AIMC Topic: Cannabinoids
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Machine learning-enhanced multi-trait genomic prediction for optimizing cannabinoid profiles in cannabis.
The Plant journal : for cell and molecular biology
Nov 27, 2024
Cannabis sativa L., known for its medicinal and psychoactive properties, has recently experienced rapid market expansion but remains understudied in terms of its fundamental biology due to historical prohibitions. This pioneering study implements GS ...
Artificial Intelligent Deep Learning Molecular Generative Modeling of Scaffold-Focused and Cannabinoid CB2 Target-Specific Small-Molecule Sublibraries.
Cells
Mar 7, 2022
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 gene...
Metabolomics predicts the pharmacological profile of new psychoactive substances.
Journal of psychopharmacology (Oxford, England)
Nov 19, 2018
BACKGROUND: The unprecedented proliferation of new psychoactive substances (NPS) threatens public health and challenges drug policy. Information on NPS pharmacology and toxicity is, in most cases, unavailable or very limited and, given the large numb...
Quantitative Determination of Δ9-THC, CBG, CBD, Their Acid Precursors and Five Other Neutral Cannabinoids by UHPLC-UV-MS.
Planta medica
Dec 20, 2017
Cannabinoids are a group of terpenophenolic compounds in the medicinal plant (Cannabaceae family). Cannabigerolic acid, Δ-tetrahydrocannabinolic acid A, cannabidiolic acid, Δ-tetrahydrocannabinol, cannabigerol, cannabidiol, cannabichromene, and tetr...
Surface enhanced Raman spectroscopy (SERS) as a method for the toxicological analysis of synthetic cannabinoids.
Talanta
Nov 12, 2016
Synthetic cannabinoids (K2, spice) present problems in forensic investigations because standard presumptive methods, such as immunoassays, are insufficiently specific for the wide range of potential target compounds. This issue can lead to problems w...
Determination of selected synthetic cannabinoids and their metabolites by micellar electrokinetic chromatography--mass spectrometry employing perfluoroheptanoic acid-based micellar phase.
Talanta
Dec 31, 2015
Perfluoroheptanoic acid was employed as a volatile micellar phase in background electrolyte for micellar electrokinetic chromatography-tandem mass spectrometry separation and determination of 15 selected naphthoyl- and phenylacetylindole- synthetic c...
Identifying metabolites of new psychoactive substances using in silico prediction tools.
Archives of toxicology
Jul 1, 2025
New psychoactive substances (NPS) pose an increasing challenge for clinical and forensic toxicology due to the initial lack of analytical and metabolic data. This study evaluates the performance of four in silico prediction tools (GLORYx, BioTransfor...
Accurate Identification of MDMB-Type Synthetic Cannabinoids through Design of Dual Excited-State Intramolecular Proton Transfer Site Probe and Deep-Learning.
Analytical chemistry
Jun 10, 2025
Synthetic cannabinoids, a novel class of highly toxic psychoactive substances with various disguised forms, have posed significant risks to public safety, and their weak reactivity presents a substantial challenge for swift and accurate analysis. In ...
Ligand biological activity predictions using fingerprint-based artificial neural networks (FANN-QSAR).
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2015
This chapter focuses on the fingerprint-based artificial neural networks QSAR (FANN-QSAR) approach to predict biological activities of structurally diverse compounds. Three types of fingerprints, namely ECFP6, FP2, and MACCS, were used as inputs to t...
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