Multi-stage virtual screening of natural products against p38α mitogen-activated protein kinase: predictive modeling by machine learning, docking study and molecular dynamics simulation

Yang, Ruoqi; Zha, Xuan; Gao, Xingyi; Wang, Kangmin; Cheng, Bin; Yan, Bin

doi:10.1016/j.heliyon.2022.e10495

Cited by 6 publications

(3 citation statements)

References 42 publications

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“…Zhao et al established a HPLC fingerprinting method centered on predicting Q-marker of Atractylodis Rhizoma [Asteraceae; Atractylodis macrocephalae Rhizoma] through network pharmacology (Zhao et al, 2023). Cheng et al screened out the potential anti-AS mechanisms and chemical Q-markers based on the combination of serum pharmacochemistry and network pharmacology (Cheng et al, 2022). He et al put forward a new strategy of multi-dimensional "radar chart" mode discover the Q-markers of Qiliqiangxin Capsule (QLQX), which provided a new idea for TCM quality management (He et al, 2021).…”

Section: Identification Of Quality Marker (Q-marker)mentioning

confidence: 99%

“…Modern research has confirmed that TCM play an important role in the medical field, as evidenced by its role in enhancing antitumor effect and treating various disease (Augustin et al, 2020;Bai et al, 2022). A large number of clinical studies have consistently demonstrated that some components in TCM show remarkable curative and relieving effect, especially for chronic and complex diseases that cannot be solved by traditional medical solutions (Huang and Xuan, 2020;Leung and Xu, 2020;Cheng et al, 2022;Huang et al, 2023). Due to the potential side effects associated with many modern chemically synthesized drugs, there is a growing need to seek safer alternative medications.…”

Section: Introductionmentioning

confidence: 99%

“…Its theories, methods and technical applications simulate, extend and expand human intelligence (Abolaban, 2023). AI uses various algorithms for machine learning and deep learning, including support vector machine (SVM), Bayesian network, artificial neural networks (ANNs), random forest (RF), convolutional neural networks (CNNs) and more (Santos et al, 2021;Yang et al, 2022). Over recent decades, AI has made significant breakthroughs in various fields, such as finance (Ahmed et al, 2022), traffic (Shaygan et al, 2022), electrical automation (Sami, 2022), medical care (Yahyaoui et al, 2023), biomedical research and others (Diakiw et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Integrating artificial intelligence into the modernization of traditional Chinese medicine industry: a review

Zhou,

Shen,

Hou

2024

Front. Pharmacol.

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Traditional Chinese medicine (TCM) is the practical experience and summary of the Chinese nation for thousands of years. It shows great potential in treating various chronic diseases, complex diseases and major infectious diseases, and has gradually attracted the attention of people all over the world. However, due to the complexity of prescription and action mechanism of TCM, the development of TCM industry is still in a relatively conservative stage. With the rise of artificial intelligence technology in various fields, many scholars began to apply artificial intelligence technology to traditional Chinese medicine industry and made remarkable progress. This paper comprehensively summarizes the important role of artificial intelligence in the development of traditional Chinese medicine industry from various aspects, including new drug discovery, data mining, quality standardization and industry technology of traditional Chinese medicine. The limitations of artificial intelligence in these applications are also emphasized, including the lack of pharmacological research, database quality problems and the challenges brought by human-computer interaction. Nevertheless, the development of artificial intelligence has brought new opportunities and innovations to the modernization of traditional Chinese medicine. Integrating artificial intelligence technology into the comprehensive application of Chinese medicine industry is expected to overcome the major problems faced by traditional Chinese medicine industry and further promote the modernization of the whole traditional Chinese medicine industry.

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Section: Identification Of Quality Marker (Q-marker)mentioning

confidence: 99%