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:

A new QSAR model, for angiotensin I-converting enzyme inhibitory oligopeptides. A new quantitative structure activity relationship (QSAR) model is established for oligopeptides that inhibit angiotensin I-converting enzyme (ACE). Information concerning the C-terminal pentapeptide is considered to describe the peptide structure in the model. A database is constructed, with 263 ACE inhibitory peptides and 38 physicochemical descriptors, abstracted from the published literature. The model is generated through a generalised linear model, with a gamma distribution that yields a coefficient of determination of 94.4%. The whole C-terminal pentapeptide information is a determinant for modelling the ACE inhibition activity of oligopeptides. Starting from the C-terminus, the C-1 position is the most relevant position in the model; this is followed by position C-4. In C-1, there is a preference for aliphatic and tiny residues. However, in the C-4 position, the model indicates a clear preference for bulky hydrophobic amino acids and for sulphur-containing amino acids. Due to its good predictive capability, this model could be used as a tool for identifying and prioritizing the potential ACE inhibitory peptides present in a complex matrix.
{"Chemical": ["sulphur", "angiotensin I", "C", "amino acids"]}