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Screening Ingredients from Herbs against Pregnane X Receptor in the Study of Inductive Herb-Drug Interactions: Combining Pharmacophore and Docking-Based Rank Aggregation.

Cui Z, Kang H, Tang K, Liu Q, Cao Z, Zhu R - Biomed Res Int (2015)

Bottom Line: Secondly, DRA was used to rerank the result of pharmacophore filtering.The accuracy of our method is higher than other traditional methods.The strategy could be extended to studies on other inductive herb-drug interactions.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioinformatics, Tongji University, Shanghai 200092, China.

ABSTRACT
The issue of herb-drug interactions has been widely reported. Herbal ingredients can activate nuclear receptors and further induce the gene expression alteration of drug-metabolizing enzyme and/or transporter. Therefore, the herb-drug interaction will happen when the herbs and drugs are coadministered. This kind of interaction is called inductive herb-drug interactions. Pregnane X Receptor (PXR) and drug-metabolizing target genes are involved in most of inductive herb-drug interactions. To predict this kind of herb-drug interaction, the protocol could be simplified to only screen agonists of PXR from herbs because the relations of drugs with their metabolizing enzymes are well studied. Here, a combinational in silico strategy of pharmacophore modelling and docking-based rank aggregation (DRA) was employed to identify PXR's agonists. Firstly, 305 ingredients were screened out from 820 ingredients as candidate agonists of PXR with our pharmacophore model. Secondly, DRA was used to rerank the result of pharmacophore filtering. To validate our prediction, a curated herb-drug interaction database was built, which recorded 380 herb-drug interactions. Finally, among the top 10 herb ingredients from the ranking list, 6 ingredients were reported to involve in herb-drug interactions. The accuracy of our method is higher than other traditional methods. The strategy could be extended to studies on other inductive herb-drug interactions.

No MeSH data available.


Related in: MedlinePlus

The detection rate in different ranking lists obtained by four methods.
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Related In: Results  -  Collection


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fig4: The detection rate in different ranking lists obtained by four methods.

Mentions: As validity of methodology, the performance of our method was compared with traditional methods. We predict the inductive herb-drug interactions through screening agonist of PXR. Because candidate agonists screened by us are a ranking list, three methods for screening ligand of protein were chosen to compare, such as molecular docking, Partial Least Squares- (PLS-) based QSAR, Principal Component Regression- (PCR-) based QSAR. Likewise, 820 herbal ingredients are screened by different methods. As shown in Figure 4, the detection rate of our method (SELF) is higher than any other methods in different top percent of ranking. Our method indeed improves the performance of predicting herb-drug interactions. The result of ranking lists was shown in Supplementary Table S3.


Screening Ingredients from Herbs against Pregnane X Receptor in the Study of Inductive Herb-Drug Interactions: Combining Pharmacophore and Docking-Based Rank Aggregation.

Cui Z, Kang H, Tang K, Liu Q, Cao Z, Zhu R - Biomed Res Int (2015)

The detection rate in different ranking lists obtained by four methods.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4538340&req=5

fig4: The detection rate in different ranking lists obtained by four methods.
Mentions: As validity of methodology, the performance of our method was compared with traditional methods. We predict the inductive herb-drug interactions through screening agonist of PXR. Because candidate agonists screened by us are a ranking list, three methods for screening ligand of protein were chosen to compare, such as molecular docking, Partial Least Squares- (PLS-) based QSAR, Principal Component Regression- (PCR-) based QSAR. Likewise, 820 herbal ingredients are screened by different methods. As shown in Figure 4, the detection rate of our method (SELF) is higher than any other methods in different top percent of ranking. Our method indeed improves the performance of predicting herb-drug interactions. The result of ranking lists was shown in Supplementary Table S3.

Bottom Line: Secondly, DRA was used to rerank the result of pharmacophore filtering.The accuracy of our method is higher than other traditional methods.The strategy could be extended to studies on other inductive herb-drug interactions.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioinformatics, Tongji University, Shanghai 200092, China.

ABSTRACT
The issue of herb-drug interactions has been widely reported. Herbal ingredients can activate nuclear receptors and further induce the gene expression alteration of drug-metabolizing enzyme and/or transporter. Therefore, the herb-drug interaction will happen when the herbs and drugs are coadministered. This kind of interaction is called inductive herb-drug interactions. Pregnane X Receptor (PXR) and drug-metabolizing target genes are involved in most of inductive herb-drug interactions. To predict this kind of herb-drug interaction, the protocol could be simplified to only screen agonists of PXR from herbs because the relations of drugs with their metabolizing enzymes are well studied. Here, a combinational in silico strategy of pharmacophore modelling and docking-based rank aggregation (DRA) was employed to identify PXR's agonists. Firstly, 305 ingredients were screened out from 820 ingredients as candidate agonists of PXR with our pharmacophore model. Secondly, DRA was used to rerank the result of pharmacophore filtering. To validate our prediction, a curated herb-drug interaction database was built, which recorded 380 herb-drug interactions. Finally, among the top 10 herb ingredients from the ranking list, 6 ingredients were reported to involve in herb-drug interactions. The accuracy of our method is higher than other traditional methods. The strategy could be extended to studies on other inductive herb-drug interactions.

No MeSH data available.


Related in: MedlinePlus