Systems pharmacology in drug development and therapeutic use - A forthcoming paradigm shift

Systems Pharmacology-Based Strategy to Investigate the Mechanism of Ruangan Lidan Decoction for Treatment of Hepatocellular Carcinoma

epatocellular carcinoma (HCC) is one of the leading contributors to cancer mortality worldwide. Currently, the prevention and treatment of HCC remains a major challenge. As a traditional Chinese medicine (TCM) formula, Ruangan Lidan decoction (RGLD) has been proved to own the effect of relieving HCC symptoms. However, due to its biological effects and complex compositions, its underlying mechanism of actions (MOAs) have not been fully clarified yet. In this study, we proposed a pharmacological framework to systematically explore the MOAs of RGLD against HCC. We firstly integrated the active ingredients and potential targets of RGLD. We next highlighted 25 key targets that played vital roles in both RGLD and HCC disease via a protein-protein interaction (PPI) network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Furthermore, an ingredient-target network of RGLD consisting of 216 ingredients with 306 targets was constructed, and multilevel systems pharmacology analyses indicated that RGLD could act on multiple biological processes related to the pathogenesis of HCC, such as cellular response to hypoxia and cell proliferation. Additionally, integrated pathway analysis of RGLD uncovered that RGLD might treat HCC through regulating various pathways, including MAPK signaling pathway, PI3K/Akt signaling pathway, TNF signaling pathway, and ERBB signaling pathway. Survival analysis results showed that HCC patients with low expression of VEGFA, HIF1A, CASP8, and TOP2A were related with a higher survival rate than those with high expression, indicating the potential clinical significance for HCC. Finally, molecular docking results of core ingredients and targets further proved the feasibility of RGLD in the treatment of HCC. Overall, this study indicates that RGLD may treat HCC through multiple mechanisms, which also provides a potential paradigm to investigate the MOAs of TCM prescription.

Exploring the molecular mechanism of action of Polygonum capitatum Buch-Ham. ex D. Don for the treatment of bacterial prostatitis based on network pharmacology and experimental verification

ETHNOPHARMACOLOGY RELEVANCE

Polygonum capitatum Buch-Ham. ex D. Don (CNPC2009), a traditional Miao-national herbal medicine, has been widely used with considerable therapeutic efficacy in the treatment of various urologic disorders including prostatitis. However, the molecular mechanism of action (MOA) remains unclear.

AIM OF THE STUDY

In this study, UPLC-Q-Exactive-MS and Network pharmacological methods were used to explore the underlying molecular MOA of Polygonum capitatum Buch-Ham. Ex D. Don (P.capitatum) for the treatment bacterial prostatitis (BP).

MATERIALS AND METHODS

The UPLC-Q-Exactive-MS technique was used to identify the chemical components of P. capitatum. Databases such as SwissTargetPrediction, Gene Cards, and OMIM were used to predict the targets of P. capitatum for the treatment of BP. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) was used to analyze the protein-protein interaction (PPI) and construct a PPI network, and the Metascape was used for Gene Ontology (GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. In addition, experimental treatment of Escherichia coli (E.coli)-induced BP was verified.

RESULTS

A total of 31 molecular components were identified by UPLC-Q-Exactive-MS. Network pharmacology revealed that P. capitatum may act on the AKT1, PI3K, MTO, EGFR and other targets through active components such as Gallic acid, Quercetin, Luteolin, Protocatechuic Acid, Kaempferol and thereby regulate PI3K-AKT, ErbB, AMPK, HIF-1, and other signaling pathways to intervene in the pathological mechanism of BP. Verification through experimental results showed that compared with the model group, treatment with P. capitatum could significantly inhibit bacterial growth in prostate tissues, lowered the prostate index, down-regulated the levels of inflammatory mediators(IL-1β, IL-6, and TNF-α) in prostate tissues, and down-regulate the protein expression and mRNA expression levels of AKT and PI3K.

CONCLUSION

This study preliminarily revealed the MOA of P. capitatum for treating BP with multiple components, multiple targets, and multiple pathways, especially affecting the PI3K-AKT signaling pathways.

Systems Biology in Periodontitis

Systems biology is a promising scientific discipline that allows an integrated investigation of host factors, microbial composition, biomarkers, immune response and inflammatory mediators in many conditions such as chronic diseases, cancer, neurological disorders, and periodontitis. This concept utilizes genetic decoding, bioinformatic, flux-balance analysis in a comprehensive approach. The aim of this review is to better understand the current literature on systems biology and identify a clear applicability of it to periodontitis. We will mostly focus on the association between this condition and topics such as genomics, transcriptomics, proteomics, metabolomics, as well as contextualize delivery systems for periodontitis treatment, biomarker detection in oral fluids and associated systemic conditions.

A Model-Based Pharmacokinetic/Pharmacodynamic Analysis of the Combination of Amoxicillin and Monophosphoryl Lipid A Against S. pneumoniae in Mice

Combining amoxicillin with the immunostimulatory toll-like receptor 4 agonist monophosphoryl lipid A (MPLA) represents an innovative approach for enhancing antibacterial treatment success. Exploiting pharmacokinetic and pharmacodynamic data from an infection model of Streptococcus pneumoniae infected mice, we aimed to evaluate the preclinical exposure-response relationship of amoxicillin with MPLA coadministration and establish a link to survival. Antibiotic serum concentrations, bacterial numbers in lung and spleen and survival data of mice being untreated or treated with amoxicillin (four dose levels), MPLA, or their combination were analyzed by nonlinear mixed-effects modelling and time-to-event analysis using NONMEM® to characterize these treatment regimens. On top of a pharmacokinetic interaction, regarding the pharmacodynamic effects the combined treatment was superior to both monotherapies: The amoxicillin efficacy at highest dose was increased by a bacterial reduction of 1.74 log10 CFU/lung after 36 h and survival was increased 1.35-fold to 90.3% after 14 days both compared to amoxicillin alone. The developed pharmacometric pharmacokinetic/pharmacodynamic disease-treatment-survival models provided quantitative insights into a novel treatment option against pneumonia revealing a pharmacokinetic interaction and enhanced activity of amoxicillin and the immune system stimulator MPLA in combination. Further development of this drug combination flanked with pharmacometrics towards the clinical setting seems promising.

An Integrated Pharmacology-Based Analysis for Antidepressant Mechanism of Chinese Herbal Formula Xiao-Yao-San

Clinical studies and basic science experiments have widely demonstrated the antidepressant and anxiolytic effects of the herbal formula Xiao-Yao-San (XYS). However, the system mechanism of these effects has not been fully characterized. The present study conducted a comprehensive network pharmacological analysis of XYS and sorted all pharmacologically active components (149) through the TCMSP webserver. Then, all potential molecular targets (449) were predicted, of which there were 99 genes clearly related to depression. To further investigate the mechanism of antidepressant effects of XYS, a compound-depression targets (C-DTs) network was constructed, and Gene Ontology (GO) functional and KEGG pathway enrichment analyses were performed for the 99 targets. Enrichment results revealed that XYS could regulate multiple aspects of depression through these targets, related to metabolism, neuroendocrine function, and neuroimmunity. Prediction and analysis of protein–protein interactions resulted in selection of three hub genes (AKT1, TP53, and VEGFA). In addition, a total of seven ingredients from XYS could act on these hub genes and they were identified through ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS), including paeoniflorin, quercetin, luteolin, acacetin, aloe-emodin, Glyasperin C, kaempferol. Hereafter, we investigated the effects of paeoniflorin and its predicted target, the results suggest that it can reverse the neurotoxicity produced by CORT and could be a neuroprotective effect by promoting the phosphorylation of Akt. Overall, our research revealed the complicated antidepressant mechanism of XYS, and also provided a rational strategy for revealing the complex composition and function of Chinese herbal formula.

Protective Effect and Mechanism of Boswellic Acid and Myrrha Sesquiterpenes with Different Proportions of Compatibility on Neuroinflammation by LPS-Induced BV2 Cells Combined with Network Pharmacology

Frankincense and myrrha (FM), commonly used as a classical herbal pair, have a wide range of clinical applications and definite anti-inflammatory activity. However, anti-neuroinflammation effects and mechanisms are not clear. In this study, we adopted a lipopolysaccharide (LPS)-induced microglial (BV2) cell model and a network pharmacology method to reveal the anti-neuroinflammatory effects and mechanisms of boswellic acid (BA) and myrrha sesquiterpenes (MS) with different proportions of compatibility. The data showed that the different ratios of BA and MS had different degrees of inhibition of interleukin-1β (IL-1β), IL-6, and inducible nitric oxide synthase (iNOS) mRNA expression, down-regulated the phosphor-nuclear factor kappa B/nuclear factor kappa B (p-NF-ҡB)/(NF-ҡB), phosphorylated protein kinase b/protein kinase b (p-AKT/AKT), and Toll-like receptor 4 (TLR4) protein expression levels, and increased phospho-PI3 kinase (p-PI3K) protein expression levels. When the ratios of BA and MS were 10:1, 5:1, and 20:1, better effective efficacy was exhibited. According to the correlation analysis between the effect index and bioactive substances, it was suggested that 2-methoxy-5-acetoxy -fruranogermacr-1(10)-en-6-one (Compound 1), 3α-acetyloxylanosta-8,24-dien-21-oic acid (Compound 2), 11-keto-boswellic acid (Compound 3), and 3-acetyl-11-keto-β -boswellic acid (Compound 4) made important contributions to the treatment of neuroinflammation. Furthermore, based on the network pharmacological analysis, it was found that these four active compounds acted on 31 targets related to neuroinflammation and were involved in 32 signaling pathways which mainly related to the immune system, cardiovascular system, and nervous system, suggesting that BA and MS could be used to treat neuroinflammation.

Exploiting Pharmacokinetic Models of Tamoxifen and Endoxifen to Identify Factors Causing Subtherapeutic Concentrations in Breast Cancer Patients

BACKGROUND AND OBJECTIVES

A better understanding of the highly variable pharmacokinetics (PK) of tamoxifen and its active metabolite endoxifen in breast cancer patients is crucial to support individualised treatment. This study used a modelling and simulation approach to quantitatively assess the influence of cytochrome P450 (CYP) 2D6 activity and other relevant factors on tamoxifen and endoxifen PK to identify subgroups at risk for subtherapeutic endoxifen concentrations.

METHODS

Simulations were performed using two previously published PK models jointly describing tamoxifen and endoxifen with CYP2D6 and CYP3A4/5 enzyme activities implemented as covariates. Steady-state predictions were compared between models and with the literature values. Factors potentially causing between-model discrepancies were explored. A previously published threshold (6 ng/mL) was used to identify patients with subtherapeutic endoxifen concentrations and to perform a dose adaptation study.

RESULTS

Steady-state predictions of tamoxifen and endoxifen were considerably different between the models. The factors, differences in sampling time, adherence and bioavailability, were not able to fully capture between-model variability. Endoxifen steady-state fluctuations within a dosing interval were minimal (<6%). Poor (97%) and intermediate (54%) CYP2D6 metabolisers failed to achieve therapeutic endoxifen concentrations, suggesting adapted doses of tamoxifen 80 and 40 mg, respectively, achieving therapeutic endoxifen concentrations in 89.7% of patients (standard dosing 45.2%). However, interindividual variability remained.

CONCLUSIONS

To achieve therapeutic endoxifen concentrations early in treatment, it is advisable to initiate treatment by CYP2D6 genotype/phenotype-guided dosing, followed by therapeutic drug monitoring at steady-state. We strongly advocate to adequately measure, report and prospectively investigate influential factors (i.e. adherence, bioavailability, time to PK steady-state) in clinical trials.

Network pharmacology exploration reveals the bioactive compounds and molecular mechanisms of Li-Ru-Kang against hyperplasia of mammary gland

Li-Ru-Kang (LRK) has been commonly used in the treatment of hyperplasia of mammary gland (HMG) as a cipher prescription and achieved obvious therapeutic effects. However, the bioactive compounds and underlying pharmacological mechanisms remain unclear. This study aims to decipher the bioactive compounds and potential action mechanisms of LRK in the treatment of HMG using an integrated pharmacology approach. The ingredients of LRK and the corresponding drug targets were retrieved through drug target databases and were used to construct the "compound-target-disease" network and function-pathway network. Ultimately, 89 compounds and 2150 drug targets were collected. Gene ontology enrichment analysis revealed that mammary gland alveolus development and mammary gland lobule development were the key biological processes and were regulated simultaneously by three direct targets, including androgen receptor (AR), estrogen receptor (ER) and cyclin-D1. Moreover, 14 compounds of LRK were directly involved in the regulation of the three aforementioned targets. KEGG pathway enrichment analysis found that five signaling pathways and seven direct targets were closely related with HMG treatment by LRK. The results of animal experiments showed that LRK significantly improved the histopathological status of HMG in rats. Additionally, LRK markedly regulated the protein expressions of AR, cyclin-D1, MMP2, MMP3 and MMP9. But interestingly, the effect of LRK on ER was not obvious. This study demonstrated that LRK exerted its therapeutic efficacy based on multi-components, multi-targets and multi-pathways. This research confirms the advantages of network pharmacology analyses and the necessity for experimental verification.

A rapid, simple and sensitive liquid chromatography tandem mass spectrometry assay to determine amoxicillin concentrations in biological matrix of little volume

To assess pharmacokinetics of amoxicillin (AMX) in mice, limitations such as a small sampling volume and low drug concentrations have to be addressed. Similar challenges are faced in a clinical framework, e.g. for therapeutic drug monitoring in neonates or small-scale in vitro investigations. An assay enabling quantification of small sample volumes but still at very low concentrations covering a broad concentration range is thus needed. A simple, rapid and highly sensitive liquid chromatography tandem mass spectrometry (LC-MS/MS) method was developed and successfully validated for quantification of AMX in mouse serum according to European Medicines Agency guidelines. Sample preparation enabled the use of only 10 μL of serum, which is 5-fold less than comparable assays and allows to reduce the number of mice used in pharmacokinetic studies. After protein precipitation with 40 μL chilled methanol and dilution of the supernatant with water, the sample was injected into the LC system on a Poroshell 120 Phenyl Hexyl column (2.1 × 100 mm, 2.7 μm). Chromatographic separation was achieved using a gradient method consisting of acetonitrile and ultra-pure water, both with 0.1% (V/V) formic acid. Positive electrospray ionisation in multiple reaction monitoring mode was used for detection and quantification of AMX. Application to murine study samples demonstrated the reliability of the developed method being accurate and precise with a quantification range from 0.01 to 10 μg/mL. The assay is easily transferable due to a simple sample preparation and confirmed stability of AMX under various applied conditions.

The Role of Systems Biologic Approach in Cell Signaling and Drug Development Responses-A Mini Review

The immune system is an integral aspect of the human defense system and is primarily responsible for and involved in the communication between the immune cells. It also plays an important role in the protection of the organism from foreign invaders. Recent studies in the literature have described its role in the process of hematopoiesis, lymphocyte recruitment, T cell subset differentiation and inflammation. However, the specific molecular mechanisms underlying these observations remain elusive, impeding the elaborate manipulation of cytokine sequential delivery in tissue repair. Previously, the discovery of new drugs and systems biology went hand in hand; although Systems biology as a term has only originated in the last century. Various new chemicals were tested on the human body, and studied through observation. Animal models replaced humans for initial trials, but the interactions, response, dose and effect between animals and humans could not be directly correlated. Therefore, there is a need to form disease models outside of human subjects to check the effectiveness and response of the newer natural or synthetic chemicals. These emulate human disease conditions wherein the behavior of the chemicals would be similar in the disease model and humans.

Understanding and reducing complex systems pharmacology models based on a novel input-response index

A growing understanding of complex processes in biology has led to large-scale mechanistic models of pharmacologically relevant processes. These models are increasingly used to study the response of the system to a given input or stimulus, e.g., after drug administration. Understanding the input-response relationship, however, is often a challenging task due to the complexity of the interactions between its constituents as well as the size of the models. An approach that quantifies the importance of the different constituents for a given input-output relationship and allows to reduce the dynamics to its essential features is therefore highly desirable. In this article, we present a novel state- and time-dependent quantity called the input-response index that quantifies the importance of state variables for a given input-response relationship at a particular time. It is based on the concept of time-bounded controllability and observability, and defined with respect to a reference dynamics. In application to the brown snake venom-fibrinogen (Fg) network, the input-response indices give insight into the coordinated action of specific coagulation factors and about those factors that contribute only little to the response. We demonstrate how the indices can be used to reduce large-scale models in a two-step procedure: (i) elimination of states whose dynamics have only minor impact on the input-response relationship, and (ii) proper lumping of the remaining (lower order) model. In application to the brown snake venom-fibrinogen network, this resulted in a reduction from 62 to 8 state variables in the first step, and a further reduction to 5 state variables in the second step. We further illustrate that the sequence, in which a recursive algorithm eliminates and/or lumps state variables, has an impact on the final reduced model. The input-response indices are particularly suited to determine an informed sequence, since they are based on the dynamics of the original system. In summary, the novel measure of importance provides a powerful tool for analysing the complex dynamics of large-scale systems and a means for very efficient model order reduction of nonlinear systems.

System Pharmacology-Based Dissection of the Synergistic Mechanism of Huangqi and Huanglian for Diabetes Mellitus

The rapidly increasing diabetes mellitus (DM) is becoming a major global public health issue. Traditional Chinese medicine (TCM) has a long history of the treatment of DM with good efficacy. Huangqi and Huanglian are one of the most frequently prescribed herbs for DM, and the combination of them occurs frequently in antidiabetic formulae. However, the synergistic mechanism of Huangqi (Radix Astragali) and Huanglian (Rhizoma Coptidis) has not been clearly elucidated. To address this problem, a feasible system pharmacology model based on chemical, pharmacokinetic and pharmacological data was developed via network construction approach to clarify the synergistic mechanisms of these two herbs. Forty-three active ingredients of Huangqi (mainly astragalosides and isoflavonoids) and Huanglian (primarily isoquinoline alkaloids) possessing favorable pharmacokinetic profiles and biological activities were selected, interacting with 50 DM-related targets to provide potential synergistic therapeutic actions. Systematic analysis of the constructed networks revealed that these targets such as GLUT2, NOS2, PTP1B, and IGF1R were mainly involved in PI3K-Akt signaling pathway, insulin resistance, insulin signaling pathway, and HIF-1 signaling pathway, and were mainly located in retina, pancreatic islet, smooth muscle, immunity-related organ tissues, and whole blood. The contribution index of every active ingredient also indicated five compounds, including berberine (BBR), astragaloside IV (AIV), quercetin, palmatine, and astragalus polysaccharides, as the principal components of this herb combination. These results successfully explained the polypharmcological and synergistic mechanisms underlying the efficiency of Huangqi and Huanglian for the treatment of DM and its complications.