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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

SPR analysis showed that quercetin, hypaconitine, mesaconitine, higenamine and SND directly bound to TNF-α.(A) The sensorgrams indicate the direct binding of quercetin to TNF-α immobilized on a CM5 sensor chip. The kinetic measurements were performed in triplicate using a set of serial dilutions as shown. (B–E) Standard curves and KD of quercetin, hypaconitine, mesaconitine and higenamine. (F) The sensorgrams indicate the direct binding of SND to TNF-α immobilized on a CM5 sensor chip. The kinetic measurements were performed in triplicate using a set of serial dilutions as shown. Data in (A–F) were representatives of three independent experiments.
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f6: SPR analysis showed that quercetin, hypaconitine, mesaconitine, higenamine and SND directly bound to TNF-α.(A) The sensorgrams indicate the direct binding of quercetin to TNF-α immobilized on a CM5 sensor chip. The kinetic measurements were performed in triplicate using a set of serial dilutions as shown. (B–E) Standard curves and KD of quercetin, hypaconitine, mesaconitine and higenamine. (F) The sensorgrams indicate the direct binding of SND to TNF-α immobilized on a CM5 sensor chip. The kinetic measurements were performed in triplicate using a set of serial dilutions as shown. Data in (A–F) were representatives of three independent experiments.

Mentions: We next investigated whether active components in SND targeted TNF-α with SPR analysis. As shown in Fig. 6F, SND (8.75–140 mg/ml) could bring about a concentration-dependent resonance change when flowing through the sensor chip coated with TNF-α, indicating the direct binding of active components in SND to TNF-α. In addition, hypaconitine, mesaconitine, higenamine and quercetin (6.25–400 μM) also brought about a concentration-dependent resonance change when flowing through the sensor chip coated with TNF-α, indicating the direct binding of hypaconitine, mesaconitine, higenamine and quercetin to TNF-α (Fig. 6). The equilibrium dissociation constant (KD) was calculated to be 53 μM, 57.5 μM, 67 μM and 35 μM. These results are consistent with results of TNF-α–mediated cytotoxicity on L929 cells, which demonstrated that SND, hypaconitine, mesaconitine,higenamine and quercetin are effective small molecule inhibitors of TNF-α. This provided us with a set of leads against TNF-α belonged to diterpenoid alkaloids.


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)

SPR analysis showed that quercetin, hypaconitine, mesaconitine, higenamine and SND directly bound to TNF-α.(A) The sensorgrams indicate the direct binding of quercetin to TNF-α immobilized on a CM5 sensor chip. The kinetic measurements were performed in triplicate using a set of serial dilutions as shown. (B–E) Standard curves and KD of quercetin, hypaconitine, mesaconitine and higenamine. (F) The sensorgrams indicate the direct binding of SND to TNF-α immobilized on a CM5 sensor chip. The kinetic measurements were performed in triplicate using a set of serial dilutions as shown. Data in (A–F) were representatives of three independent experiments.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f6: SPR analysis showed that quercetin, hypaconitine, mesaconitine, higenamine and SND directly bound to TNF-α.(A) The sensorgrams indicate the direct binding of quercetin to TNF-α immobilized on a CM5 sensor chip. The kinetic measurements were performed in triplicate using a set of serial dilutions as shown. (B–E) Standard curves and KD of quercetin, hypaconitine, mesaconitine and higenamine. (F) The sensorgrams indicate the direct binding of SND to TNF-α immobilized on a CM5 sensor chip. The kinetic measurements were performed in triplicate using a set of serial dilutions as shown. Data in (A–F) were representatives of three independent experiments.
Mentions: We next investigated whether active components in SND targeted TNF-α with SPR analysis. As shown in Fig. 6F, SND (8.75–140 mg/ml) could bring about a concentration-dependent resonance change when flowing through the sensor chip coated with TNF-α, indicating the direct binding of active components in SND to TNF-α. In addition, hypaconitine, mesaconitine, higenamine and quercetin (6.25–400 μM) also brought about a concentration-dependent resonance change when flowing through the sensor chip coated with TNF-α, indicating the direct binding of hypaconitine, mesaconitine, higenamine and quercetin to TNF-α (Fig. 6). The equilibrium dissociation constant (KD) was calculated to be 53 μM, 57.5 μM, 67 μM and 35 μM. These results are consistent with results of TNF-α–mediated cytotoxicity on L929 cells, which demonstrated that SND, hypaconitine, mesaconitine,higenamine and quercetin are effective small molecule inhibitors of TNF-α. This provided us with a set of leads against TNF-α belonged to diterpenoid alkaloids.

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