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:

Identification and Characterization of a Cellulose Binding Heptapeptide Revealed by Phage Display. Cellulose nanowhiskers (CNWs) were used in conjunction with phage display technology to identify polypeptides which bind the crystalline region of cellulose. A consensus peptide WHWTYYW was identified to efficiently bind the CNWs. The binding affinities of specific phage particles were assessed using biopanning assays and enzyme-linked immunosorbent assay (ELISA). The WHWTYYW peptide was synthesized and isothermal titration calorimetry (ITC) analysis showed that the peptide exhibited a binding constant of ~10(5) M(-1) toward the crystalline CNWs. In order to understand how the affinity of this peptide differs for non-crystalline cellulose, binding properties were characterized using cello-oligosaccharides as substrates. Binding analysis was performed using UV spectroscopy and fluorescence quenching experiments. The specific molecular interactions of the WHWTYYW peptide with cellohexaose were examined using nuclear magnetic resonance (NMR). Interactions of this peptide with crystalline cellulose were also investigated using computational molecular modeling (MM) studies. The MM and NMR experiments indicate that the WHWTYYW peptide exhibits a bent structure when bound, allowing the Y5 amino acid to form a CH/π stacking interaction and H-bond with the glucose ring of cellulose.
{"Chemical": ["glucose", "cellohexaose", "amino acid", "Heptapeptide", "CH", "H"]}