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

Li, Lian; Zuo, Zhiyan; Wang, Yuanzhong

doi:10.3389/fmicb.2022.931967

Cited by 4 publications

(4 citation statements)

References 44 publications

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“…Thus, the development of natural products is of a great importance in clinical therapy, especially in combination with machine learning, is an innovative, forward-looking, and applicable new model. The effective scientific characterization of natural products is the basis for using machine learning [ 48 ]. Chemical descriptors and fingerprints are often used to quantify the natural products’ effective chemical entities physicochemical characteristics and the related biological target molecules.…”

Section: Applications Of Machine Learning In Tcm Researchmentioning

confidence: 99%

“…While chemical fingerprints are more complex for encoding as binary bit strings. Chemical fingerprints can reflect the active constituents in substances and can effectively characterize the quality of TCM’s materials [ 48 ]. Both molecular descriptors and fingerprints perform crucial functions in machine learning-based applications for drug discovery processes such as target molecule ranking, similarity-based compound search, and virtual screening [ 49 ].…”

Section: Applications Of Machine Learning In Tcm Researchmentioning

confidence: 99%

“…On the basis of these biomarkers, several natural products such as dan shen and san qi , were identified as the potential TCM preparations for the treatment of myocardial infarction. By utilizing machine learning (residual CNN and partial least squares discriminant analysis), fingerprint, and network pharmacology, Li [ 48 ] screened the potential biomarkers in different parts of Wolfiporia cocos . Yuan [ 91 ] used RF to construct a drug-target prediction model to predict the key targets of Corydalis Rhizoma in the treatment of cardiovascular and cerebrovascular diseases.…”

Section: Applications Of Machine Learning In Tcm Researchmentioning

confidence: 99%

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Machine learning in TCM with natural products and molecules: current status and future perspectives

Liu

et al. 2023

Chin Med

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Traditional Chinese medicine (TCM) has been practiced for thousands of years with clinical efficacy. Natural products and their effective agents such as artemisinin and paclitaxel have saved millions of lives worldwide. Artificial intelligence is being increasingly deployed in TCM. By summarizing the principles and processes of deep learning and traditional machine learning algorithms, analyzing the application of machine learning in TCM, reviewing the results of previous studies, this study proposed a promising future perspective based on the combination of machine learning, TCM theory, chemical compositions of natural products, and computational simulations based on molecules and chemical compositions. In the first place, machine learning will be utilized in the effective chemical components of natural products to target the pathological molecules of the disease which could achieve the purpose of screening the natural products on the basis of the pathological mechanisms they target. In this approach, computational simulations will be used for processing the data for effective chemical components, generating datasets for analyzing features. In the next step, machine learning will be used to analyze the datasets on the basis of TCM theories such as the superposition of syndrome elements. Finally, interdisciplinary natural product-syndrome research will be established by unifying the results of the two steps outlined above, potentially realizing an intelligent artificial intelligence diagnosis and treatment model based on the effective chemical components of natural products under the guidance of TCM theory. This perspective outlines an innovative application of machine learning in the clinical practice of TCM based on the investigation of chemical molecules under the guidance of TCM theory.

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Section: Applications Of Machine Learning In Tcm Researchmentioning

confidence: 99%

Section: Applications Of Machine Learning In Tcm Researchmentioning

confidence: 99%

Section: Applications Of Machine Learning In Tcm Researchmentioning

confidence: 99%

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Machine learning in TCM with natural products and molecules: current status and future perspectives

Liu

et al. 2023

Chin Med

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“… 31 Machine-learning (ML), a research hotspot in artificial intelligence, has been proven to be highly efficient and accurate in predicting relevant data when applied to the medical field. 32 …”

Section: Introductionmentioning

confidence: 99%

Network Pharmacology Analysis and Machine-Learning Models Confirmed the Ability of YiShen HuoXue Decoction to Alleviate Renal Fibrosis by Inhibiting Pyroptosis

Feng,

Luo,

et al. 2023

DDDT

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Purpose YiShen HuoXue decoction (YSHXD) is a formulation that has been used clinically for the treatment of renal fibrosis (RF) for many years. We aimed to clarify therapeutic effects of YSHXD against RF and potential pharmacological mechanisms. Materials and Methods We used network pharmacology analysis and machine-learning to screen the core components and core targets of YSHXD against RF, followed by molecular docking and molecular dynamics simulations to confirm the reliability of the results. Finally, we validated the network pharmacology analysis experimentally in HK-2 cells and a rat model of RF established by unilateral ureteral ligation (UUO). Results Quercetin, kaempferol, luteolin, beta-sitosterol, wogonin, stigmasterol, isorhamnetin, baicalein, and dihydrotanshinlactone progesterone were identified as the main active components of YSHXD in the treatment of unilateral ureteral ligation-induced RF, with IL-6, IL1β, TNF, AR, and PTGS2 as core target proteins. Molecular docking and molecular dynamics simulations further confirmed the relationship between compounds and target proteins. The potential molecular mechanism of YSHXD predicted by network pharmacology analysis was confirmed in HK-2 cells and UUO rats. YSHXD downregulated NLRP3, ASC, NF-κBp65, Caspase-1, GSDMD, PTGS2, IL-1β, IL-6, IL-18, TNF-α, α-SMA and upregulated HGF, effectively alleviating the RF process. Conclusion YSHXD exerts important anti-inflammatory and anti-cellular inflammatory necrosis effects by inhibiting the NLRP3/caspase-1/GSDMD-mediated pyroptosis pathway, indicating that YSHXD represents a new strategy and complementary approach to RF therapy.

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Prospects for the application of traditional Chinese medicine network pharmacology in food science research

Bai

Tao

et al. 2023

J Sci Food Agric

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There has always been a particular difficulty with in‐depth research on the mechanisms of food nutrition and bioactivity. The main function of food is to meet the nutritional needs of the human body, rather than to exert a therapeutic effect. Its relatively modest biological activity makes it difficult to study from the perspective of general pharmacological models. With the popularity of functional foods and the concept of dietary therapy, and the development of information and multi‐omics technology in food research, research into these mechanisms is moving towards a more microscopic future. Network pharmacology has accumulated nearly 20 years of research experience in traditional Chinese medicine (TCM), and there has been no shortage of work from this perspective on the medicinal functions of food. Given the similarity between the concept of ‘multi‐component‐multi‐target’ properties of food and TCM, we think that network pharmacology is applicable to the study of the complex mechanisms of food. Here we review the development of network pharmacology, summarize its application to ‘medicine and food homology’, and propose a methodology based on food characteristics for the first time, demonstrating its feasibility for food research. © 2023 Society of Chemical Industry.

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

Cited by 4 publications

References 44 publications

Machine learning in TCM with natural products and molecules: current status and future perspectives

Machine learning in TCM with natural products and molecules: current status and future perspectives

Network Pharmacology Analysis and Machine-Learning Models Confirmed the Ability of YiShen HuoXue Decoction to Alleviate Renal Fibrosis by Inhibiting Pyroptosis

Prospects for the application of traditional Chinese medicine network pharmacology in food science research

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