Expanding potential targets of herbal chemicals by node2vec based on herb-drug interactions.

BACKGROUND: The identification of chemical-target interaction is key to pharmaceutical research and development, but the unclear materials basis and complex mechanisms of traditional medicine (TM) make it difficult, especially for low-content chemicals which are hard to test in experiments. In this research, we aim to apply the node2vec algorithm in the context of drug-herb interactions for expanding potential targets and taking advantage of molecular docking and experiments for verification. METHODS: Regarding the widely reported risks between cardiovascular drugs and herbs, Salvia miltiorrhiza (Danshen, DS) and Ligusticum chuanxiong (Chuanxiong, CX), which are widely used in the treatment of cardiovascular disease (CVD), and approved drugs for CVD form the new dataset as an example. Three data groups DS-drug, CX-drug, and DS-CX-drug were applied to serve as the context of drug-herb interactions for link prediction. Three types of datasets were set under three groups, containing information from chemical-target connection (CTC), chemical-chemical connection (CCC) and protein-protein interaction (PPI) in increasing steps. Five algorithms, including node2vec, were applied as comparisons. Molecular docking and pharmacological experiments were used for verification. RESULTS: Node2vec represented the best performance with average AUROC and AP values of 0.91 on the datasets "CTC, CCC, PPI". Targets of 32 herbal chemicals were identified within 43 predicted edges of herbal chemicals and drug targets. Among them, 11 potential chemical-drug target interactions showed better binding affinity by molecular docking. Further pharmacological experiments indicated caffeic acid increased the thermal stability of the protein GGT1 and ligustilide and low-content chemical neocryptotanshinone induced mRNA change of FGF2 and MTNR1A, respectively. CONCLUSIONS: The analytical framework and methods established in the study provide an important reference for researchers in discovering herb-drug interactions, alerting clinical risks, and understanding complex mechanisms of TM.

Leocarpinolide B Attenuates Collagen Type II-Induced Arthritis by Inhibiting DNA Binding Activity of NF-κB.

Rheumatoid arthritis (RA) is a chronic autoimmune disease triggered by a cascading inflammatory response. Sigesbeckia Herba (SH) has long been utilized as a traditional remedy to alleviate symptoms associated with rheumatism. Our previous study found that leocarpinolide B (LB), a sesquiterpene lactone isolated from the whole plant of SH, possesses potent a anti-inflammatory effect on macrophages. This study was designed to evaluate the therapeutic effects of LB on RA, and further investigate the underlying mechanisms. In collagen type II-induced arthritic mice, LB was demonstrated to decrease the production of autoimmune antibodies in serum and inflammatory cytokines in the joint muscles and recover the decreased regulatory T lymphocytes in spleen. Moreover, LB significantly suppressed the inflammatory infiltration, formation of pannus and bone erosion in the paw joints. In vitro testing showed that LB inhibited the proliferation, migration, invasion, and secretion of inflammatory cytokines in IL-1ß-induced human synovial SW982 cells. Network pharmacology and molecular docking suggested NF-κB p65 could be the potential target of LB on RA treatment, subsequent experimental investigation confirmed that LB directly interacted with NF-κB p65 and reduced the DNA binding activity of NF-κB in synovial cells. In conclusion, LB significantly attenuated the collagen type II-induced arthritis, which was at least involved in the inhibition of DNA binding activity of NF-κB through a direct binding to NF-κB p65. These findings suggest that LB could be a valuable lead compound for developing anti-RA drugs.

A network pharmacology-based study on the quality control markers of antithrombotic herbs: Using Salvia miltiorrhiza - Ligusticum chuanxiong as an example.

ETHNOPHARMACOLOGICAL RELEVANCE: Salvia miltiorrhiza (Danshen, DS), the dried root and rhizome of Salvia miltiorrhiza Bunge and Ligusticum chuanxiong (Chuanxiong, CX), the dried rhizomes of Ligusticum striatum DC are effective in invigorating blood circulation and eliminating stasis which is highly related with cardiovascular disease (CVD). AIM OF STUDY: The identification of activity-based chemical markers is very important, but the complex mechanism of "multi-component, multi-target, and multi-effect" within traditional Chinese medicine (TCM) poses a great challenge to this work. In this study, we combined network pharmacological prediction with experimental validation of the DS and CX to explore an effective method for discovering quality control (QC) of antithrombotic herbs by clarifying the intermediate layer "module/cluster" between the whole complex system and a single component. MATERIALS AND METHODS: Based on structural similarity analysis of compound and the thrombosis network published before, we firstly modularized two layers called chemical cluster (CC) network and functional module (FM) network respectively and linked them into one bilayer modularized compound target (BMCT) network. "Two-step" calculation was applied on identifying the significant compounds as the potential QC markers from CC. The in vitro inhibitory activity of selected QC marker compounds on thrombin was evaluated to partially verify their pharmacological activities. HPLC was used to determine contents. RESULTS: According to the network-based analysis, nine compounds with great importance in the BMCT network were identified as QC markers of DS-CX, including tanshinone I, tanshinone IIA, cryptotanshinone, salvianolic acid B, ferulic acid, salvianolic acid A, rosmarinic acid, chlorogenic acid, and coniferyl ferulate. Enzyme inhibitory test partially verified the activity of tanshinone I and tanshinone IIA. Chemical profiling indicated that the nine marker compounds are the main components in the herbal pair. CONCLUSIONS: This study identified activity-based QC markers of DS-CX herbal pair and provided a new methodology that can be used in the QC of other herbs, herbal pairs, or formulas.

Rapid Screening of Lipase Inhibitors from Ophiopogonis Radix Using High-Performance Thin Layer Chromatography by Two Step Gradient Elution Combined with Bioautographic Method.

In this study, a high-performance thin layer chromatography (HPTLC) method by two step gradient elution with two mobile phases was developed for the simultaneous analysis of seven constituents in Ophiopogonis Radix. The chromatography was performed on silica gel 60 F254 plate with dichloromethane-methanol-ethyl acetate-water (70:25:12:3, v/v/v/v) and dichloromethane-methanol (300:1, v/v) as the mobile phase for two step gradient elution. Then, the HPTLC profiles were observed after derivatization with 10% sulfuric acid in ethanol solution. The obtained HPTLC images were further analyzed by chemometric approaches and the samples could be clustered based on regions and/or growth years, which were two important factors affecting the constituents in Ophiopogonis Radix. Furthermore, five compounds including ophiopogonin D, ophiopojaponin C, ophiopogonin D', ophiopogonin C' and methylophiopogonanone B were screened as potential lipase inhibitors from Ophiopogonis Radix by the HPTLC-bioautographic method. The binding modes and interactions between the five compounds and lipase were further explored by molecular docking analysis. The developed HPTLC method could be used for quality control of Ophiopogonis Radix and screening of the potential lipase inhibitors.

[Traditional Chinese medicine network pharmacology: development in new era under guidance of network pharmacology evaluation method guidance].

Traditional Chinese medicine(TCM) has unique advantages in the prevention and treatment of diseases owing to its holistic view and more than 2 000 years of experience in the clinical use of natural medicine. The "holistic" characteristic of TCM gives birth to a new generation of research paradigm featuring "network" and "system", which has been developing rapidly in the era of biomedical big data and artificial intelligence. Network pharmacology, a representative research field, provides new ideas and methods for the research of the interdiscipline of artificial intelligence and medicine, the analysis of massive biomedical data, and the transformation from data to knowledge. TCM plays an important role in proposing the core theory of "network target" and promoting the establishment and development of network pharmacology, and has taken the lead in formulating the first international standard of network pharmacology--Network Pharmacology Evaluation Method Guidance. In terms of theory, network target can systematically link drugs and diseases and quantitatively interpret the overall regulatory mechanism of drugs. In the aspect of method, network pharmacology is developing towards a research model that combines computational, experimental, and clinical approaches. This review introduces the resent important progress of TCM network pharmacology in predicting drug targets, understanding the biological basis of drugs and diseases, and searching for disease and syndrome biomarkers. Under the guidance of Network Pharmacology Evaluation Method Guidance, the development of network pharmacology is expected to become more and more standardized and healthy. Network target will help produce more high-quality research outcomes in TCM and effectively boost the modernization and internationalization of TCM.

Screening of Potential Thrombin and Factor Xa Inhibitors from the Danshen-Chuanxiong Herbal Pair through a Spectrum-Effect Relationship Analysis.

In this study; a spectrum-effect relationship analysis combined with a high-performance liquid chromatography-mass spectrometry (LC-MS) analysis was established to screen and identify active components that can inhibit thrombin and factor Xa (THR and FXa) in Salviae Miltiorrhizae Radix et Rhizoma-Chuanxiong Rhizoma (Danshen-Chuanxiong) herbal pair. Ten potential active compounds were predicted through a canonical correlation analysis (CCA), and eight of them were tentatively identified through an LC-MS analysis. Furthermore; the enzyme inhibitory activity of six available compounds; chlorogenic acid; Z-ligustilide; caffeic acid; ferulic acid; tanshinone I and tanshinone IIA; were tested to verify the feasibility of the method. Among them; chlorogenic acid was validated to possess a good THR inhibitory activity with IC50 of 185.08 µM. Tanshinone I and tanshinone IIA are potential FXa inhibitors with IC50 of 112.59 µM and 138.19 µM; respectively. Meanwhile; molecular docking results show that tanshinone I and tanshinone IIA; which both have binding energies of less than -7.0 kcal·mol-1; can interact with FXa by forming H-bonds with residues of SER214; GLY219 and GLN192. In short; the THR and FXa inhibitors in the Danshen-Chuanxiong herbal pair have been successfully characterized through a spectrum-effect relationship analysis and an LC-MS analysis.