Insight of Captagon Abuse by Chemogenomics Knowledgebase-guided Systems Pharmacology Target Mapping Analyses

Chemical composition of Ecstasy tablets seized in Poland between 2005 and 2020

PURPOSE

The most commonly associated substance found in Ecstasy tablets is MDMA (3,4-methylenedioxymethamphetamine). In our study, we showed how the composition of psychoactive ingredients in Ecstasy tablets seized on the drug market in Poland has changed in the years 2005-2020.

METHODS

The study material consisted of nearly 20,000 single Ecstasy tablets seized by representatives of law enforcement (the police, prosecutors) from 2005 to 2020 and analysed by the Institute of Forensic Research, Krakow, Poland. The analysis of the tablets was carried out by gas chromatography-mass spectrometry (GC-MS), high-performance liquid chromatography with diode array detection (HPLC-DAD) and ultra-high-performance liquid chromatography with photodiode array detection (UHPLC-PDA).

RESULTS

Currently, new types of MDMA tablets are introduced onto the market, available in various colours and shapes. Our study showed that tablets sold on the street as Ecstasy have variable purity and sometimes contain little or no MDMA. The mean content of MDMA in one tablet seized in 2005-2011 decreased from 90 to 50 mg. In 2013, Ecstasy tablets with a very high MDMA content (average 195 mg per tablet) appeared on the market, but in the next 2 years, the MDMA content decreased again. From 2016, the average MDMA content began to rise again, ranging from 60 to 280 mg.

CONCLUSION

Tablets sold as Ecstasy also contained completely different psychoactive substances, including new psychoactive substances (NPS) (found in almost 20% of all examined tablets sold as Ecstasy) belonging to different chemical groups or their dangerous combinations (i.e. phenylethylamines, piperazines, tryptamines, cathinones, arylalkylamines, arylcyclohexylamines and piperidines). Such a large variety of psychoactive substances in Ecstasy tablets is associated with a high risk for users unaware of their composition.

Nonmedical Use of Stimulants Among Students in Jordan: A Nationwide Study

OBJECTIVES

Nonmedical use (NMU) of stimulants is an increasingly common phenomenon worldwide. Motivated by enhancing academic performance, peer pressure, and seeking pleasure, students in the Middle East are thought to be a high-risk population. This is especially important in times when the political instability in the region facilitates the production and trafficking of such substances. This study aimed to unveil the burden of NMU of stimulants and examine associated correlates among senior high school and university students in Jordan.

METHODS

We describe a cross-sectional study of senior high school and university students in Jordan assessing NMU of stimulants. Data were collected between January and April of 2022 through a survey, which was distributed online leading to a google forms page. The survey queried sociodemographic characteristics, history of NMU of stimulants, use of other illicit substances, attitudes toward NMU of stimulants, as well as a mental health assessment.

RESULTS

A total of 8739 students completed the survey (mean age of 20.40 ± 2.45 years), of which 5.1% reported a lifetime NMU of stimulants. Fenethylline (Captagon) was the most widely reported stimulant (2.6%). Living in the southern region, being diagnosed with a personality disorder, and using concomitant illicit substances were associated with the NMU of stimulants.

CONCLUSIONS

The NMU of CNS stimulants, especially fenethylline, is prevalent in Jordan. More surveillance ought to be heeded toward the southern borders of Jordan. Students who use stimulants for academic reasons must be made aware of the potential consequences of the NMU of stimulants.

Captagon-induced Brugada phenocopy: A report of two cases

Brugada phenocopies (BrP) represent electrocardiogram changes identical to those of true congenital Brugada syndrome but are induced by reversible clinical conditions. Previous cases have been reported in patients following recreational drug use. This report presents two cases of type 1B BrP associated with Fenethylline abuse, a recreational drug known by its trade name, Captagon.

Tramadol, captagon and khat use in the Eastern Mediterranean Region: opening Pandora's box

As defined by the World Health Organization, the Eastern Mediterranean Region (EMR), given its special geopolitical situation and internal/external conflicts, faces an increase in illegal activities such as drug production and trafficking, highlighting the need for a comprehensive understanding of the substance use situation. On the basis of a review of published papers between 2015 and 2021 we briefly review substance use in the EMR with special focus on the emerging drugs pertinent to this region, namely tramadol, captagon and khat.

The Psychonauts' Benzodiazepines; Quantitative Structure-Activity Relationship (QSAR) Analysis and Docking Prediction of Their Biological Activity

Designer benzodiazepines (DBZDs) represent a serious health concern and are increasingly reported in polydrug consumption-related fatalities. When new DBZDs are identified, very limited information is available on their pharmacodynamics. Here, computational models (i.e., quantitative structure-activity relationship/QSAR and Molecular Docking) were used to analyse DBZDs identified online by an automated web crawler (NPSfinder^®) and to predict their possible activity/affinity on the gamma-aminobutyric acid A receptors (GABA-ARs). The computational software MOE was used to calculate 2D QSAR models, perform docking studies on crystallised GABA-A receptors (6HUO, 6HUP) and generate pharmacophore queries from the docking conformational results. 101 DBZDs were identified online by NPSfinder^®. The validated QSAR model predicted high biological activity values for 41% of these DBDZs. These predictions were supported by the docking studies (good binding affinity) and the pharmacophore modelling confirmed the importance of the presence and location of hydrophobic and polar functions identified by QSAR. This study confirms once again the importance of web-based analysis in the assessment of drug scenarios (DBZDs), and how computational models could be used to acquire fast and reliable information on biological activity for index novel DBZDs, as preliminary data for further investigations.

MCCS, a novel characterization method for protein-ligand complex

Delineating the fingerprint or feature vector of a receptor/protein will facilitate the structural and biological studies, as well as the rational design and development of drugs with high affinities and selectivity. However, protein is complicated by its different functional regions that can bind to some of its protein partner(s), substrate(s), orthosteric ligand(s) or allosteric modulator(s) where cogent methods like molecular fingerprints do not work well. We here elaborate a scoring-function-based computing protocol Molecular Complex Characterizing System to help characterize the binding feature of protein-ligand complexes. Based on the reported receptor-ligand interactions, we first quantitate the energy contribution of each individual residue which may be an alternative of MD-based energy decomposition. We then construct a vector for the energy contribution to represent the pattern of the ligand recognition at a receptor and qualitatively analyze the matching level with other receptors. Finally, the energy contribution vector is explored for extensive use in similarity and clustering. The present work provides a new approach to cluster proteins, a perspective counterpart for determining the protein characteristics in the binding, and an advanced screening technique where molecular docking is applicable.

Binding Characterization of Agonists and Antagonists by MCCS: A Case Study from Adenosine A2A Receptor

Characterizing the structural basis of ligand recognition of adenosine A_2A receptor (AA_2AR) will facilitate its rational design and development of small molecules with high affinity and selectivity, as well as optimal therapeutic effects for pain, cancers, drug abuse disorders, etc. In the present work, we applied our reported algorithm, molecular complex characterizing system (MCCS), to characterize the binding features of AA_2AR based on its reported 3D structures of protein-ligand complexes. First, we compared the binding score to the reported experimental binding affinities of each compound. Then, we calculated an output example of residue energy contribution using MCCS and compared the results with data obtained from MM/GBSA. The consistency in results indicated that MCCS is a powerful, fast, and accurate method. Sequentially, using a receptor-ligand data set of 57 crystallized structures of AA_2ARs, we characterized the binding features of the binding pockets in AA_2AR, summarized the key residues that distinguish antagonist from agonist, produced heatmaps of residue energy contribution for clustering various statuses of AA_2ARs, explored the selectivity between AA_2AR and AA_1AR, etc. All the information provided new insights into the protein features of AA_2AR and will facilitate its rational drug design.

IsAb: a computational protocol for antibody design

The design of therapeutic antibodies has attracted a large amount of attention over the years. Antibodies are widely used to treat many diseases due to their high efficiency and low risk of adverse events. However, the experimental methods of antibody design are time-consuming and expensive. Although computational antibody design techniques have had significant advances in the past years, there are still some challenges that need to be solved, such as the flexibility of antigen structure, the lack of antibody structural data and the absence of standard antibody design protocol. In the present work, we elaborated on an in silico antibody design protocol for users to easily perform computer-aided antibody design. First, the Rosetta web server will be applied to generate the 3D structure of query antibodies if there is no structural information available. Then, two-step docking will be used to identify the binding pose of an antibody-antigen complex when the binding information is unknown. ClusPro is the first method to be used to conduct the global docking, and SnugDock is applied for the local docking. Sequentially, based on the predicted binding poses, in silico alanine scanning will be used to predict the potential hotspots (or key residues). Finally, computational affinity maturation protocol will be used to modify the structure of antibodies to theoretically increase their affinity and stability, which will be further validated by the bioassays in the future. As a proof of concept, we redesigned antibody D44.1 and compared it with previously reported data in order to validate IsAb protocol. To further illustrate our proposed protocol, we used cemiplimab antibody, a PD-1 checkpoint inhibitor, as an example to showcase a step-by-step tutorial.

Binding Characterization of GPCRs-Modulator by Molecular Complex Characterizing System (MCCS)

Increasing attention has been devoted to allosteric modulators as the preferred therapeutic agents for their colossal advantages such as higher selectivity, fewer side effects, and lower toxicity since they bind at allosteric sites that are topographically distinct from the classic orthosteric sites. However, the allosteric binding pockets are not conserved and there are no cogent methods to comprehensively characterize the features of allosteric sites with the binding of modulators. To overcome this limitation, our lab has developed a novel algorithm that can quantitatively characterize the receptor-ligand binding feature named Molecular Complex Characterizing System (MCCS). To illustrate the methodology and application of MCCS, we take G protein coupled receptors (GPCRs) as an example. First, we summarized and analyzed the reported allosteric binding pockets of class A GPCRs using MCCS. Sequentially, a systematic study was conducted between cannabinoid receptor type 1 (CB1) and its allosteric modulators, where we used MCCS to analyze the residue energy contribution and the interaction pattern. Finally, we validated the predicted allosteric binding site in CB2 via MCCS in combination with molecular dynamics (MD) simulation. Our results demonstrate that the MCCS program is advantageous in recapitulating the allosteric regulation pattern of class A GPCRs of the reported pockets as well as in predicting potential allosteric binding pockets. This MCCS program can serve as a valuable tool for the discovery of small-molecule allosteric modulators for class A GPCRs.

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.