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:

Configurational Assignment of Secondary Hydroxyl Groups and Methyl Branches in Polyketide Natural Products through Bioinformatic Analysis of the Ketoreductase Domain. Profile hidden Markov models (HMMs) were used to predict the configuration of secondary alcohols and α-methyl branches of modular polyketides. Based on the configurations of two chiral centers in these polyketides, 78 ketoreductases were classified into four different types of polyketide producers. The identification of positions that discriminate between these protein families was followed by fitting six profile HMMs to the data set and the corresponding subsets, to model the conserved regions of the protein types. Ultimately, the profile HMMs described herein predict protein subtypes based on the complete information-rich region; consequently, slight changes in a multiple sequence alignment do not significantly alter the outcome of this classification method. Additionally, Viterbi scores can be used to assess the reliability of the classification.
{"Chemical": ["Methyl", "\u03b1-methyl", "Hydroxyl", "secondary alcohols"]}