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

Advances in Activity/Property Prediction from Chemical Structures

Recent technological advancement in AI modeling of molecular property databases has significantly expanded the opportunities for drug design and development. Quantitative structure-activity relationships (QSARs) are shown to provide more accurate predictions with regards to biological activity as well as toxicological assessment. By using a combination of in-silico models or by combining disparate structure-activity databases, researchers have been able to improve accuracy for a variety of drug discovery and analysis methods, generating viable compounds, which in certain cases, can be synthesized and further studied in vitro to find candidates for potential development. Additionally, the development of compounds of determined toxicology can be discontinued earlier, allowing alternative routes to be evaluated, preventing wasted time and resources. Although the progress that has been made is tremendous, expert review is still necessary for most in-silico generated predictions. Regardless, the scientific community continues to move ever closer to completely automated drug discovery and evaluation.

Chemoinformatics Study of Benzodiazepine-1, 2, 3-triazole Derivatives Targeting Butyrylcholinesterase

This study aims to assess the potential bioactivity of newly designed benzodiazepine-1,2,3-triazole derivatives using in-silico methodologies, with a primary focus on elucidating their inhibitory interactions with the butyrylcholinesterase (BuChE) enzyme, which is implicated in Alzheimer's disease. We employed multiple linear regression (MLR) methods to conduct a quantitative structure-activity relationship (QSAR) analysis on a collection of 31 benzodiazepine-1,2,3-triazole derivatives, with the goal of investigating, assessing, and predicting their activities, as well as designing novel compounds. This approach yielded highly accurate results, with coefficients of determination (R²) of 0.77 and 0.81 for the training and test datasets, respectively. Additionally, the optimized compounds were subjected to an Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analysis, demonstrating their potential as non-hepatotoxic agents with enhanced absorption and blood-brain barrier permeability. To further validate these findings, the most favorable docking conformations were analyzed using molecular dynamics (MD) simulations with GROMACS software, predicting the stability of the formed complexes. These simulations underscored the critical role of hydrogen bonds in stabilizing the compounds at the BuChE receptor binding site. The results hold great promise for the development of innovative benzodiazepine-1,2,3-triazole derivatives as effective BuChE inhibitors, potentially leading to therapeutic interventions for Alzheimer's disease.

Ultrasonic-induced synthesis of novel diverse arylidenes via Knoevenagel condensation reaction. Antitumor, QSAR, docking and DFT assessment

A series of arylidenes derivatives was synthesized under ultrasonic methodology via Knoevenagel condensation reaction of cyanoacetohydrazide derivative with the appropriate aldehydes and/or ketone. The anticancer properties of the newly synthesized compounds were tested against four different human cancer cell lines (HEPG-2, MCF-7, HCT-116, and PC-3); compounds 5d and 6 demonstrated the greatest anticancer activity against all cancer cell lines. The MLR technique was used to create the QSAR model using five molecular descriptors (AATS6p, AATS7p, AATS8p, AATS0i, and SpMax4_Bhv). The examination of the constructed QSAR model equations revealed that the selected descriptors influence the tested compound's anti-proliferative activity. The descriptors identified in this work by QSAR models can be utilized to predict the anticancer activity levels of novel arylidenes derivatives. This will allow for significant cost savings in the drug development process and synthesis at pharmaceutical chemistry laboratories. According to the physicochemical properties, the results revealed that all of these compounds comply with Lipinski's Rule of Five, indicating that they may have high permeability across biological membranes and reveal drug-relevant properties. The Swiss Target Prediction webtool was used to assess the probable cellular mechanism for the promising candidate compounds (5d and 6), and the results revealed that adenosine A1 receptor (ADORA1) was a common target for both compounds. ADORA1 is involved in the regulation of cell metabolism and gene transcription. ADORA1 overexpression has been linked to a variety of cancers, including colon cancer, breast cancer, leukemia, and melanoma. The docking study of tested compounds 5d and 6 revealed that their binding scores to ADORA1 are more favorable than those of its co-crystalized ligand (DU172, selective ADORA1 antagonist) and adenosine (ADORA1 endogenous agonist), implying that they may hold great promise as an anti-cancer therapy. Density functional theory (DFT) with a (B3LYP)/6-31G (d,p) basis set was used to calculate the physicochemical parameters of these compounds. The theoretical data from the DFT computation was found to be in good agreement with the experimental values.

Designer benzodiazepines: an update

INTRODUCTION

Designer benzodiazepines (DBs) are a subclass of novel psychoactive substances (NPS). DBs mimic the properties of approved and prescribed benzodiazepines.

AREA COVERED

A systematic search of literature on DB classification, structure-activity relationships, pharmacologic properties, and adverse effects.

EXPERT OPINION

The prevalence of DB use has increased substantially over the last decade. All DBs are full-agonist ligands at the gamma-aminobutyric acid type A-benzodiazepine (GABA_A-BZ) receptor system. This is not surprising, since DBs largely represent either minor structural modifications, or well-recognized active metabolites, of existing approved benzodiazepines. As such, the pharmacologic profile and associated risks and hazards of DBs are similar or identical to clinically approved and legitimately prescribed benzodiazepines, most of which have been in use for decades. Concurrent use of DBs along with other abusable or recreational drugs (alcohol, opioids, cocaine, stimulants, hallucinogens, other sedative-hypnotics) represents the principal public health risk. The increasing illicit availability and use of DBs is of concern and requires regulatory attention, but DBs do not rank highly among designer psychotropic agents in terms of health risk to humans.

In silico studies on recreational drugs: 3D quantitative structure activity relationship prediction of classified and de novo designer benzodiazepines

Currently, increasing availability and popularity of designer benzodiazepines (DBZDs) constitutes a primary threat to public health. To assess this threat, the biological activity/potency of DBZDs was investigated using in silico studies. Specific Quantitative Structure Activity Relationship (QSAR) models were developed in Forge™ for the prediction of biological activity (IC50 ) on the γ-aminobutyric acid A receptor (GABA-AR) of previously identified classified and unclassified DBDZs. A set of new potential ligands resulting from scaffold hopping studies conducted with MOE® was also evaluated. Two generated QSAR models (i.e. 3D-field QSAR and RVM) returned very good performance statistics (r2  = 0.98 [both] and q2  = 0.75 and 0.72, respectively). The DBZDs predicted to be the most active were flubrotizolam, clonazolam, pynazolam and flucotizolam, consistently with what reported in literature and/or drug discussion fora. The scaffold hopping studies strongly suggest that replacement of the pendant phenyl moiety with a five-membered ring could increase biological activity and highlight the existence of a still unexplored chemical space for DBZDs. QSAR could be of use as a preliminary risk assessment model for (newly) identified DBZDs, as well as scaffold hopping for the creation of computational libraries that could be used by regulatory bodies as support tools for scheduling procedures.

Designer Benzodiazepines' Activity on Opioid Receptors: A Docking Study

BACKGROUND

Previous studies have reported that benzodiazepines (BZDs) seem to enhance euphoric and reinforcing properties of opioids in opioid users so that a direct effect on opioid receptors has been postulated, together with a possible synergistic induction of severe side effects due to co use of BDZs and opioids. This is particularly worrisome given the appearance on the market of designer benzodiazepines (DBZDs), whose activity/toxicity profiles are scarcely known.

OBJECTIVES

This study aimed to evaluate, through computational studies, the binding affinity (or lack thereof) of 101 DBZDs identified online on the kappa, mu, and delta opioid receptors (K, M, DOR); and to assess whether their mechanism of action could include activation of the latter.

METHODS

MOE® was used for the computational studies. Pharmacophore mapping based on strong opioids agonist binders' 3D chemical features was used to filter the DBZDs. Resultant DBZDs were docked into the crystallised 3D active conformation of KOR (PDB6B73), DOR (PDB6PT3) and MOR (PDB5C1M). Co-crystallised ligands and four strong agonists were used as reference compounds. A score (S, Kcal/mol) representative of the predicted binding affinity, and a description of ligand interactions were obtained from MOE®.

RESULTS

The docking results, filtered for S < -8.0 and the interaction with the Asp residue, identified five DBZDs as putative binders of the three ORs : ciclotizolam, fluloprazolam, JQ1, Ro 48-6791, and Ro 48-8684.

CONCLUSION

It may be inferred that at least some DBZDs may have the potential to activate opioid receptors. This could mediate/increase their anxiolytic, analgesic, and addiction potentials, as well as worsen the side effects associated with opioid co-use.

Molecular mechanisms of action of stimulant novel psychoactive substances that target the high-affinity transporter for dopamine

Drug misuse is a significant social and public health problem worldwide. Misused substances exert their neurobehavioural effects through changing neural signalling within the brain, many of them leading to substance dependence and addiction in the longer term. Among drugs with addictive liability, there are illicit classical stimulants such as cocaine and amphetamine, and their more recently available counterparts known as novel psychoactive substances (NPS). Stimulants normally increase dopamine availability in the brain, including the pathway implicated in reward-related behaviour. This pattern is observed in both animal and human brain. The main biological target of stimulants, both classical and NPS, is the dopamine transporter (DAT) implicated in the dopamine-enhancing effects of these drugs. This article aims at reviewing research on the molecular mechanisms underpinning the interactions between stimulant NPS, such as benzofurans, cathinones or piperidine derivatives and DAT, to achieve a greater understanding of the core phenomena that decide about the addictive potential of stimulant NPS. As the methodology is essential in the process of experimental research in this area, we review the applications of in vitro, in vivo and in silico approaches. The latter, including molecular dynamics, attracts the focus of the present review as the method of choice in molecular and atomistic investigations of the mechanisms of addiction of stimulant NPS. Research of this kind is of interest to not only scientists but also health professionals as updated knowledge of NPS, their modes of action and health risks, is needed to tackle the challenges posed by NPS misuse.