RESUMEN
Cannabis sativa is the drug of abuse most cultivated, trafficked, and consumed worldwide. One of several techniques used to detect cannabinoids is based on the thin-layer chromatography (TLC). However, the designation of the colors observed can be inaccurate and not reproducible. The designation of colors goes beyond physical and physiological aspects, because what is conventionally called color is a socio-cultural construction. Thus, the objective of this paper was to evaluate the different TLC methods to detection of cannabinoids, and apply standardization method in naming of colors. TLC analysis performed using silica gel 60 F254 as a stationary phase. Three mobile phase compositions [hexane:chloroform (8:2 v:v), hexane:ethyl ether (8:2 v:v), and chloroform:hexane (8:2 v:v)], as well as, two different solutions of Fast Blue B salt (FBBS, Azoic Diazo No. 48) and Fast Blue RR (FBRR, Azoic Diazo No. 24) were evaluated. Determination of colors names was realized through the Sci-Chromus® software. The best resolution was obtained using hexane:ethyl ether (8:2 v:v) as a mobile phase. It was observed that although the cannabidiol (CBD), delta-9-tetrahydrocannabinol (Δ9 -THC), cannabinol (CBN), and cannabigerol (CBG) were detect using both the FBBS- and FBRR-acidified solutions, the best visualization was achieved using the latter reagent. To the best of our knowledge, this is the first study that applied and demonstrated a method for standardization and denomination of colors in the TLC analysis of cannabinoids. This method was able to reduce the subjectivity in naming the colors observed and presented several application possibilities.
Asunto(s)
Cannabinoides/análisis , Cromatografía en Capa Delgada , Color , Cloroformo , Compuestos de Diazonio , Éter , Hexanos , HumanosRESUMEN
Octopus is an automated workflow management tool that is scalable for virtual high-throughput screening (vHTS). It integrates MOPAC2016, MGLTools, PyMOL, and AutoDock Vina. In contrast to other platforms, Octopus can perform docking simulations of an unlimited number of compounds into a set of molecular targets. After generating the ligands in a drawing package in the Protein Data Bank (PDB) format, Octopus can carry out geometry refinement using the semi-empirical method PM7 implemented in MOPAC2016. Docking simulations can be performed using AutoDock Vina and can utilize the Our Own Molecular Targets (OOMT) databank. Finally, the proposed software compiles the best binding energies into a standard table. Here, we describe two successful case studies that were verified by biological assay. In the first case study, the vHTS process was carried out for 22 (phenylamino)urea derivatives. The vHTS process identified a metalloprotease with the PDB code 1GKC as a molecular target for derivative LE&007. In a biological assay, compound LE&007 was found to inhibit 80% of the activity of this enzyme. In the second case study, compound Tx001 was submitted to the Octopus routine, and the results suggested that Plasmodium falciparum ATP6 (PfATP6) as a molecular target for this compound. Following an antimalarial assay, Tx001 was found to have an inhibitory concentration (IC50) of 8.2 µM against PfATP6. These successful examples illustrate the utility of this software for finding appropriate molecular targets for compounds. Hits can then be identified and optimized as new antineoplastic and antimalarial drugs. Finally, Octopus has a friendly Linux-based user interface, and is available at www.drugdiscovery.com.br . Graphical Abstract Octopus: A platform for inverse virtual screening (IVS) to search new molecular targets for drugs.