Computational pharmacological studies on cardiovascular disease by Qishen Yiqi Diwan

QiShenYiQi Pill Improves Myocardial Hypertrophy Caused by Pressure Overload in Rats

Pressure-overloaded myocardial hypertrophy is an independent risk factor for various cardiovascular diseases (CVDs), such as heart failure (HF), arrhythmia, and even sudden death. It is reported that QiShenYiQi pill (QSYQ) is widely used in the treatment of CVDs and can prevent pathological hypertrophy of myocardium, but its specific mechanism is still unclear. In this study, a rat model of myocardial hypertrophy was established through the pressure overload caused by abdominal aortic constriction in Wistar rats. The rats were randomly divided into model group, valsartan group, and QSYQ group, and sham-operated animals served as the control group. At the 4 and 8 weeks of intervention, the general morphology of the heart, myocardial collagen content, collagen volume factor (CVF), collagen type I, collagen type III, myocardial pathological changes, and the expression of ANP, β-MHC, TGF-β1, and CTGF were analyzed, respectively, in order to explore the possible effect of QSYQ on the mechanism of myocardial hypertrophy. We observed that QSYQ could effectively improve myocardial hypertrophy in pressure-overloaded rats, which was related to the regulatory mechanism of TGF-β1 and CTGF.

CVDHD: a cardiovascular disease herbal database for drug discovery and network pharmacology

Background

Cardiovascular disease (CVD) is the leading cause of death and associates with multiple risk factors. Herb medicines have been used to treat CVD long ago in china and several natural products or derivatives (e.g., aspirin and reserpine) are most common drugs all over the world. The objective of this work was to construct a systematic database for drug discovery based on natural products separated from CVD-related medicinal herbs and to research on action mechanism of herb medicines.

Description

The cardiovascular disease herbal database (CVDHD) was designed to be a comprehensive resource for virtual screening and drug discovery from natural products isolated from medicinal herbs for cardiovascular-related diseases. CVDHD comprises 35230 distinct molecules and their identification information (chemical name, CAS registry number, molecular formula, molecular weight, international chemical identifier (InChI) and SMILES), calculated molecular properties (AlogP, number of hydrogen bond acceptor and donors, etc.), docking results between all molecules and 2395 target proteins, cardiovascular-related diseases, pathways and clinical biomarkers. All 3D structures were optimized in the MMFF94 force field and can be freely accessed.

Conclusions

CVDHD integrated medicinal herbs, natural products, CVD-related target proteins, docking results, diseases and clinical biomarkers. By using the methods of virtual screening and network pharmacology, CVDHD will provide a platform to streamline drug/lead discovery from natural products and explore the action mechanism of medicinal herbs. CVDHD is freely available at http://pkuxxj.pku.edu.cn/CVDHD.

Deciphering the combination principles of Traditional Chinese Medicine from a systems pharmacology perspective based on Ma-huang Decoction

ETHNOPHARMACOLOGY RELEVANCE

The main therapeutic concept in Traditional Chinese Medicine (TCM) is herb formula, which treats various diseases via potential herb interactions to maximize the efficacy and minimize the adverse effects. However, the combination principle of herb formula still remains a mystery due to the lack of appropriate methods.

METHODS

A systems pharmacology method integrating the pharmacokinetic analysis, drug targeting, and drug-target-disease network is developed to dissect this rule embedded in the herbal formula. All these are exemplified by a representative TCM formula, Ma-huang decoction, made up of four botanic herbs.

RESULTS

Based on the deep investigation of the function and compatibility of each herb, in a molecular/systems level, we demonstrate the different pharmacological roles that each herb might play in the prescription. By the way of enhancing the bioavailability and/or making the pharmacological synergy among different herbs, the four herbs effectively combine together to be suitable for treating diseases.

CONCLUSIONS

The present work lays foundations for a more comprehensive understanding of the combination rule of TCM, which might also be beneficial to drug development and applications.

Investigation into the mechanism of Eucommia ulmoides Oliv. based on a systems pharmacology approach

ETHNOPHARMACOLOGY RELEVANCE

Though Traditional Chinese Medicine (TCM) has long been playing a significant role in the maintenance of health for people in Asia as well as many other places, the mechanism of its action still remains ambiguous for most of the plants used in TCM, such as Eucommia ulmoides Oliv., a kind of herb that is widely used to help regulate hypertension and the immune system nowadays. However, its functioning mechanism is still unknown. Thus it is necessary to exploit the mechanism of Eucommia ulmoides Oliv.

METHODS

A systems pharmacology approach combining drug-likeness evaluation, oral bioavailability prediction, multiple drug targets prediction as well as network pharmacology techniques has been used.

RESULTS

This comprehensive systematic approach helps successfully to identify 41 candidate compounds contained in Eucommia ulmoides Oliv. while 39 potential targets hit by these ingredients and helps to uncover the synergistic mechanism of action on a systematic level.

CONCLUSIONS

Our work successfully explains the mechanism of the efficiency of Eucommia ulmoides Oliv. for the treatment of hypertension and enhancing immune. These results not only provide a new insight for the understanding of the chemical and pharmacological basis of Eucommia ulmoides Oliv., but also provide an efficient way for drug discovery from herbal medicine.

Computational pharmacological comparison of Salvia miltiorrhiza and Panax notoginseng used in the therapy of cardiovascular diseases

The herb pair comprising Salvia miltiorrhiza (SM) and Panax notoginseng (PN) has been used as a classical formula for cardiovascular diseases (CVDs) in China and in western countries. However, the pharmacology of SM and PN in this herb pair has not been fully elucidated. The aim of this study was to compare the mechanisms of SM and PN at the molecular level for the treatment of CVDs. We used a systems pharmacology approach, integrating ligand clustering, chemical space, docking simulation and network analysis, to investigate these two herbal medicines. The compounds in SM were attached to clusters 2, 3, 5, 6, 8 and 9, while the compounds in PN were attached to clusters 1, 2, 4, 5, 6, 7, 8 and 10. The distributions of chemical space between the compounds from SM and PN were discrete, with the existence of small portions of overlap, and the majority of the compounds did not violate 'Lipinski's rule of five'. Docking indicated that the average number of targets correlated with each compound in SM and PN were 5.0 and 3.6, respectively. The minority nodes in the SM and PN drug-target networks possessed common values of betweenness centrality, closeness centrality, topological coefficients and shortest path length. Furthermore, network analyses revealed that SM and PN exerted different modes of action between compounds and targets. These results suggest that the method of computational pharmacology is able to intuitively trace out the similarities and differences of two herbs and their interaction with targets from the molecular level, and that the combination of two herbs may extend their activities in different potential multidrug combination therapies for CVDs.

Drug-target network and polypharmacology studies of a Traditional Chinese Medicine for type II diabetes mellitus

Many Traditional Chinese Medicines (TCMs) are effective to relieve complicated diseases such as type II diabetes mellitus (T2DM). In this work, molecular docking and network analysis were employed to elucidate the action mechanism of a medical composition which had clinical efficacy for T2DM. We found that multiple active compounds contained in this medical composition would target multiple proteins related to T2DM and the biological network would be shifted. We predicted the key players in the medical composition and some of them have been reported in literature. Meanwhile, several compounds such as Rheidin A, Rheidin C, Sennoside C, procyanidin C1 and Dihydrobaicalin were notable although no one have reported their pharmacological activity against T2DM. The association between active compounds, target proteins and other diseases was also discussed.