You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["Chemical"].

Please return the output as a JSON object of the format: {"Chemical": ["Arsenic", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Novel screening assay for the selective detection of G-protein-coupled receptor heteromer signaling. Drugs targeting G-protein-coupled receptors (GPCRs) make up more than 25% of all prescribed medicines. The ability of GPCRs to form heteromers with unique signaling properties suggests an entirely new and unexplored pool of drug targets. However, current in vitro assays are ill equipped to detect heteromer-selective compounds. We have successfully adapted an approach, using fusion proteins of GPCRs and chimeric G proteins, to create an in vitro screening assay (in human embryonic kidney cells) in which only activated heteromers are detectable. Here we show that this assay can demonstrate heteromer-selective G-protein bias as well as measure transinhibition. Using this assay, we reveal that the δ-opioid receptor agonist ADL5859, which is currently in clinical trials, has a 10-fold higher potency against δ-opioid receptor homomers than δ/μ-opioid receptor heteromers (pEC(50) = 6.7 ± 0.1 versus 5.8 ± 0.2). The assay enables the screening of large compound libraries to identify heteromer-selective compounds that could then be used in vivo to determine the functional role of heteromers and develop potential therapeutic agents.
{"Chemical": ["ADL5859"]}