A strategy for the discovery and validation of toxicity quality marker of Chinese medicine based on network toxicology

doi:10.1016/j.phymed.2018.01.018

Phytomedicine

Volume 54, 15 February 2019, Pages 365-370

https://doi.org/10.1016/j.phymed.2018.01.018 Get rights and content

Abstract

Background

Considering that the quality control indicators in Chinese medicine (CM) are disconnected from safety and effectiveness, Prof. Chang-xiao Liu et al. has proposed a concept regarding the quality marker (Q-marker) of CM to promote the healthy development of the CM industry and improve the CM quality control method.

Purpose

In this study, we proposed a strategy to discover and verify the toxicity Q-marker of CM based on network toxicology.

Methods

First, traditional biochemical pathology indicators and sensitive biomarkers were used to predict the toxicity of CM. Next, the chemical composition of toxic CMs and their metabolites were rapidly identified by multidimensional detection techniques. Subsequently, the interaction network between “toxicity - toxic chemical composition - toxic target - effect pathway” was built through network toxicology, and the potential toxicity Q-marker of CM was initially screened. Finally, the chemical properties of toxicity Q-markers were verified by traceability and testability.

Results

Based on the predicted results of network toxicology, the toxic compounds of CM were preliminarily identified, and the toxic mechanism was comprehensively interpreted. In the context of definite biological properties and chemical properties, the toxicity Q-marker was finally confirmed.

Conclusion

This extensive review provides a study method for the toxicity Q-marker of CM, which helps to systemically and thoroughly reveal the internal toxicity mechanism of CM. The in-depth study of the toxicity Q-marker provides the material basis and technical support for the safety evaluation of CM.

Graphical abstract

Introduction

Chinese medicine (CM) comprises many complex chemical compositions, and their therapeutic effects are the synergistic effect of the multicomponents, multitargets, and multipathways (Jiang, 2005). Currently, since the quality control standard of CM is mainly limited to appearance identification and characteristic inspection, it cannot effectively and comprehensively reflect the safety and effectiveness of CM by qualitatively and quantitatively analyzing a single indicator or several indicators, which seriously influences the clinical application and quality evaluation of CM (Normile, 2003, Ruiz et al., 2016, Liu et al., 2016). To promote the healthy development of CM and solve the problems existing in the quality control methods in the CM industry, Prof. Chang-xiao Liu has proposed a concept for the quality marker (Q-marker) of CM. Q-markers were derived from chemical compositions that were inherent in raw medicine and related to the functional properties of CM and could be used as the labeling substance to reflect the safety and effectiveness of CM (Liu et al., 2016, 2017). The Q-marker was proposed to address the disconnection of quality control indicators of CM from the safety and effectiveness.

The side effects of CM primarily affect their clinic use; therefore, the CM toxicology studies should be improved to help discover and verify the toxicity Q-marker of CM. Network toxicology integrates the beliefs of network biology and network pharmacology and constructs the network model of “toxic characterization - compound - gene - protein” to describe the toxicological properties of drugs with the help of genomics, proteomics and other biological techniques. Subsequently, through analyzing the relationship between the network models, the toxicity effects of CM, as well as toxic substances, are determined, which might help explore the toxicity mechanism further (Youns et al., 2010). Compared with the traditional toxicological methods, which are time-consuming and less comprehensively researched, network toxicology understands the interaction between drugs and the body from the overall perspective of biological networks, explains the mechanisms of the adverse reactions of CM, and emphasizes the multichannel regulation of signaling pathways. Using network toxicology, we can comprehensively discover the potentially toxic substances in CM, predict the toxicity effects of known compounds, and explain the toxicity mechanism to provide the experimental basis and technical support to study the toxicity Q-Marker of CM (Li et al., 2011; Fan et al., 2011, Calixto, 2000 Wang et al., 2009).

To address the disconnection of the quality control indicators of Chinese medicine (CM) from safety and effectiveness, a research strategy for toxicity Q-marker oriented by network toxicology was proposed in this study. First, according to the traditional biochemical pathology indicators and sensitive biomarkers, the toxicity of CM was predicted, and the toxic target organ was judged. Next, the chemical compositions of toxic CM and their metabolites were rapidly identified by a multidimensional detection technique. Then, the toxic compounds, functional targets and pathways of CM were predicted through network toxicology, and the interaction network underlying “toxic compositions - effect target - effect pathways” was built to comprehensively interpret the poisoning mechanism of CM as well as discover the potential toxicity Q-marker of CM. Finally, based on the biological properties of the Q-Marker, the chemical properties of the toxicity Q-markers were verified from traceability and testability. The technical route is shown in Fig. 1.

Section snippets

Toxicity prediction technology of Chinese medicine

Safety, effectiveness and quality control are the three conditions of CM quality evaluation, and safety is a prerequisite that plays an important role in the development of CM. However, the quality control indicators used for quality evaluation are disconnected from the safety of CM, the understanding of toxicity evaluation is not yet complete, and a set toxicity evaluation system of CM has not been formed. Therefore, it is important to determine the evaluation technology and model, which can

Analysis of chemical constituents and metabolic components of Chinese medicine

Combining the chemical compositions of CM with efficacy and toxicity data provides the background information on efficacy Q-marker and toxicity Q-marker. The effect of CM is determined both by the prototype constituents in vitro and the metabolic components in vivo. Therefore, the study on the pharmacodynamic basis of CM is not only necessary to clarify the chemical constituents in the CM but also to analyze their metabolic regularity in vivo. Comprehensively considering the chemical

A study on the toxicity quality markers of Chinese medicine based on network toxicology

In a study of the toxicity Q-marker oriented by network toxicology, first, the effective targets and pathways of chemical compositions were predicted by reverse molecular docking technology (RMDT), and a network relation of the “chemical composition - effect targets - effect pathway” was constructed, which helped to preliminarily explore the toxicity mechanism. Second, the toxic compositions of Chinese medicine were virtually screened through forward molecular docking technology; a network

Verification of toxicity quality markers of Chinese medicine

According to the determination principle of Q-marker, Q - marker is defined as the chemical component with the features of traceability, transferability, biological specificity and testability. In this study, we attempted to explore the relationship underlying toxicity Q-marker and exogenous compounds or metabolites based on the features of Q-marker. First, toxicity Q-marker is the chemical component which exists naturally in Chinese medicines and Chinese medicine products, or forms in the

Summary

In this study, the Q-marker was used to carry out studies on the biological and chemical properties of toxicity Q-markers. A research strategy was proposed to discover the toxicity Q-marker oriented by network toxicology, which helped to solve the disconnection of the quality control indicator from effectiveness and drug safety. With the introduction of network toxicology, many problems in the complex system of CM have been effectively explained, and the regulatory network of “toxicity - toxic

Acknowledgments

This project was supported by the Program for Changjiang Scholars and Innovative Research Team in University (No. IRT 14R41), the National Natural Science Foundation of China (No. 81573825), The National Natural Science Foundation of China (No. 81273998), and the Research Programs of Application of Basic and Frontier Technology in Tianjin (15JCYBJC29400)

Conflicts of interest

None of the authors has any financial/commercial conflicts of interest to declare.

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¹: These two authors contributed equally to this work and should be co-author.

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A strategy for the discovery and validation of toxicity quality marker of Chinese medicine based on network toxicology

Abstract

Background

Purpose

Methods

Results

Conclusion

Graphical abstract

Introduction

Section snippets

Toxicity prediction technology of Chinese medicine

Analysis of chemical constituents and metabolic components of Chinese medicine

A study on the toxicity quality markers of Chinese medicine based on network toxicology

Verification of toxicity quality markers of Chinese medicine

Summary

Acknowledgments

Conflicts of interest

J. Pharm. Biomed. Anal

J. Pharm. Biomed. Anal.

Trends Pharmacol.

J. Chromatogr. A

Kidney Int.

J. Ethnopharmacol.

Biomed. Pharmacother.

J. Pharm. Biomed. Anal.

Efficacy, safety, quality control, marketing and regulatory guidelines for herbal medicines (phytotherapeutic agents)

Braz. J. Med. Biol. Res.

Systems Toxicology: Integrated genomic, proteomic and metabonomic analysis of methapyrilene induced hepatotoxicity in the rat

J. Proteome Res.

Ultra - performance liquid chromatography - high - definition mass spectrometry analysis of constituents in the root of Radix Stemonae and those absorbed in blood after oral administration of the extract of the crude drug

Phytochem. Anal.

Cholinesterase enzymes inhibitors from the leaves of Rauvolfia reflexa and their molecular docking study

Molecules

Network toxicology and its application to traditional Chinese medicine

Zhonguo Zhong Yi Yao Za Zhi

Multiple receptor-ligand based pharmacophore modeling and molecular docking to screen the selective inhibitors of matrix metalloproteinase-9 from natural products

J. Comput.-Aided Mol. Des.

Challenges, applications, and recent advances of protein-ligand docking in structure-based drug design

Molecules