Suchergebnisse

The nonmedical use of synthetic cathinones is increasing on a global scale. 4-Methyl-N-methylcathinone (mephedrone) is a popular synthetic cathinone that is now illegal in the United States and other countries. Since the legislative ban on mephedrone, a number of 'second-generation' analogs have appeared in the street drug marketplace, including 4-methyl-N-ethylcathinone (4-MEC) and 4′-methyl-α-pyrrolidinopropiophenone (4-MePPP). Here we characterized the interactions of 4-MEC and 4-MePPP with transporters for 5-HT (SERT) and dopamine (DAT) using molecular, cellular, and whole-animal methods. In vitro transporter assays revealed that 4-MEC displays unusual 'hybrid' activity as a SERT substrate (ie, 5-HT releaser) and DAT blocker, whereas 4-MePPP is a blocker at both transporters but more potent at DAT. In vivo microdialysis experiments in rat brain demonstrated that 4-MEC (1–3 mg/kg, i.v.) produced large increases in extracellular 5-HT, small increases in dopamine, and minimal motor stimulation. In contrast, 4-MePPP (1–3 mg/kg, i.v.) produced selective increases in dopamine and robust motor stimulation. Consistent with its activity as a SERT substrate, 4-MEC evoked inward current in SERT-expressing Xenopus oocytes, whereas 4-MePPP was inactive in this regard. To examine drug–transporter interactions at the molecular level, we modeled the fit of 4-MEC and 4-MePPP into the binding pockets for DAT and SERT. Subtle distinctions in ligand–transporter binding were found that account for the differential effects of 4-MEC and 4-MePPP at SERT. Collectively, our results provide key information about the pharmacology of newly emerging mephedrone analogs, and give clues to structural requirements that govern drug selectivity at DAT vs SERT.

Computational approaches in drug discovery and development hold great promise, with artificial intelligence methods undergoing widespread contemporary use, but the experimental validation of these new approaches is frequently inadequate. We are initiating Critical Assessment of Computational Hit-finding Experiments (CACHE) as a public benchmarking project that aims to accelerate the development of small molecule hit-finding algorithms by competitive assessment. Compounds will be identified by participants using a wide range of computational methods for dozens of protein targets selected for different types of prediction scenarios, as well as for their potential biological or pharmaceutical relevance. Community-generated predictions will be tested centrally and rigorously in an experimental hub(s), and all data, including the chemical structures of experimentally tested compounds, will be made publicly available without restrictions. The ability of a range of computational approaches to find novel compounds will be evaluated, compared, and published. The overarching goal of CACHE is to accelerate the development of computational chemistry methods by providing rapid and unbiased feedback to those developing methods, with an ancillary and valuable benefit of identifying new compound-protein binding pairs for biologically interesting targets. The initiative builds on the power of crowd sourcing and expands the open science paradigm for drug discovery. ; ACKNOWLEDGEMENTS The Structural Genomics Consortium is a registered charity (no: 1097737) that receives funds from Bayer AG, Boehringer Ingelheim, Bristol Myers Squibb, Genentech, Genome Canada through Ontario Genomics Institute [OGI-196], Janssen, Merck KGaA (aka EMD in Canada and US), Pfizer, Takeda and the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 875510. The JU receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA and Ontario Institute for Cancer Research, Royal Institution for ...