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:

Small and colorful stones make beautiful mosaics: fragment-based chemogenomics. Smaller stones with a wide variety of colors make a higher resolution mosaic. In much the same way, smaller chemical entities that are structurally diverse are better able to interrogate protein binding sites. This feature article describes the construction of a diverse fragment library and an analysis of the screening of six representative protein targets belonging to three diverse target classes (G protein-coupled receptors ADRB2, H1R, H3R, and H4R, the ligand-gated ion channel 5-HT3R, and the kinase PKA) using chemogenomics approaches. The integration of experimentally determined bioaffinity profiles across related and unrelated protein targets and chemogenomics analysis of fragment binding and protein structure allow the identification of: (i) unexpected similarities and differences in ligand binding properties, and (ii) subtle ligand affinity and selectivity cliffs. With a wealth of fragment screening data being generated in industry and academia, such approaches will contribute to a more detailed structural understanding of ligand-protein interactions.
{"Chemical": []}