Xuetong Chen

Large-scale exploration and analysis of drug combinations

MOTIVATION Drug combinations are a promising strategy for combating complex diseases by improving the efficacy and reducing corresponding side effects. Currently, a widely studied problem in pharmacology is to predict effective drug combinations, either through empirically screening in clinic or pure experimental trials. However, the large-scale prediction of drug combination by a systems method is rarely considered. RESULTS We report a systems pharmacology framework to predict drug combinations (PreDCs) on a computational model, termed probability ensemble approach (PEA), for analysis of both the efficacy and adverse effects of drug combinations. First, a Bayesian network integrating with a similarity algorithm is developed to model the combinations from drug molecular and pharmacological phenotypes, and the predictions are then assessed with both clinical efficacy and adverse effects. It is illustrated that PEA can predict the combination efficacy of drugs spanning different therapeutic classes with high specificity and sensitivity (AUC = 0.90), which was further validated by independent data or new experimental assays. PEA also evaluates the adverse effects (AUC = 0.95) quantitatively and detects the therapeutic indications for drug combinations. Finally, the PreDC database includes 1571 known and 3269 predicted optimal combinations as well as their potential side effects and therapeutic indications. AVAILABILITY AND IMPLEMENTATION The PreDC database is available at http://sm.nwsuaf.edu.cn/lsp/predc.php.

Large-scale Direct Targeting for Drug Repositioning and Discovery

A system-level identification of drug-target direct interactions is vital to drug repositioning and discovery. However, the biological means on a large scale remains challenging and expensive even nowadays. The available computational models mainly focus on predicting indirect interactions or direct interactions on a small scale. To address these problems, in this work, a novel algorithm termed weighted ensemble similarity (WES) has been developed to identify drug direct targets based on a large-scale of 98,327 drug-target relationships. WES includes: (1) identifying the key ligand structural features that are highly-related to the pharmacological properties in a framework of ensemble; (2) determining a drug’s affiliation of a target by evaluation of the overall similarity (ensemble) rather than a single ligand judgment; and (3) integrating the standardized ensemble similarities (Z score) by Bayesian network and multi-variate kernel approach to make predictions. All these lead WES to predict drug direct targets with external and experimental test accuracies of 70% and 71%, respectively. This shows that the WES method provides a potential in silico model for drug repositioning and discovery.

Systems Pharmacology Dissection of Multi-Scale Mechanisms of Action for Herbal Medicines in Stroke Treatment and Prevention

Annually, tens of millions of first-ever strokes occur in the world; however, currently there is lack of effective and widely applicable pharmacological treatments for stroke patients. Herbal medicines, characterized as multi-constituent, multi-target and multi-effect, have been acknowledged with conspicuous effects in treating stroke, and attract extensive interest of researchers although the mechanism of action is yet unclear. In this work, we introduce an innovative systems-pharmacology method that combines pharmacokinetic prescreening, target fishing and network analysis to decipher the mechanisms of action of 10 herbal medicines like Salvia miltiorrhizae, Ginkgo biloba and Ephedrae herba which are efficient in stroke treatment and prevention. Our systematic analysis results display that, in these anti-stroke herbal medicines, 168 out of 1285 constituents with the favorable pharmacokinetic profiles might be implicated in stroke therapy, and the systematic use of these compounds probably acts through multiple mechanisms to synergistically benefit patients with stroke, which can roughly be classified as preventing ischemic inflammatory response, scavenging free radicals and inhibiting neuronal apoptosis against ischemic cerebral damage, as well as exhibiting lipid-lowering, anti-diabetic, anti-thrombotic and antiplatelet effects to decrease recurrent strokes. Relying on systems biology-based analysis, we speculate that herbal medicines, being characterized as the classical combination therapies, might be not only engaged in multiple mechanisms of action to synergistically improve the stroke outcomes, but also might be participated in reducing the risk factors for recurrent strokes.

Systems-Pharmacology Dissection of Traditional Chinese Medicine Compound Saffron Formula Reveals Multi-scale Treatment Strategy for Cardiovascular Diseases.

Cardiovascular diseases (CVDs) have been regarding as “the world’s first killer” of human beings in recent years owing to the striking morbidity and mortality, the involved molecular mechanisms are extremely complex and remain unclear. Traditional Chinese medicine (TCM) adheres to the aim of combating complex diseases from an integrative and holistic point of view, which has shown effectiveness in CVDs therapy. However, system-level understanding of such a mechanism of multi-scale treatment strategy for CVDs is still difficult. Here, we developed a system pharmacology approach with the purpose of revealing the underlying molecular mechanisms exemplified by a famous compound saffron formula (CSF) in treating CVDs. First, by systems ADME analysis combined with drug targeting process, 103 potential active components and their corresponding 219 direct targets were retrieved and some key interactions were further experimentally validated. Based on this, the network relationships among active components, targets and diseases were further built to uncover the pharmacological actions of the drug. Finally, a “CVDs pathway” consisted of several regulatory modules was incorporated to dissect the therapeutic effects of CSF in different pathological features-relevant biological processes. All this demonstrates CSF has multi-scale curative activity in regulating CVD-related biological processes, which provides a new potential way for modern medicine in the treatment of complex diseases.

Pathway as a Pharmacological Target for Herbal Medicines: An Investigation from Reduning Injection

As a rich natural resource for drug discovery, Traditional Chinese Medicine (TCM) plays an important role in complementary and alternative medical systems. TCM shows a daunting complexity of compounds featuring multi-components and multi-targets to cure diseases, which thus always makes it extremely difficult to systematically explain the molecular mechanisms adequately using routine methods. In the present work, to reveal the systematic mechanism of herbal formulae, we developed a pathway-based strategy by combining the pathways integrating, target selection, reverse drug targeting and network analysis together, and then exemplified it by Reduning injection (RDN), a clinically widely used herbal medicine injection, in combating inflammation. The anti-inflammatory effects exerted by the major ingredients of RDN at signaling pathways level were systematically investigated. More importantly, our predicted results were also experimentally validated. Our strategy provides a deep understanding of the pharmacological functions of herbal formulae from molecular to systematic level, which may lead to more successful applications of systems pharmacology for drug discovery and development.

Systems Pharmacology Dissecting Holistic Medicine for Treatment of Complex Diseases: An Example Using Cardiocerebrovascular Diseases Treated by TCM

Holistic medicine is an interdisciplinary field of study that integrates all types of biological information (protein, small molecules, tissues, organs, external environmental signals, etc.) to lead to predictive and actionable models for health care and disease treatment. Despite the global and integrative character of this discipline, a comprehensive picture of holistic medicine for the treatment of complex diseases is still lacking. In this study, we develop a novel systems pharmacology approach to dissect holistic medicine in treating cardiocerebrovascular diseases (CCDs) by TCM (traditional Chinese medicine). Firstly, by applying the TCM active ingredients screened out by a systems-ADME process, we explored and experimentalized the signed drug-target interactions for revealing the pharmacological actions of drugs at a molecule level. Then, at a/an tissue/organ level, the drug therapeutic mechanisms were further investigated by a target-organ location method. Finally, a translational integrating pathway approach was applied to extract the diseases-therapeutic modules for understanding the complex disease and its therapy at systems level. For the first time, the feature of the drug-target-pathway-organ-cooperations for treatment of multiple organ diseases in holistic medicine was revealed, facilitating the development of novel treatment paradigm for complex diseases in the future.

Systems Pharmacology Dissection of the Integrated Treatment for Cardiovascular and Gastrointestinal Disorders by Traditional Chinese Medicine

Though cardiovascular diseases (CVDs) and gastrointestinal disorders (GIDs) are different diseases associated with different organs, they are highly correlated clinically. Importantly, in Traditional Chinese Medicine (TCM), similar treatment strategies have been applied in both diseases. However, the etiological mechanisms underlying them remain unclear. Here, an integrated systems pharmacology approach is presented for illustrating the molecular correlations between CVDs and GIDs. Firstly, we identified pairs of genes that are associated with CVDs and GIDs and found that these genes are functionally related. Then, the association between 115 heart meridian (HM) herbs and 163 stomach meridian (SM) herbs and their combination application in Chinese patent medicine was investigated, implying that both CVDs and GIDs can be treated by the same strategy. Exemplified by a classical formula Sanhe Decoration (SHD) treating chronic gastritis, we applied systems-based analysis to introduce a drug-target-pathway-organ network that clarifies mechanisms of different diseases being treated by the same strategy. The results indicate that SHD regulated several pathological processes involved in both CVDs and GIDs. We experimentally confirmed the predictions implied by the effect of SHD for myocardial ischemia. The systems pharmacology suggests a novel integrated strategy for rational drug development for complex associated diseases.

Systems Pharmacology Uncovers the Multiple Mechanisms of Xijiao Dihuang Decoction for the Treatment of Viral Hemorrhagic Fever

Background. Viral hemorrhagic fevers (VHF) are a group of systemic diseases characterized by fever and bleeding, which have posed a formidable potential threat to public health with high morbidity and mortality. Traditional Chinese Medicine (TCM) formulas have been acknowledged with striking effects in treatment of hemorrhagic fever syndromes in Chinas history. Nevertheless, their accurate mechanisms of action are still confusing. Objective. To systematically dissect the mechanisms of action of Chinese medicinal formula Xijiao Dihuang (XJDH) decoction as an effective treatment for VHF. Methods. In this study, a systems pharmacology method integrating absorption, distribution, metabolism, and excretion (ADME) screening, drug targeting, network, and pathway analysis was developed. Results. 23 active compounds of XJDH were obtained and 118 VHF-related targets were identified to have interactions with them. Moreover, systematic analysis of drug-target network and the integrated VHF pathway indicate that XJDH probably acts through multiple mechanisms to benefit VHF patients, which can be classified as boosting immune system, restraining inflammatory responses, repairing the vascular system, and blocking virus spread. Conclusions. The integrated systems pharmacology method provides precise probe to illuminate the molecular mechanisms of XJDH for VHF, which will also facilitate the application of traditional medicine in modern medicine.

A novel systems pharmacology platform to dissect action mechanisms of traditional Chinese medicines for bovine viral diarrhea disease

Due to the large direct and indirect productivity losses in the livestock industry caused by bovine viral diarrhea (BVD) and the lack of effective pharmacological therapies, developing an efficient treatment is extremely urgent. Traditional Chinese medicines (TCMs) that simultaneously address multiple targets have been proven to be effective therapies for BVD. However, the potential molecular action mechanisms of TCMs have not yet been systematically explored. In this work, take the example of a herbal remedy Huangqin Zhizi (HQZZ) for BVD treatment in China, a systems pharmacology approach combining with the pharmacokinetics and pharmacodynamics evaluation was developed to screen out the active ingredients, predict the targets and analyze the networks and pathways. Results show that 212 active compounds were identified. Utilizing these lead compounds as probes, we predicted 122 BVD related-targets. And in vitro experiments were conducted to evaluate the reliability of some vital active compounds and targets. Network and pathway analysis displayed that HQZZ was effective in the treatment of BVD by inhibiting inflammation, enhancing immune responses in hosts toward virus infection. In summary, the analysis of the complete profile of the pharmacological activities, as well as the elucidation of targets, networks and pathways can further elucidate the underlying anti-inflammatory, antiviral and immune regulation mechanisms of HQZZ against BVD.

Insights from systems pharmacology into cardiovascular drug discovery and therapy.

BackgroundGiven the complex nature of cardiovascular disease (CVD), information derived from a systems-level will allow us to fully interrogate features of CVD to better understand disease pathogenesis and to identify new drug targets.ResultsHere, we describe a systematic assessment of the multi-layer interactions underlying cardiovascular drugs, targets, genes and disorders to reveal comprehensive insights into cardiovascular systems biology and pharmacology. We have identified 206 effect-mediating drug targets, which are modulated by 254 unique drugs, of which, 43% display activities across different protein families (sequence similarity < 30%), highlighting the fact that multitarget therapy is suitable for CVD. Although there is little overlap between cardiovascular protein targets and disease genes, the two groups have similar pleiotropy and intimate relationships in the human disease gene-gene and cellular networks, supporting their similar characteristics in disease development and response to therapy. We also characterize the relationships between different cardiovascular disorders, which reveal that they share more etiological commonalities with each other rooted in the global disease-disease networks. Furthermore, the disease modular analysis demonstrates apparent molecular connection between 227 cardiovascular disease pairs.ConclusionsAll these provide important consensus as to the cause, prevention, and treatment of various CVD disorders from systems-level perspective.