Application Values of Coumarin Compound Against Pediatric Bronchopneumonia and Autonomous Prediction of Novel Structures with Machine Learning

摘要

In this research, a new coumarin compound was obtained, and then its crystal architecture was determined. This complex's application value against pediatric bronchopneumonia was identified, and the specific mechanism was simultaneously discussed. First, real time RT-PCR was conducted, and the suppressive activity on the relative expression of Streptococcus pneumonia survival gene was measured. Next, the inflammatory cytokines released into the alveolar lavage fluid was tested using ELISA. Through reinforcement learning and molecular docking simulation, several novel molecules with low binding affinity energy and high quantitative estimate of drug-likeness and synthetic accessibility scores were predicted, and their biological activities were evaluated due to the multiple hydrogen bonds with the given receptor.