Cannabinoid Receptor Subtype 2 (CB2R) in a Multitarget Approach: Perspective of an Innovative Strategy in Cancer and Neurodegeneration

DeLA-DrugSelf: Empowering multi-objective de novo design through SELFIES molecular representation

In this paper, we introduce DeLA-DrugSelf, an upgraded version of DeLA-Drug [J. Chem. Inf. Model. 62 (2022) 1411-1424], which incorporates essential advancements for automated multi-objective de novo design. Unlike its predecessor, which relies on SMILES notation for molecular representation, DeLA-DrugSelf employs a novel and robust molecular representation string named SELFIES (SELF-referencing Embedded String). The generation process in DeLA-DrugSelf not only involves substitutions to the initial string representing the starting query molecule but also incorporates insertions and deletions. This enhancement makes DeLA-DrugSelf significantly more adept at executing data-driven scaffold decoration and lead optimization strategies. Remarkably, DeLA-DrugSelf explicitly addresses the SELFIES-related collapse issue, considering only collapse-free compounds during generation. These compounds undergo a rigorous quality metrics evaluation, highlighting substantial advancements in terms of drug-likeness, uniqueness, and novelty compared to the molecules generated by the previous version of the algorithm. To evaluate the potential of DeLA-DrugSelf as a mutational operator within a genetic algorithm framework for multi-objective optimization, we employed a fitness function based on Pareto dominance. Our objectives focused on target-oriented properties aimed at optimizing known cannabinoid receptor 2 (CB2R) ligands. The results obtained indicate that DeLA-DrugSelf, available as a user-friendly web platform (https://www.ba.ic.cnr.it/softwareic/delaself/), can effectively contribute to the data-driven optimization of starting bioactive molecules based on user-defined parameters.

Synthesis of novel indol-3-acetamido analogues as potent anticancer agents, biological evaluation and molecular modeling studies

Cannabinoids bind to cannabinoid receptors CB1 and CB2 and their antitumoral activity has been reported against some various cancer cell lines. Some synthetic cannabinoids possessing indole rings such as JWH-015 and JWH-133 particularly bind to the cannabinoid CB2 receptor and it was reported that they inhibit the proliferation and growth of various cancer cells without their psychoactive effects. However, the pharmacological action mechanisms of the cannabinoids are completely unknown. In this study, we report the synthesis of some new cannabinoidic novel indoles and evaluate their anticancer activity on various cancerous and normal cell lines (U87, RPMI 8226, HL60 and L929) using several cellular and molecular assays including MTT assay, real-time q-PCR, scratch assay, DAPI assay, Annexin V-PE/7AAD staining, caspase3/7 activity tests. Our findings indicated that compounds 7, 10, 13, 16, and 17 could reduce cell viability effectively. Compound 17 markedly increased proapoptotic genes (BAX, BAD, and BIM), tumor suppressor gene (p53) expression levels as well as the BAX/BCL-2 ratio in U87 cells. In addition, 17 inhibited cell migration. Based on these results, 17 was chosen for determining the mechanism of cell death in U87 cells. DAPI and Annexin V-7AAD staining results showed that 17 induced apoptosis, moreover activated caspase 3/7 significantly. Hence, compound 17, was selected as a lead compound for further pharmacomodulation. To rationalize the observed biological activities of 17, our study also included a comprehensive analysis using molecular docking and MD simulations. This integrative approach revealed that 17 fits tightly into the active site of the CB2 receptor and is involved in key interactions that may be responsible for its anti-proliferative effects.

Discovery of first novel sigma/HDACi dual-ligands with a potent in vitro antiproliferative activity

Designing and discovering compounds for dual-target inhibitors is challenging to synthesize new, safer, and more efficient drugs than single-target drugs, especially to treat multifactorial diseases such as cancer. The simultaneous regulation of multiple targets might represent an alternative synthetic approach to optimize patient compliance and tolerance, minimizing the risk of target-based drug resistance due to the modulation of a few targets. To this end, we conceived for the first time the design and synthesis of dual-ligands σR/HDACi to evaluate possible employment as innovative candidates to address this complex disease. Among all synthesized compounds screened for several tumoral cell lines, compound 6 (Kiσ1R = 38 ± 3.7; Kiσ2R = 2917 ± 769 and HDACs IC50 = 0.59 µM) is the most promising candidate as an antiproliferative agent with an IC50 of 0.9 µM on the HCT116 cell line and no significant toxicity to normal cells. Studies of molecular docking, which confirmed the affinity over σ1R and a pan-HDACs inhibitory behavior, support a possible balanced affinity and activity between both targets.

ALPACA: A machine Learning Platform for Affinity and selectivity profiling of CAnnabinoids receptors modulators

The development of small molecules that selectively target the cannabinoid receptor subtype 2 (CB2R) is emerging as an intriguing therapeutic strategy to treat neurodegeneration, as well as to contrast the onset and progression of cancer. In this context, in-silico tools able to predict CB2R affinity and selectivity with respect to the subtype 1 (CB1R), whose modulation is responsible for undesired psychotropic effects, are highly desirable. In this work, we developed a series of machine learning classifiers trained on high-quality bioactivity data of small molecules acting on CB2R and/or CB1R extracted from ChEMBL v30. Our classifiers showed strong predictive power in accurately determining CB2R affinity, CB1R affinity, and CB2R/CB1R selectivity. Among the built models, those obtained using random forest as algorithm proved to be the top-performing ones (AUC in validation ≥0.96) and were made freely accessible through a user-friendly web platform developed ad hoc and called ALPACA (https://www.ba.ic.cnr.it/softwareic/alpaca/). Due to its user-friendly interface and robust predictive power, ALPACA can be a valuable tool in saving both time and resources involved in the design of selective CB2R modulators.

Dual-Acting Small Molecules: Subtype-Selective Cannabinoid Receptor 2 Agonist/Butyrylcholinesterase Inhibitor Hybrids Show Neuroprotection in an Alzheimer's Disease Mouse Model

We present the synthesis and characterization of merged human butyrylcholinesterase (hBChE) inhibitor/cannabinoid receptor 2 (hCB₂R) ligands for the treatment of neurodegeneration. In total, 15 benzimidazole carbamates were synthesized and tested for their inhibition of human cholinesterases, also with regard to their pseudoirreversible binding mode and affinity toward both cannabinoid receptors in radioligand binding studies. After evaluation in a calcium mobilization assay as well as a β-arrestin 2 (βarr2) recruitment assay, two compounds with balanced activities on both targets were tested for their immunomodulatory effect on microglia activation and regarding their pharmacokinetic properties and blood-brain barrier penetration. Compound 15d, containing a dimethyl carbamate motif, was further evaluated in vivo, showing prevention of Aβ_25-35-induced learning impairments in a pharmacological mouse model of Alzheimer's disease for both short- and long-term memory responses. Additional combination studies proved a synergic effect of BChE inhibition and CB₂R activation in vivo.

Development of the High-Affinity Carborane-Based Cannabinoid Receptor Type 2 PET Ligand [18F]LUZ5-d8

The development of cannabinoid receptor type 2 (CB2R) radioligands for positron emission tomography (PET) imaging was intensively explored. To overcome the low metabolic stability and simultaneously increase the binding affinity of known CB2R radioligands, a carborane moiety was used as a bioisostere. Here we report the synthesis and characterization of carborane-based 1,8-naphthyridinones and thiazoles as novel CB2R ligands. All tested compounds showed low nanomolar CB2R affinity, with (Z)-N-[3-(4-fluorobutyl)-4,5-dimethylthiazole-2(3H)-ylidene]-(1,7-dicarba-closo-dodecaboranyl)-carboxamide (LUZ5) exhibiting the highest affinity (0.8 nM). Compound [18F]LUZ5-d8 was obtained with an automated radiosynthesizer in high radiochemical yield and purity. In vivo evaluation revealed the improved metabolic stability of [18F]LUZ5-d8 compared to that of [18F]JHU94620. PET experiments in rats revealed high uptake in spleen and low uptake in brain. Thus, the introduction of a carborane moiety is an appropriate tool for modifying literature-known CB2R ligands and gaining access to a new class of high-affinity CB2R ligands, while the in vivo pharmacology still needs to be addressed.

N-adamantyl-anthranil amide derivatives: New selective ligands for the cannabinoid receptor subtype 2 (CB2R)

Cannabinoid type 2 receptor (CB2R) is a G-protein-coupled receptor that, together with Cannabinoid type 1 receptor (CB1R), endogenous cannabinoids and enzymes responsible for their synthesis and degradation, forms the EndoCannabinoid System (ECS). In the last decade, several studies have shown that CB2R is overexpressed in activated central nervous system (CNS) microglia cells, in disorders based on an inflammatory state, such as neurodegenerative diseases, neuropathic pain, and cancer. For this reason, the anti-inflammatory and immune-modulatory potentials of CB2R ligands are emerging as a novel therapeutic approach. The design of selective ligands is however hampered by the high sequence homology of transmembrane domains of CB1R and CB2R. Based on a recent three-arm pharmacophore hypothesis and latest CB2R crystal structures, we designed, synthesized, and evaluated a series of new N-adamantyl-anthranil amide derivatives as CB2R selective ligands. Interestingly, this new class of compounds displayed a high affinity for human CB2R along with an excellent selectivity respect to CB1R. In this respect, compounds exhibiting the best pharmacodynamic profile in terms of CB2R affinity were also evaluated for the functional behavior and molecular docking simulations provided a sound rationale by highlighting the relevance of the arm 1 substitution to prompt CB2R action. Moreover, the modulation of the pro- and anti-inflammatory cytokines production was also investigated to exert the ability of the best compounds to modulate the inflammatory cascade.

CB2R activation ameliorates late adolescent chronic alcohol exposure-induced anxiety-like behaviors during withdrawal by preventing morphological changes and suppressing NLRP3 inflammasome activation in prefrontal cortex microglia in mice

BACKGROUND

Chronic alcohol exposure (CAE) during late adolescence increases the risk of anxiety development. Alcohol-induced prefrontal cortex (PFC) microglial activation, characterized by morphological changes and increased associations with neurons, plays a critical role in the pathogenesis of anxiety. Alcohol exposure increases NLRP3 inflammasome expression, increasing cytokine secretion by activated microglia. Cannabinoid type 2 receptor (CB2R), an essential receptor of the endocannabinoid system, regulates microglial activation and neuroinflammatory reactions. We aimed to investigate the role of CB2R activation in ameliorating late adolescent CAE-induced anxiety-like behaviors and microglial activation in C57BL/6J mice.

METHODS

Six-week-old C57BL/6J mice were acclimated for 7 days and then were administered alcohol by gavage (4 g/kg, 25 % w/v) for 28 days. The mice were intraperitoneally injected with the specific CB2R agonist AM1241 1 h before alcohol treatment. Anxiety-like behaviors during withdrawal were assessed by open field test and elevated plus maze test 24 h after the last alcohol administration. Microglial activation, microglia-neuron interactions, and CB2R and NLRP3 inflammasome-related molecule expression in the PFC were measured using immunofluorescence, immunohistochemical, qPCR, and Western blotting assays. Microglial morphology was evaluated by Sholl analysis and the cell body-to-total cell size index. Additionally, N9 microglia were activated by LPS in vitro, and the effects of AM1241 on NLRP3 and N9 microglial activation were investigated.

RESULTS

After CAE, mice exhibited severe anxiety-like behaviors during withdrawal. CAE induced obvious microglia-neuron associations, and increased expression of microglial activation markers, CB2R, and NLRP3 inflammasome-related molecules in the PFC. Microglia also showed marked filament retraction and reduction and cell body enlargement after CAE. AM1241 treatment ameliorated anxiety-like behaviors in CAE model mice, and it prevented microglial morphological changes, reduced microglial activation marker expression, and suppressed the microglial NLRP3 inflammasome activation and proinflammatory cytokine secretion induced by CAE. AM1241 suppressed the LPS-induced increase in NLRP3 inflammasome-related molecules, IL-1β release, and M1 phenotype markers (iNOS and CD86) in N9 cell, which was reversed by CB2R antagonist treatment.

CONCLUSIONS

CAE caused anxiety-like behaviors in late adolescent mice at least partly by inducing microglial activation and increasing microglia-neuron associations in the PFC. CB2R activation ameliorated these effects by preventing morphological changes and suppressing NLRP3 inflammasome activation in PFC microglia.

Endocannabinoid Degradation Enzyme Inhibitors as Potential Antipsychotics: A Medicinal Chemistry Perspective

The endocannabinoid system (ECS) plays a very important role in numerous physiological and pharmacological processes, such as those related to the central nervous system (CNS), including learning, memory, emotional processing, as well pain control, inflammatory and immune response, and as a biomarker in certain psychiatric disorders. Unfortunately, the half-life of the natural ligands responsible for these effects is very short. This perspective describes the potential role of the inhibitors of the enzymes fatty acid amide hydrolase (FAAH) and monoacylglycerol lipase (MGL), which are mainly responsible for the degradation of endogenous ligands in psychic disorders and related pathologies. The examination was carried out considering both the impact that the classical exogenous ligands such as Δ⁹-tetrahydrocannabinol (THC) and (-)-trans-cannabidiol (CBD) have on the ECS and through an analysis focused on the possibility of predicting the potential toxicity of the inhibitors before they are subjected to clinical studies. In particular, cardiotoxicity (hERG liability), probably the worst early adverse reaction studied during clinical studies focused on acute toxicity, was predicted, and some of the most used and robust metrics available were considered to select which of the analyzed compounds could be repositioned as possible oral antipsychotics.

Development of N-(1-Adamantyl)benzamides as Novel Anti-Inflammatory Multitarget Agents Acting as Dual Modulators of the Cannabinoid CB2 Receptor and Fatty Acid Amide Hydrolase

Cannabinoid type 2 receptor (CB2R), belonging to the endocannabinoid system, is overexpressed in pathologies characterized by inflammation, and its activation counteracts inflammatory states. Fatty acid amide hydrolase (FAAH) is an enzyme responsible for the degradation of the main endocannabinoid anandamide; thus, the simultaneous CB2R activation and FAAH inhibition may be a synergistic anti-inflammatory strategy. Encouraged by principal component analysis (PCA) data identifying a wide chemical space shared by CB2R and FAAH ligands, we designed a small library of adamantyl-benzamides, as potential dual agents, CB2R agonists, and FAAH inhibitors. The new compounds were tested for their CB2R affinity/selectivity and CB2R and FAAH activity. Derivatives 13, 26, and 27, displaying the best pharmacodynamic profile as CB2R full agonists and FAAH inhibitors, decreased pro-inflammatory and increased anti-inflammatory cytokines production. Molecular docking simulations complemented the experimental findings by providing a molecular rationale behind the observed activities. These multitarget ligands constitute promising anti-inflammatory agents.

Reliable prediction of cannabinoid receptor 2 ligand by machine learning based on combined fingerprints

Cannabinoid receptors, as part of the family of the G protein-coupled receptors (GPCRs), are involved in various physiological functions. Its subtype cannabinoid receptor subtype 2 (CB2), mainly distributed in the periphery, is a crucial therapeutic target for anti-epileptic, anti-inflammation, anti-fibrosis, and bone metabolism regulation, and it regulates these physiological functions without psychiatric side effects. Recently machine learning methods for predicting biophysics properties have attracted much attention. Successful application of machine learning usually highly depends on the appropriate representation of the compounds. In this study, we comprehensively evaluate the performance of the descriptor-based models (including XGBoost, Random Forest, and KNN) and two graph-based models (D-MPNN, MolMap) for the prediction of the CB2 regulators, and found that XGBoost offers outstanding performance for both regression tasks and classification tasks. 13 different molecular fingerprints and 12 descriptors, as well as their combination were further screened; AvalonFP + AtomPairFP + RDkitFP + MorganFP and AtomPairFP + MorganFP + AvalonFP were the optimum combinations for regression task (R² increase to 0.667) and classification task (AUC-ROC increase to 0.933), respectively. Specifically, the best XGBoost regression model with optimum features achieves better performance than Mizera's QSAR model on the same dataset developed by Mizera (R² 0.664 versus 0.62). It also achieves optimal performance with an AUC-ROC of 0.917 on the external validation set. By comparison, MolMap and D-MPNN only provide 0.912 and 0.898. The Shapley additive explanation method was used to interpret the models, and features importance were shown for both regression and classification task. The XGBoost model equipped with essential molecular fingerprints combination in this paper may provide valuable clues to designing novel CB2 ligands and developing models for other properties prediction.

The Role of Cannabinoid Type 2 Receptors in Parkinson's Disease

Parkinson's disease (PD) is the second most frequent neurodegenerative disease and currently represents a clear unmet medical need. Therefore, novel preventive and therapeutic strategies are needed. Cannabinoid type 2 (CB2) receptors, one of the components of the endocannabinoid system, can regulate neuroinflammation in PD. Here, we review the current preclinical and clinical studies investigating the CB2 receptors in PD with the aim to clarify if these receptors could have a role in PD. Preclinical data show that CB2 receptors could have a neuroprotective action in PD and that the therapeutic targeting of CB2 receptors could be promising. Indeed, it has been shown that different CB2 receptor-selective agonists exert protective effects in different PD models. Moreover, the alterations in the expression of CB2 receptors observed in brain tissues from PD animal models and PD patients suggest the potential value of CB2 receptors as possible novel biomarkers for PD. However, to date, there is no direct evidence of the role of CB2 receptors in PD. Further studies are strongly needed in order to fully clarify the role of CB2 receptors in PD and thus pave the way to novel possible diagnostic and therapeutic opportunities for PD.

Butyrylcholinesterase inhibitors as potential anti-Alzheimer's agents: an updated patent review (2018-present)

INTRODUCTION

Alzheimer's disease (AD) constitutes one of the most complex and devastating diseases, with an extraordinarily high increase expected for the next few years. Despite the numerous efforts accomplished so far there is still no cure but just palliative treatments.

AREAS COVERED

The main topic covered herein has been the development of butyrylcholinesterase (BuChE) inhibitors with the aim of increasing the levels of the neurotransmitter acetylcholine (ACh). Two main groups of compounds have been considered: multitarget and non-multitarget ligands, depending if the structural design is focused or not on other key targets and pathogenic factors of the disease. Seventeen patents regarding multitarget-directed ligands (MTDLs), twelve for not multitarget derivatives, and three for miscellaneous uses have been covered in the period 2018‒2021.

EXPERT OPINION

BuChE is an attractive target in the treatment of AD for many reasons. It is the most prevalent cholinesterase within more advanced stages of the disease, so drugs inhibiting it would be suitable for the treatment of mid- to severe Alzheimer's patients. Moreover, BuChE has been proved to be connected with some other key hallmarks of the disease, like amyloidogenesis; hybridization of a BuChE-targeting pharmacophore with other scaffolds designed for other therapeutic targets is quite a promising design for potential anti-Alzheimer's drugs.

DeLA-Drug: A Deep Learning Algorithm for Automated Design of Druglike Analogues

In this paper, we present a deep learning algorithm for automated design of druglike analogues (DeLA-Drug), a recurrent neural network (RNN) model composed of two long short-term memory (LSTM) layers and conceived for data-driven generation of similar-to-bioactive compounds. DeLA-Drug captures the syntax of SMILES strings of more than 1 million compounds belonging to the ChEMBL28 database and, by employing a new strategy called sampling with substitutions (SWS), generates molecules starting from a single user-defined query compound. Remarkably, the algorithm preserves druglikeness and synthetic accessibility of the known bioactive compounds present in the ChEMBL28 repository. The absence of any time-demanding fine-tuning procedure enables DeLA-Drug to perform a fast generation of focused libraries for further high-throughput screening and makes it a suitable tool for performing de novo design even in low-data regimes. To provide a concrete idea of its applicability, DeLA-Drug was applied to the cannabinoid receptor subtype 2 (CB2R), a known target involved in different pathological conditions such as cancer and neurodegeneration. DeLA-Drug, available as a free web platform (http://www.ba.ic.cnr.it/softwareic/deladrugportal/), can help medicinal chemists interested in generating analogues of compounds already available in their laboratories and, for this reason, good candidates for an easy and low-cost synthesis.

Candidate Therapeutics by Screening for Multitargeting Ligands: Combining the CB2 Receptor With CB1, PPARγ and 5-HT4 Receptors

In recent years, the cannabinoid type 2 receptor (CB2R) has become a major target for treating many disease conditions. The old therapeutic paradigm of “one disease-one target-one drug” is being transformed to “complex disease-many targets-one drug.” Multitargeting, therefore, attracts much attention as a promising approach. We thus focus on designing single multitargeting agents (MTAs), which have many advantages over combined therapies. Using our ligand-based approach, the “Iterative Stochastic Elimination” (ISE) algorithm, we produce activity models of agonists and antagonists for desired therapeutic targets and anti-targets. These models are used for sequential virtual screening and scoring large libraries of molecules in order to pick top-scored candidates for testing in vitro and in vivo. In this study, we built activity models for CB2R and other targets for combinations that could be used for several indications. Those additional targets are the cannabinoid 1 receptor (CB1R), peroxisome proliferator-activated receptor gamma (PPARγ), and 5-Hydroxytryptamine receptor 4 (5-HT4R). All these models have high statistical parameters and are reliable. Many more CB2R/CBIR agonists were found than combined CB2R agonists with CB1R antagonist activity (by 200 fold). CB2R agonism combined with PPARγ or 5-HT4R agonist activity may be used for treating Inflammatory Bowel Disease (IBD). Combining CB2R agonism with 5-HT4R generates more candidates (14,008) than combining CB2R agonism with agonists for the nuclear receptor PPARγ (374 candidates) from an initial set of ∼2.1 million molecules. Improved enrichment of true vs. false positives may be achieved by requiring a better ISE score cutoff or by performing docking. Those candidates can be purchased and tested experimentally to validate their activity. Further, we performed docking to CB2R structures and found lower statistical performance of the docking (“structure-based”) compared to ISE modeling (“ligand-based”). Therefore, ISE modeling may be a better starting point for molecular discovery than docking.

Targeting Endocannabinoid System in Epilepsy: For Good or for Bad

Epilepsy is a neurological disorder with a high prevalence worldwide. Several studies carried out during the last decades indicate that the administration of cannabinoids as well as the activation of the endocannabinoid system (ECS) represent a therapeutic strategy to control epilepsy. However, there are controversial studies indicating that activation of ECS results in cell damage, inflammation and neurotoxicity, conditions that facilitate the seizure activity. The present review is focused to present findings supporting this issue. According to the current discrepancies, it is relevant to elucidate the different effects induced by the activation of ECS and determine the conditions under which it facilitates the seizure activity.

Screening of potential antidiabetic phytochemicals from Gongronema latifolium leaf against therapeutic targets of type 2 diabetes mellitus: multi-targets drug design

Diabetes mellitus (DM) is the most predominant group of metabolic disorders wreaking havoc on the wellbeing of man, with type 2 diabetes mellitus (type 2 DM) accounting for most DM related cases. This study, hence, investigated the antidiabetic potential of Gongronema latifolium leaf fractionated compounds against proteins implicated in different molecular pathways related to the onset and progression of type 2 DM. A total of fifteen proteins that can act as type 2 DM therapeutic targets were identified from the literature and downloaded/modelled using respective repositories. After docking the compounds with the fifteen proteins, glycogen synthase kinase 3 beta (GSK 3β), glucagon-like peptide-1 receptor (GLP-1R) and human aldose reductase were chosen as the ideal targets due to their high binding affinities with the compounds. Subsequent in silico analysis like binding free energy, ADMET predictions using different servers, and machine-learning predictive models (QSAR) using kernel partial least square regression were employed to identify promising compounds against the three targets. The eleven identified compounds (Luteonin, Kampferol, Robinetin, Gallocatechin, Baicalin, Apigenin, Genistein, Rosmaric acid, Chicoric acid and Naringenin) formed stable complexes with the proteins, showed moderation for toxicity, drugability, GI absorptions and drug-drug interactions, though structure modifications may be needed for lead optimization. The predictive QSAR models with reliable correlation coefficient (R2) showed the potency of the compounds to act as inhibitors (pIC50) of aldose reductase and GSK 3β, and act as agonists (pEC50) of GLP-1R. Thus, this study experimental framework can be used to design compounds that can modulate proteins related to type 2 DM without inducing off-target effects.

The CB2 cannabinoid receptor as a therapeutic target in the central nervous system

INTRODUCTION

Targeting CB2 cannabinoid receptor (CB2r) represents a promising approach for the treatment of central nervous system disorders. These receptors were identified in peripheral tissues, but also in neurons in the central nervous system. New findings have highlighted the interest to target these central receptors to obtain therapeutic effects devoid of the classical cannabinoid side-effects.

AREAS COVERED

In this review, we searched PubMed (January 1991-May 2021), ClinicalTrials.gov and Cochrane Library databases for articles, reviews and clinical trials. We first introduce the relevance of CB2r as a key component of the endocannabinoid system. We discuss CB2r interest as a possible novel target in the treatment of pain. This receptor has raised interest as a potential target for neurodegenerative disorders treatment, as we then discussed. Finally, we underline studies revealing a novel potential CB2r interest in mental disorders treatment.

EXPERT OPINION

In spite of the interest of targeting CB2r for pain, clinical trials evaluating CB2r agonist analgesic efficacy have currently failed. The preferential involvement of CB2r in preventing the development of chronic pain could influence the failure of clinical trials designed for the treatment of already established pain syndromes. Specific trials should be designed to target the prevention of chronic pain development.

Integrated network analysis identifying potential novel drug candidates and targets for Parkinson's disease

This study aimed to identify potential novel drug candidates and targets for Parkinson's disease. First, 970 genes that have been reported to be related to PD were collected from five databases, and functional enrichment analysis of these genes was conducted to investigate their potential mechanisms. Then, we collected drugs and related targets from DrugBank, narrowed the list by proximity scores and Inverted Gene Set Enrichment analysis of drug targets, and identified potential drug candidates for PD treatment. Finally, we compared the expression distribution of the candidate drug-target genes between the PD group and the control group in the public dataset with the largest sample size (GSE99039) in Gene Expression Omnibus. Ten drugs with an FDR < 0.1 and their corresponding targets were identified. Some target genes of the ten drugs significantly overlapped with PD-related genes or already known therapeutic targets for PD. Nine differentially expressed drug-target genes with p < 0.05 were screened. This work will facilitate further research into the possible efficacy of new drugs for PD and will provide valuable clues for drug design.

Multi-Target Directed Ligands (MTDLs) Binding the σ1 Receptor as Promising Therapeutics: State of the Art and Perspectives

The sigma-1 (σ1) receptor is a 'pluripotent chaperone' protein mainly expressed at the mitochondria-endoplasmic reticulum membrane interfaces where it interacts with several client proteins. This feature renders the σ1 receptor an ideal target for the development of multifunctional ligands, whose benefits are now recognized because several pathologies are multifactorial. Indeed, the current therapeutic regimens are based on the administration of different classes of drugs in order to counteract the diverse unbalanced physiological pathways associated with the pathology. Thus, the multi-targeted directed ligand (MTDL) approach, with one molecule that exerts poly-pharmacological actions, may be a winning strategy that overcomes the pharmacokinetic issues linked to the administration of diverse drugs. This review aims to point out the progress in the development of MTDLs directed toward σ1 receptors for the treatment of central nervous system (CNS) and cancer diseases, with a focus on the perspectives that are proper for this strategy. The evidence that some drugs in clinical use unintentionally bind the σ1 protein (as off-target) provides a proof of concept of the potential of this strategy, and it strongly supports the promise that the σ1 receptor holds as a target to be hit in the context of MTDLs for the therapy of multifactorial pathologies.

Recent Advances in the Development of Sigma Receptor Ligands as Cytotoxic Agents: A Medicinal Chemistry Perspective

Since their discovery as distinct receptor proteins, the specific physiopathological role of sigma receptors (σRs) has been deeply investigated. It has been reported that these proteins, classified into two subtypes indicated as σ₁ and σ₂, might play a pivotal role in cancer growth, cell proliferation, and tumor aggressiveness. As a result, the development of selective σR ligands with potential antitumor properties attracted significant attention as an emerging theme in cancer research. This perspective deals with the recent advances of σR ligands as novel cytotoxic agents, covering articles published between 2010 and 2020. An up-to-date description of the medicinal chemistry of selective σ₁R and σ₂R ligands with antiproliferative and cytotoxic activities has been provided, including major pharmacophore models and comprehensive structure–activity relationships for each main class of σR ligands.