-binding pocket, and protein bound with inverse agonist in the allosteric-binding pocket. We found that the orthosteric-binding pocket in the apo-form RORγt was mostly open, confirming that apo-form RORγt was constitutively active and could be readily activated (ca. tens of nanoseconds scale). The tracked data from MD simulations supported that RORγt could be activated by an agonist binding at the orthosteric-binding pocket, because the bound agonist helped to enhance the triplet His479-Tyr502-Phe506 interactions and stabilized H12 structure. The stabilized H12 helped RORγt to form the protein-binding site, and therefore made the receptor ready to recruit a coactivator molecule. We also showed that transcription function of RORγt could be interrupted by the binding of inverse agonist at the orthosteric-binding pocket or at the allosteric-binding site. After the inverse agonist was bound, H12 either structurally collapsed, or reorientated to a different position, at which the presumed protein-binding site was not able to be formed.

Deep Convolutional Generative Adversarial Network (dcGAN) Models for Screening and Design of Small Molecules Targeting Cannabinoid Receptors

A deep convolutional generative adversarial network (dcGAN) model was developed in this study to screen and design target-specific novel compounds for cannabinoid receptors. In the adversarial process of training, two models, the discriminator D and the generator G, are iteratively trained. D is trained to discover the hidden patterns among the input data to have the accurate discrimination of the authentic compounds and the "fake" compounds generated by G; G is trained to generate "fake" compounds to fool the well-trained D by optimizing the weights for matrix multiplication of data sampling. In order to determine the appropriate architecture and the input data structure for the involved convolutional neural networks (CNNs), the combinations of various network architectures and molecular fingerprints were explored. Well-developed CNN models including LeNet-5, AlexNet, ZFNet, and VGGNet were investigated. Four types of fingerprints, including MACCS, ECFP6, AtomPair, and AtomPair Count, were calculated to describe the small molecules with diverse structural characteristics. The limitation of generating fingerprints as output remains that the concrete molecular structures cannot be converted directly, while the generative models with convolutional networks provide promising opportunities to the screening of molecules and rational modifications afterward. This study demonstrated how computer-aided drug discovery could benefit from the recent advances in deep learning.

Insights about multi-targeting and synergistic neuromodulators in Ayurvedic herbs against epilepsy: integrated computational studies on drug-target and protein-protein interaction networks

Epilepsy, that comprises a wide spectrum of neuronal disorders and accounts for about one percent of global disease burden affecting people of all age groups, is recognised as apasmara in the traditional medicinal system of Indian antiquity commonly known as Ayurveda. Towards exploring the molecular level complex regulatory mechanisms of 63 anti-epileptic Ayurvedic herbs and thoroughly examining the multi-targeting and synergistic potential of 349 drug-like phytochemicals (DPCs) found therein, in this study, we develop an integrated computational framework comprising of network pharmacology and molecular docking studies. Neuromodulatory prospects of anti-epileptic herbs are probed and, as a special case study, DPCs that can regulate metabotropic glutamate receptors (mGluRs) are inspected. A novel methodology to screen and systematically analyse the DPCs having similar neuromodulatory potential vis-à-vis DrugBank compounds (NeuMoDs) is developed and 11 NeuMoDs are reported. A repertoire of 74 DPCs having poly-pharmacological similarity with anti-epileptic DrugBank compounds and those under clinical trials is also reported. Further, high-confidence PPI-network specific to epileptic protein-targets is developed and the potential of DPCs to regulate its functional modules is investigated. We believe that the presented schema can open-up exhaustive explorations of indigenous herbs towards meticulous identification of clinically relevant DPCs against various diseases and disorders.

Prediction of Orthosteric and Allosteric Regulations on Cannabinoid Receptors Using Supervised Machine Learning Classifiers

Designing highly selective compounds to protein subtypes and developing allosteric modulators targeting them are critical considerations to both drug discovery and mechanism studies for cannabinoid receptors. It is challenging but in demand to have classifiers to identify active ligands from inactive or random compounds and distinguish allosteric modulators from orthosteric ligands. In this study, supervised machine learning classifiers were built for two subtypes of cannabinoid receptors, CB1 and CB2. Three types of features, including molecular descriptors, MACCS fingerprints, and ECFP6 fingerprints, were calculated to evaluate the compound sets from diverse aspects. Deep neural networks, as well as conventional machine learning algorithms including support vector machine, naïve Bayes, logistic regression, and ensemble learning, were applied. Their performances on the classification with different types of features were compared and discussed. According to the receiver operating characteristic curves and the calculated metrics, the advantages and drawbacks of each algorithm were investigated. The feature ranking was followed to help extract useful knowledge about critical molecular properties, substructural keys, and circular fingerprints. The extracted features will then facilitate the research on cannabinoid receptors by providing guidance on preferred properties for compound modification and novel scaffold design. Besides using conventional molecular docking studies for compound virtual screening, machine-learning-based decision-making models provide alternative options. This study can be of value to the application of machine learning in the area of drug discovery and compound development.

Significantly different effects of tetrahydroberberrubine enantiomers on dopamine D1/D2 receptors revealed by experimental study and integrated in silico simulation

Tetrahydroberberrubine (TU), an active tetrahydroprotoberberines (THPBs), is gaining increasing popularity as a potential candidate for treatment of anxiety and depression. One of its two enantiomers, l-TU, has been reported to be an antagonist of both D1 and D2 receptors, but the functional activity of the other enantiomer, d-TU, is still unknown. In this study, experiments were combined with in silico molecular simulations to (1) confirm and discover the functional activities of l-TU and d-TU, and (2) systematically evaluate the molecular mechanisms beyond the experimental observations. l-TU proved to be an antagonist of both D1 and D2 receptors (IC50 = 385 nM and 985 nM, respectively), while d-TU shows no affinity against either D1 or D2 receptor, based on the cAMP assay (D1 receptor) and calcium flux assay (D2 receptor). Results from both flexible-ligand docking studies and molecular dynamic (MD) simulations provided insights at the atomic level. The l-TU-bound structures predicted by MD (1) undergo an outward rotation of the extracellular helical bundles; (2) have an enlarged orthosteric binding pocket; and (3) have a central toggle switch that is prevented from rotating freely. These features are unique to the l-TU enantiomer and provide an explanation for its antagonistic behavior toward both D1 and D2 receptors. The present study provides new sight on the structural and functional relationships of l-TU and d-TU binding to dopamine receptors, and provides guidance to the rational design of novel molecules targeting these two dopamine receptors in the future.

Harnessing Human Microphysiology Systems as Key Experimental Models for Quantitative Systems Pharmacology

Two technologies that have emerged in the last decade offer a new paradigm for modern pharmacology, as well as drug discovery and development. Quantitative systems pharmacology (QSP) is a complementary approach to traditional, target-centric pharmacology and drug discovery and is based on an iterative application of computational and systems biology methods with multiscale experimental methods, both of which include models of ADME-Tox and disease. QSP has emerged as a new approach due to the low efficiency of success in developing therapeutics based on the existing target-centric paradigm. Likewise, human microphysiology systems (MPS) are experimental models complementary to existing animal models and are based on the use of human primary cells, adult stem cells, and/or induced pluripotent stem cells (iPSCs) to mimic human tissues and organ functions/structures involved in disease and ADME-Tox. Human MPS experimental models have been developed to address the relatively low concordance of human disease and ADME-Tox with engineered, experimental animal models of disease. The integration of the QSP paradigm with the use of human MPS has the potential to enhance the process of drug discovery and development.