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:

Profiling the structural determinants of heteroarylnitrile scaffold-based derivatives as falcipain-2 inhibitors by in silico methods. Evidence indicates that cysteine protease falcipain-2 plays essential role in malaria parasites; therefore the potent and selective inhibitors of falcipain-2 may be therapeutically useful drugs for treatment of various forms of malaria parasite plasmodium. In order to understand the structure-activity correlation of falcipain-2 inhibitors, a set of ligand- and receptor-based 3D-QSAR models were, for the first time, developed in the present work employing Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) for 240 promising molecules. Based on the ligand-based alignment, an optimal 3D-QSAR model was obtained with good predictive power of Q(2) = 0.501, R(2) ncv = 0.890, SEE = 0.282, F = 153.522 and R(2) pred = 0.768. And the contour maps intuitively suggest where to modify the molecular structures in order to improve the binding affinity. In addition, docking analysis and molecular dynamics simulation (MD) study were also carried out on the dataset with purpose of exploring the detailed binding modes of ligand in the falcipain-2 binding pocket. The combination of docking analysis and MD simulation shows that Gly83, Trp43 and Ala175 which formed several H-bonds are crucial for falcipain-2 inhibitors. The analysis of the best QSAR model reveals the structural features related to the activity, and provides an insight into molecular mechanisms of inhibition and possible modification of the molecules for better activity.
{"Chemical": ["cysteine", "Trp", "Ala", "heteroarylnitrile", "H", "Gly"]}