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:

Carbonic anhydrase inhibitors: Inhibition of the β-class enzyme from the pathogenic yeast Candida glabrata with sulfonamides, sulfamates and sulfamides. The fungal pathogen Candida glabrata encodes for a β-carbonic anhydrase (CA, EC 4.2.1.1), CgNce103, recently discovered. Only anions have been investigated as CgNce103 inhibitors up until now. Here we report the first sulfonamides inhibition study of this enzyme. Simple sulfonamides showed weak or moderate CgNce103 inhibitory properties, whereas acetazolamide, and a series of 4-substituted ureido-benzene-sulfonamides, sulfamates and sulfamides showed effective CgNce103 inhibitory properties, with KIs in the range of 4.1-115nM, being also ineffective as human CA II inhibitors. As there is significant resistance of C. glabrata clinical isolates to many classical antifungal agents, inhibition of the β-CA from this organism may allow an interesting means of controlling the pathogen growth, eventually leading to antifungals with a novel mechanism of action.
{"Chemical": ["sulfonamides", "sulfamides", "acetazolamide", "sulfamates", "4-substituted ureido-benzene-sulfonamides"]}