Fe-N-C single-atom nanozymes based sensor array for dual signal selective determination of antioxidants.

Machine learning algorithms as a powerful tool can efficiently utilize and process large quantities of data generated by high-throughput experiments in various fields. In this work, we used a general ionic salt-assisted synthesis method to prepare oxidase-like Fe-N-C SANs. The possible reason for the excellent enzyme-mimicking activity and affinity of Fe-N-C SANs was further verified by density functional theory calculations. Due to the remarkable oxidase-mimicking activity, the prepared Fe-N-C SANs were used to detect ascorbic acid (AA) with a detection limit of 0.5 µM. Based on the machine learning algorithms, we successfully distinguished six antioxidants (ascorbic acid, glutathione, L-cysteine, dithiothreitol, uric acid, and dopamine) with the same concentration by either one kind of Fe-N-C SANs or three kinds of different Fe-N-C SANs. The usefulness of the Fe-N-C SANs sensor arrays was further validated by the hierarchal cluster analysis, where they also can be correctly identified. More importantly, a SANs-based digital-image colorimetric sensor array has also been successfully constructed and thereby achieved visual and informative colorimetric analysis for practical samples out of the lab. This work not only provides a design synthesis method to prepare SANs but also combines machine learning algorithms with SANs sensors to identify analytes with similar properties, which can further expand to the detection of proteins and cells related to diseases in the future.

Material Basis of Xuanfei Huazhuo Prescription in Treatment of COVID-19 by Multi-target Molecular Docking / 中国实验方剂学杂志

Objective:Structure-based angiotension converting enzyme 2 (ACE2) and interleukin-6R (IL-6R) were taken as the target proteins to in the investigation of the material basis of Xuanfei Huazhuo prescription in the treatment of coronavirus disease-2019 (COVID-19) by molecular docking. Method:The compounds in Xuanfei Huazhuo prescription were retrieved through TCMSP. Structure-based ACE2 and IL-6R were taken as the target proteins to screen out the compounds with a better activity by molecular docking, and analyze structural properties of these compounds. Furthermore, the potential molecular mechanism of Xuanfei Huazhuo prescription in the treatment of COVID-19 was analyzed by target reverse prediction. Result:There were 312 potentially active compounds in Xuanfei Huazhuo prescription, including 75 highly active compounds and 15 highly active compounds for ACE2. There were 100 eligible active compounds and 3 highly active compounds for IL-6R, most of which belong to flavonoids. The herb-component-target network included 10 herbs, 126 compounds and 130 targets. String analysis showed that PIK3R1, SRC, AKT1, AR and EGFR might be the key targets of Xuanfei Huazhuo prescription. Conclusion:Based on the virtual screening of multi-target molecular docking, the anti-virus and anti-inflammatory material basis of Xuanfei Huazhuo prescription was preliminarily obtained. At the same time, based on the reverse prediction and analysis, potential targets and molecular mechanism of the recipe in the treatment of COVID-19 were explored, so as to provide clues for the multi-angle mining of Xuanfei Huazhuo prescription and its relevant prescriptions and the modernization development of monomer components.