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:

Unraveling the Role of the Protein Environment for [FeFe]-Hydrogenase: A New Application of Coarse-Graining. Hydrogenase enzymes are natural biocatalysts that might be harnessed to reduce the cost of hydrogen gas production. [FeFe]-hydrogenases are the most effective of three such enzymes at catalyzing H(+) reduction. In this study, we develop and apply a novel combination of all-atom molecular dynamics and coarse-grained (CG) analysis to characterize two important steps of the catalytic cycle of [FeFe]-hydrogenase. The first is the electron transport through FeS clusters to the active site. We use a Marcus formulation to compute the free energy and the reorganization energy of three electron transport steps and decompose these values into contributions from the CG protein sites and the solvent. The three-step transport process is found to be downhill with relative free energies of -11.7 for the first step, -14.8 for the second step, and -17.1 kcal/mol for the third step. The electron-transport process is also found to activate a water channel suggesting a coupled mechanism for proton and electron transport to the active site. The channel opening is orchestrated by three CG sites located in the active-site domain of the protein with one of the sites also contributing a strong attractive electrostatic potential (ESP) to help shuttle protons to the active site. Overall, our CG analysis points to a concerted mechanism of electron and proton delivery to the active site in these proteins thus providing important insight for the development of biomimetic devices.
{"Chemical": ["hydrogen", "H(+)", "FeS", "[FeFe]"]}