New strategy for drug discovery by large-scale association analysis of molecular networks of different species

The improvement of modified Si-Miao granule on hepatic insulin resistance and glycogen synthesis in type 2 diabetes mellitus involves the inhibition of TNF-α/JNK1/IRS-2 pathway: network pharmacology, molecular docking, and experimental validation

BACKGROUND

Modified Si-Miao granule (mSMG), a traditional Chinese medicine, is beneficial for T2DM and insulin resistance (IR), but the underlying mechanism remains unknown.

METHODS

Using network pharmacology, we screened the compounds of mSMG and identified its targets and pathway on hepatic IR in T2DM. Using molecular docking, we identified the affinity between the compounds and hub target TNF-α. Then these were verified in KK-Ay mice and HepG2 cells.

RESULTS

50 compounds and 170 targets of mSMG against IR in T2DM were screened, and 9 hub targets such as TNF and MAPK8 were identified. 170 targets were mainly enriched in insulin resistance and TNF pathway, so we speculated that mSMG might act on TNF-α, JNK1 and then regulate insulin signaling to mitigate IR. Experimental validation proved that mSMG ameliorated hyperglycemia, IR, and TNF-α, enhanced glucose consumption and glycogen synthesis, relieved the phosphorylation of JNK1 and IRS-2 (Ser388), and elevated the phosphorylation of Akt (Ser473) and GSK-3β (Ser9) and GLUT2 expression in KK-Ay mice. Molecular docking further showed berberine from mSMG had excellent binding capacity with TNF-α. Then, in vitro validation experiments, we found that 20% mSMG-MS or 50 μM berberine had little effect in IR-HepG2 cell viability, but significantly increased glucose consumption and glycogen synthesis and regulated TNF-α/JNK1/IRS-2 pathway.

CONCLUSION

Network pharmacology and molecular docking help us predict potential mechanism of mSMG and further guide experimental validation. mSMG and its representative compound berberine improve hepatic IR and glycogen synthesis, and its mechanism may be related to the inhibition of TNF-α/JNK1/IRS-2 pathway.

Synthetic lethality theory approaches to effective substance discovery and functional mechanisms elucidation of anti-cancer phytomedicine

BACKGROUND

Longstanding, successful use of combinations of phytopharmaceuticals in traditional Chinese medicine (TCM) has caught the attention of several pharmacologists to natural medicines. However, the development and popularisation of TCM is mainly limited because of the unavailability of reports clarifying the mechanisms of action and pharmacologically active ingredients in such formulations. Previous studies on natural medicines have mostly focused on their dominant components using forward pharmacology which often neglects trace components. It is necessary to assess the pharmacological and therapeutic superiority of many such trace components in comparison with single constituents.

PURPOSE

In this study, we aimed to propose a new pharmacological research strategy for TCM. In particular, we presented the possibility that the effective mechanism of action of trace components of TCM is based on synthetic lethality. We sincerely hope to explore this theory further.

METHOD

We obtained retrieve published research information related to synthetic lethality, phytochemicals and Chinese medicine from PubMed and Google scholar. Based on the inclusion criteria, 71 studies were selected and discussed in this review.

RESULTS

As an interaction among genes, synthetic lethality can amplify co-regulatory biological effects exponentially. Synthetic strategies have been successfully applied for research and development of anti-tumour agents, including poly ADP-ribose polymerase inhibitors and clinical combination of chemotherapeutic agents for efficacy enhancement and toxicity reduction. TCM drugs contain several secondary metabolites to combat environmental stresses, providing a multi-component basis for corresponding synergistic targets. Therefore, we aimed to study whether this method could be used to identify active components present in trace amounts in TCM drugs. Based on a reverse concept of target-component-effect and identified synergistic targets, we explored the mechanisms of action of weakly active components present in trace amounts in TCM drugs to assess combinations of potential synergistic components.

CONCLUSION

This pattern of synthetic lethality not only elucidated the mechanisms of action of TCM drugs from a new perspective but also inspired future studies on discovering naturally occurring active components.

Identification of potential bioactive compounds and mechanisms of GegenQinlian decoction on improving insulin resistance in adipose, liver, and muscle tissue by integrating system pharmacology and bioinformatics analysis

ETHNOPHARMACOLOGICAL RELEVANCE

GegenQinlian Decoction (GQD), a classical formula in traditional Chinese medicine, is widely used in the treatment of diabetes. While studies have demonstrated that GQD is an efficacious treatment for insulin resistance (IR) in type 2 diabetes mellitus (T2DM), the potential bioactive compounds and mechanisms remain unclear.

AIM OF THE STUDY

To further investigate the potential bioactive compounds, targets, and pathways of GQD on improving IR in T2DM for adipose, liver, and muscle tissue using an integrated strategy of system pharmacology and bioinformatics analysis.

MATERIALS AND METHODS

We screened the candidate compounds and targets of GQD and identified IR-associated differentially expressed genes (DEGs) of adipose, liver, and muscle tissue, respectively. Then the intersecting target genes between candidate targets and DEGs were used for "GQD-compounds-targets-tissue" network construction in each type of tissue. The top 10 bioactive compounds acting on each type of tissue were intersected and consequently identified as potential bioactive compounds of GQD. Furthermore, pathway enrichment, protein-protein interaction (PPI) network construction, and hub target identification were performed based on the targets of GQD and the targets of quercetin in each type of tissue, respectively. Finally, to further confirm the role of quercetin, we intersected the hub targets of quercetin and the hub targets of GQD, and the pathways were intersected as well.

RESULTS

132 compounds and 119 potential targets of these compounds were obtained. 1,765, 3,206, and 3594 DEGs were identified between IR and insulin sensitivity (IS) tissue in adipose, liver, and muscle, respectively. There were 21, 23, 45 targets and 103, 73, 123 compounds in the "GQD-compounds-targets-tissue" network of adipose, liver, and muscle tissue, respectively. Then compounds such as quercetin, kaempferol, baicalein, wogonin, isorhamnetin, beta-sitosterol and licochalcone A, were identified as the potential bioactive compounds of GQD, and quercetin had the highest degree among the compounds. Moreover, based on the targets of GQD, hub targets like PPARG, RELA, EGFR, CASP3, VEGFA, AR, ESR1 and CCND1, and signaling pathways such as insulin signaling pathway, endocrine resistance, TNF signaling pathway, PI3K-Akt signaling pathway, AMPK signaling pathway, MAPK signaling pathway, NF-κB signaling pathway, HIF-1 signaling pathway, apoptosis, and VEGF signaling pathway, were filtered out as the underlying mechanisms of GQD on improving diabetic IR. In addition, the hub targets and pathways of quercetin coincided with most of the hub targets and pathways of GQD in each type of tissue, respectively, suggesting that quercetin may be a potential representative compound of GQD.

CONCLUSIONS

Our analysis identifies the potential bioactive compounds, targets, and pathways of GQD on improving IR in T2DM for adipose, liver, and muscle tissue, which shows the characteristics of multi-compounds, multi-targets, multi-pathways, and multi-mechanisms of GQD and lays a solid foundation for further experimental research and clinical application.

Plant Endophytes and Epiphytes: Burgeoning Sources of Known and "Unknown" Cytotoxic and Antibiotic Agents?

In the last 20 or so years, the influence of endophytes and, quite recently, epiphytes of plants upon the compounds found in those plants, which were usually assumed to be phytochemicals produced by the plant for a variety of reasons, often as a defense against predators, is becoming more evident, in particular in the case of antitumor agents originally isolated from plant sources, though antibiotic agents might also be found, particularly from epiphytes. In this review, we started with the first report in 1993 of a taxol-producing endophyte and then expanded the compounds discussed to include camptothecin, the vinca alkaloids, podophyllotoxin, and homoharringtonine from endophytic microbes and then the realization that maytansine is not a plant secondary metabolite at all, and that even such a well-studied plant such as Arabidopsis thaliana has a vast repertoire of potential bioactive agents in its leaf epiphytic bacteria. We have taken data from a variety of sources, including a reasonable history of these discoveries that were not given in recent papers by us, nor in other papers covering this topic. The sources included the Scopus database, but we also performed other searches using bibliographic tools, thus, the majority of the papers referenced are the originals, though we note some very recent papers that have built on previous results. We concluded with a discussion of the more modern techniques that can be utilized to "persuade" endophytes and epiphytes to switch on silent biosynthetic pathways and how current analytical techniques may aid in evaluating such programs. We also comment at times on some findings, particularly in the case of homoharringtonine, where there are repetitious data reports differing by a few years claiming the same endophyte as the producer.

Integration of molecular networking and fingerprint analysis for studying constituents in Microctis Folium

Microctis Folium is the dried leaves of a plant (Microcos paniculata L.) used to improve the digestive system, alleviate diarrhoea, and relieve fever, but information regarding its chemical composition has rarely been reported. The traditional research approach of determining chemical composition has included isolating, purifying, and identifying compounds with high-cost and time-consuming processes. In this study, molecular networking (MN) and fingerprint analysis were integrated as a comprehensive approach to study the chemical composition of Microctis Folium by an ultra fast liquid chromatography-photo diode array detector-triple-time of flight-tandem mass spectrometry (UFLC-DAD-Triple TOF-MS/MS). Large numbers of mass spectrometric data were processed to identify constituents, and the identified compounds and their unknown analogues were comprehensively depicted as visualized figures comprising distinct families by MN. A validated fingerprint methodology was established to quantitatively determine compounds in Microctis Folium. Ultimately, 165 constituents were identified in Microctis Folium for the first time and the identified compounds and approximately five hundred unknown analogues were applied to create visualized figures by MN, indicating compound groups and their chemical structure analogues in Microctis Folium. The validated fingerprint methodology was indicated to be specific, repeatable, precise, and stable and was used to determine 15 batches of samples during three seasons in three districts. Furthermore, seasonal or geographic environmental influences on the chemical profile were estimated by principal coordinate analysis. The results can be used to control the quality of Microctis Folium, observe seasonal or geographic environmental influences on the chemical profiles, and provide a reference for further exploitation of potential active unknown analogues in the future.

Cross-Species Annotation of Expressed Genes and Detection of Different Functional Gene Modules Between 10 Cold- and 10 Hot-Propertied Chinese Herbal Medicines

According to the traditional Chinese medicine (TCM) system, Chinese herbal medicines (HMs) can be divided into four categories: hot, warm, cold, and cool. A cool nature usually is categorized as a cold nature, and a warm nature is classified as a hot nature. However, the detectable characteristics of the gene expression profile associated with the cold and hot properties have not been studied. To address this question, a strategy for the cross-species annotation of conserved genes was established in the present study by using transcriptome data of 20 HMs with cold and hot properties. Functional enrichment analysis was performed on group-specific expressed genes inferred from the functional genome of the reference species (i.e., Arabidopsis). Results showed that metabolic pathways relevant to chrysoeriol, luteolin, paniculatin, and wogonin were enriched for cold-specific genes, and pathways of inositol, heptadecane, lauric acid, octanoic acid, hexadecanoic acid, and pentadecanoic acid were enriched for hot-specific genes. Six functional modules were identified in the HMs with the cold property: nucleotide biosynthetic process, peptidy-L-cysteine S-palmitoylation, lipid modification, base-excision repair, dipeptide transport, and response to endoplasmic reticulum stress. For the hot HMs, another six functional modules were identified: embryonic meristem development, embryonic pattern specification, axis specification, regulation of RNA polymerase II transcriptional preinitiation complex assembly, mitochondrial RNA modification, and cell redox homeostasis. The research provided a new insight into HMs’ cold and hot properties from the perspective of the gene expression profile of plants.

Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives

The discovery of new pharmaceutical drugs is one of the preeminent tasks-scientifically, economically, and socially-in biomedical research. Advances in informatics and computational biology have increased productivity at many stages of the drug discovery pipeline. Nevertheless, drug discovery has slowed, largely due to the reliance on small molecules as the primary source of novel hypotheses. Natural products (such as plant metabolites, animal toxins, and immunological components) comprise a vast and diverse source of bioactive compounds, some of which are supported by thousands of years of traditional medicine, and are largely disjoint from the set of small molecules used commonly for discovery. However, natural products possess unique characteristics that distinguish them from traditional small molecule drug candidates, requiring new methods and approaches for assessing their therapeutic potential. In this review, we investigate a number of state-of-the-art techniques in bioinformatics, cheminformatics, and knowledge engineering for data-driven drug discovery from natural products. We focus on methods that aim to bridge the gap between traditional small-molecule drug candidates and different classes of natural products. We also explore the current informatics knowledge gaps and other barriers that need to be overcome to fully leverage these compounds for drug discovery. Finally, we conclude with a "road map" of research priorities that seeks to realize this goal.

Plant Species Recognition Skills in Finnish Students and Teachers

Limited awareness about nature and its species can have a negative influence on children’s relationship to nature. Plant species recognition and outdoor education are perhaps the easiest way to approach nature relationships and increase knowledge. Unfortunately, it has been shown that people do not recognize plant species very well. This phenomenon is called “plant blindness”. This study presents information about the phenomenon in Finland. The purpose of this research was to determine how well Finnish students from different age groups recognize plant species and which variables explain recognition of plant species in general education in Finland. The subjects were pupils from primary school to university teachers. A total of 754 people took part in the research. The results showed that Finnish pupils do not recognize plant species very well, with wide variations in responses between student levels. Species recognition skills improved from primary school to university teachers.

Screening and analysis of key active constituents in Guanxinshutong capsule using mass spectrum and integrative network pharmacology

Guanxinshutong capsule (GXSTC) is an effective and safe traditional Chinese medicine used in the treatment of cardiovascular diseases (CVDs) for many years. However, the targets of this herbal formula and the underlying molecular mechanisms of action involved in the treatment of CVDs are still unclear. In the present study, we used a systems pharmacology approach to identify the active ingredients of GXSTC and their corresponding targets in the calcium signaling pathway with respect to the treatment of CVDs. This method integrated chromatographic techniques, prediction of absorption, distribution, metabolism, and excretion, analysis using Kyoto Encyclopedia of Genes and Genomes, network construction, and pharmacological experiments. 12 active compounds and 33 targets were found to have a role in the treatment of CVDs, and four main active ingredients, including protocatechuic acid, cryptotanshinone, eugenol, and borneol were selected to verify the effect of (GXSTC) on calcium signaling system in cardiomyocyte injury induced by hypoxia and reoxygenation. The results from the present study revealed the active components and targets of GXSTC in the treatment of CVDs, providing a new perspective to enhance the understanding of the role of the calcium signaling pathway in the therapeutic effect of GXSTC.

Clarifying of the potential mechanism of Sinisan formula for treatment of chronic hepatitis by systems pharmacology method

Chronic hepatitis is a general designation class of diseases, which results in different degrees of liver necrosis and inflammatory reaction, followed by liver fibrosis, may eventually develop into cirrhosis. However, the molecular pathogenesis of chronic hepatitis is too complex to elucidate. Herbal medicines, featured with multiple targets and compounds, have long displayed therapeutic effect in treating chronic hepatitis, though their molecular mechanisms of contribution remain indistinct. This research utilized the network pharmacology to confirm the molecular pathogenesis of chronic hepatitis through providing a comprehensive analysis of active chemicals, drug targets and pathways' interaction of Sinisan formula for treating chronic hepatitis. The outcomes showed that 80 active ingredients of Sinisan formula interacting with 91 therapeutic proteins were authenticated. Sinisan formula potentially participates in immune modulation, anti-inflammatory and antiviral activities, even has regulating effects on lipid metabolism. These mechanisms directly or indirectly are involved in curing chronic hepatitis by an interaction way. The network pharmacology based analysis demonstrated that Sinisan has multi-scale curative activity in regulating chronic hepatitis related biological processes, which provides a new potential way for modern medicine in the treatment of chronic diseases.

Network pharmacological mechanisms of Vernonia anthelmintica (L.) in the treatment of vitiligo: Isorhamnetin induction of melanogenesis via up-regulation of melanin-biosynthetic genes

Background

Vitiligo is a long-term skin disease characterized by the loss of pigment in the skin. The current therapeutic approaches are limited. Although the anti-vitiligo mechanisms of Vernonia anthelmintica (L.) remain ambiguous, the herb has been broadly used in Uyghur hospitals to treat vitiligo. The overall objective of the present study aims to identify the potential lead compounds from Vernonia anthelmintica (L.) in the treatment of vitiligo via an oral route as well as the melanogenic mechanisms in the systematic approaches in silico of admetSAR and substructure-drug-target network-based inference (SDTNBI).

Results

The results showed that the top 5 active compounds with a relatively higher bioavailability that interacted with 23 therapeutic targets were identified in Vernonia anthelmintica (L.) using admetSAR and SDTNBI methods. Among these compounds, Isorhamnetin and Kaempferide, which are methyl-flavonoids, performed 1st and 2nd. Isorhamnetin and Kaempferide significantly increased the expression of melanin-biosynthetic genes (MC1R, MITF, TYR, TYRP1 and DCT) and the tyrosinase activity in B16F10 cells. Isorhamnetin and Kaempferide significantly increased the mRNA-expression of melanin-biosynthetic genes (MC1R, MITF, TYR, TYRP1 and DCT), the protein level of MITF and the tyrosinase activity. Based on the SDTNBI method and experimental verification, Isorhamnetin and Kaempferide effectively increased melanogenesis by targeting the MC1R-MITF signaling pathway, MAPK signaling pathway, PPAR signaling pathway (PPARA, PPARD, PPARG), arachidonic acid metabolism pathway (ALOX12, ALOX15, CBR1) and serotonergic synapses (ALOX12, ALOX15) in the treatment of vitiligo from a network perspective.

Conclusion

We identified the melanogenic activity of the methyl-flavonoids Isorhamnetin and Kaempferide, which were successfully predicted in a network pharmacological analysis of Vernonia anthelmintica (L.) by admetSAR and SDTNBI methods.

Electronic supplementary material

The online version of this article (10.1186/s12918-017-0486-1) contains supplementary material, which is available to authorized users.

Systems Pharmacology-based strategy to screen new adjuvant for hepatitis B vaccine from Traditional Chinese Medicine Ophiocordyceps sinensis

Adjuvants are common component for many vaccines but there are still few licensed for human use due to low efficiency or side effects. The present work adopted Systems Pharmacology analysis as a new strategy to screen adjuvants from traditional Chinese medicine. Ophiocordyceps sinensis has been used for many years in China and other Asian countries with many biological properties, but the pharmacological mechanism has not been fully elucidated. First in this study, 190 putative targets for 17 active compounds in Ophiocordyceps sinensis were retrieved and a systems pharmacology-based approach was applied to provide new insights into the pharmacological actions of the drug. Pathway enrichment analysis found that the targets participated in several immunological processes. Based on this, we selected cordycepin as a target compound to serve as an adjuvant of the hepatitis B vaccine because the existing vaccine often fails to induce an effective immune response in many subjects. Animal and cellular experiments finally validated that the new vaccine simultaneously improves the humoral and cellular immunity of BALB/c mice without side effects. All this results demonstrate that cordycepin could work as adjuvant to hepatitis b vaccine and systems-pharmacology analysis could be used as a new method to select adjuvants.

Predominately Uncultured Microbes as Sources of Bioactive Agents

In this short review, I am discussing the relatively recent awareness of the role of symbionts in plant, marine-invertebrates and fungal areas. It is now quite obvious that in marine-invertebrates, a majority of compounds found are from either as yet unculturable or poorly culturable microbes, and techniques involving “state of the art” genomic analyses and subsequent computerized analyses are required to investigate these interactions. In the plant kingdom evidence is amassing that endophytes (mainly fungal in nature) are heavily involved in secondary metabolite production and that mimicking the microbial interactions of fermentable microbes leads to involvement of previously unrecognized gene clusters (cryptic clusters is one name used), that when activated, produce previously unknown bioactive molecules.

Network motifs modulate druggability of cellular targets

Druggability refers to the capacity of a cellular target to be modulated by a small-molecule drug. To date, druggability is mainly studied by focusing on direct binding interactions between a drug and its target. However, druggability is impacted by cellular networks connected to a drug target. Here, we use computational approaches to reveal basic principles of network motifs that modulate druggability. Through quantitative analysis, we find that inhibiting self-positive feedback loop is a more robust and effective treatment strategy than inhibiting other regulations, and adding direct regulations to a drug-target generally reduces its druggability. The findings are explained through analytical solution of the motifs. Furthermore, we find that a consensus topology of highly druggable motifs consists of a negative feedback loop without any positive feedback loops, and consensus motifs with low druggability have multiple positive direct regulations and positive feedback loops. Based on the discovered principles, we predict potential genetic targets in Escherichia coli that have either high or low druggability based on their network context. Our work establishes the foundation toward identifying and predicting druggable targets based on their network topology.