AUTHOR=Li Lian , Zuo ZhiTian , Wang YuanZhong 

TITLE=Practical Qualitative Evaluation and Screening of Potential Biomarkers for Different Parts of Wolfiporia cocos Using Machine Learning and Network Pharmacology

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2022.931967

DOI=10.3389/fmicb.2022.931967

ISSN=1664-302X

ABSTRACT=Macrohyporia cocos, has a widely used traditional Chinese medicine and dietary supplement. Artificial intelligence algorithms use different types of data based on different strategies to complete multiple tasks such as search and discrimination, which has become a trend to be suitable for solving massive data analysis problems faced in network pharmacology research. In this study, we attempt to screen the potential biomarkers in different parts of M. cocos from the perspective of measurability and effectiveness based on fingerprint, machine learning, and network pharmacology. From all results: (1) Exploratory analysis results showed that differences between different parts were greater than between different regions, the partial least squares discriminant analysis and residual network models were excellent to identify Poria and Poriae cutis based on Fourier transform near-infrared spectroscopy spectra; (2) From the perspective of effectiveness, the results of network pharmacology showed that 11 components such as dehydrotermoic acid, 16α-hydroxyspinene acid, etc. had high connectivity in the “component-target-pathway” network and were the main active components. (3) For measurability perspective, through orthogonal partial least squares discriminant analysis and the variable importance projection > 1, it was confirmed that three components were the main potential biomarkers based on high performance liquid chromatography, such as dehydrotrametenolic acid, poricoic acid A, and pachymic acid. (4) The content of the three components in Poria was significantly higher than that in Poriae cutis. (5) Integrated analysis showed that dehydrotrametenolic acid, poricoic acid A, and pachymic acid were potential biomarkers for Poria and Poriae cutis. Overall, this approach provided a novel strategy to explore potential biomarkers as a basic with explanation for the clinical application and reasonable development and utilization in Poria and Poriae cutis.