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Drug target identification using network analysis: Taking active components in Sini decoction as an example.

Chen S, Jiang H, Cao Y, Wang Y, Hu Z, Zhu Z, Chai Y - Sci Rep (2016)

Bottom Line: The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database.Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level.Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects.

View Article: PubMed Central - PubMed

Affiliation: School of Pharmacy, Second Military Medical University, 325 Guohe Road, Shanghai, 200433, China.

ABSTRACT
Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmacology and metabolomics to identify targets of active components in sini decoction (SND) simultaneously against heart failure. To begin with, 48 potential active components in SND against heart failure were predicted by serum pharmacochemistry, text mining and similarity match. Then, we employed network pharmacology including text mining and molecular docking to identify the potential targets of these components. The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database. At last, network analysis was conducted to identify most possible targets of components in SND. Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level. Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects. We envisage that network analysis will also be useful in target identification of a bioactive compound.

No MeSH data available.


Related in: MedlinePlus

Active components in SND inhibited TNF-α-mediated cytotoxicity on L929 cells.L929 cells were treated for 18 h with 10 ng/ml of TNF-α and 1 mg/ml of Actinomycin D (D) in the presence of indicated concentrations of active components. TNF-α-mediated cytotoxicity on L929 cells were measured with CCK8 assay. Data were obtained from three independent experiments performed in triplicate and presented as means (±SD). *p < 0.05 vs. TNF-α (T) only, #p < 0.05 vs. Actinomycin D (D) only. Necrostatin-1 (20 μM) is used as a positive drug.
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f5: Active components in SND inhibited TNF-α-mediated cytotoxicity on L929 cells.L929 cells were treated for 18 h with 10 ng/ml of TNF-α and 1 mg/ml of Actinomycin D (D) in the presence of indicated concentrations of active components. TNF-α-mediated cytotoxicity on L929 cells were measured with CCK8 assay. Data were obtained from three independent experiments performed in triplicate and presented as means (±SD). *p < 0.05 vs. TNF-α (T) only, #p < 0.05 vs. Actinomycin D (D) only. Necrostatin-1 (20 μM) is used as a positive drug.

Mentions: We began our validation of interaction between active components in SND and TNF-α using TNF-α-mediated L929 cytotoxicity assay. Results showed that SND, hypaconitine, mesaconitine, higenamine and quercetin are effective small molecule inhibitors of TNF-α. As shown in Fig. 5, SND inhibits TNF-α-mediated cytotoxicity on L929 cells dose-dependently within the range of 0.39–12.5 mg/ml. In addition, hypaconitine, mesaconitine, higenamine and quercetin inhibit TNF-α-mediated cytotoxicity on L929 cells dose-dependently within the range of 6.75–200 μM. Whereas, aconitine, 6-gingerol and glycyrrhizic acid are not effective small molecule inhibitors of TNF-α.


Drug target identification using network analysis: Taking active components in Sini decoction as an example.

Chen S, Jiang H, Cao Y, Wang Y, Hu Z, Zhu Z, Chai Y - Sci Rep (2016)

Active components in SND inhibited TNF-α-mediated cytotoxicity on L929 cells.L929 cells were treated for 18 h with 10 ng/ml of TNF-α and 1 mg/ml of Actinomycin D (D) in the presence of indicated concentrations of active components. TNF-α-mediated cytotoxicity on L929 cells were measured with CCK8 assay. Data were obtained from three independent experiments performed in triplicate and presented as means (±SD). *p < 0.05 vs. TNF-α (T) only, #p < 0.05 vs. Actinomycin D (D) only. Necrostatin-1 (20 μM) is used as a positive drug.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4837341&req=5

f5: Active components in SND inhibited TNF-α-mediated cytotoxicity on L929 cells.L929 cells were treated for 18 h with 10 ng/ml of TNF-α and 1 mg/ml of Actinomycin D (D) in the presence of indicated concentrations of active components. TNF-α-mediated cytotoxicity on L929 cells were measured with CCK8 assay. Data were obtained from three independent experiments performed in triplicate and presented as means (±SD). *p < 0.05 vs. TNF-α (T) only, #p < 0.05 vs. Actinomycin D (D) only. Necrostatin-1 (20 μM) is used as a positive drug.
Mentions: We began our validation of interaction between active components in SND and TNF-α using TNF-α-mediated L929 cytotoxicity assay. Results showed that SND, hypaconitine, mesaconitine, higenamine and quercetin are effective small molecule inhibitors of TNF-α. As shown in Fig. 5, SND inhibits TNF-α-mediated cytotoxicity on L929 cells dose-dependently within the range of 0.39–12.5 mg/ml. In addition, hypaconitine, mesaconitine, higenamine and quercetin inhibit TNF-α-mediated cytotoxicity on L929 cells dose-dependently within the range of 6.75–200 μM. Whereas, aconitine, 6-gingerol and glycyrrhizic acid are not effective small molecule inhibitors of TNF-α.

Bottom Line: The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database.Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level.Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects.

View Article: PubMed Central - PubMed

Affiliation: School of Pharmacy, Second Military Medical University, 325 Guohe Road, Shanghai, 200433, China.

ABSTRACT
Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmacology and metabolomics to identify targets of active components in sini decoction (SND) simultaneously against heart failure. To begin with, 48 potential active components in SND against heart failure were predicted by serum pharmacochemistry, text mining and similarity match. Then, we employed network pharmacology including text mining and molecular docking to identify the potential targets of these components. The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database. At last, network analysis was conducted to identify most possible targets of components in SND. Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level. Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects. We envisage that network analysis will also be useful in target identification of a bioactive compound.

No MeSH data available.


Related in: MedlinePlus