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:

Binding of glyco-acridine derivatives to lysozyme leads to inhibition of amyloid fibrillization. While amyloid-related diseases are at the center of intense research efforts, no feasible cure is currently available for these diseases. The experimental and computational techniques were used to study the ability of glyco-acridines to prevent lysozyme amyloid fibrillization in vitro. Fluorescence spectroscopy and atomic force microscopy have shown that glyco-acridines inhibit amyloid aggregation of lysozyme; the inhibition efficiency characterized by the half-maximal inhibition concentration IC50 was affected by the structure and concentration of the derivative. We next investigated relationship between the binding affinity and the inhibitory activity of the compounds. The semiempirical quantum PM6-DH+ method provided a good correlation pointing to the importance of quantum effects on the binding of glyco-acridine derivatives to lysozyme. The contribution of linkers may be explained by the valence bond theory. Our data provide a basis for the development of new small molecule inhibitors effective in therapy of amyloid-related diseases.
{"Chemical": ["acridines", "acridine"]}