Network pharmacology analysis of Xinbao Pill against heart failure with preserved ejection fraction

Q: What are the key findings of this study?

Xinbao Pill network pharmacology identified 32 active compounds and 11 key HFpEF target genes, with top binding affinities for Withanolide D-VDR (-12.0 kcal/mol) and 12-Deoxywithastramonolide-EPHX2 (-11.5 kcal/mol).

Q: What is the clinical evidence from this study?

Population: Heart failure with preserved ejection fraction (HFpEF) (n=35). Intervention: Xinbao Pill vs. Control group (in transcriptomic datasets). Primary outcome: Identification of candidate active compounds, key intersecting target genes, and molecular docking binding affinities.

Jianmin Shao

doi:10.36721/pjps/2026.40.16875.1

October 6, 2026Pakistan Journal of Pharmaceutical SciencesOpen Access

Network pharmacology analysis of Xinbao Pill against heart failure with preserved ejection fraction

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Key result

Xinbao Pill network pharmacology identifies 32 active compounds and 11 key target genes in HFpEF.

n=35

Why the study?

HFpEF lacks effective targeted therapy, and the molecular mechanisms underlying the potential cardiovascular benefits of traditional Chinese medicine formulas like Xinbao Pill are not yet fully understood.

Key Points

To systematically investigate the multi-compound, multi-target mechanisms of the traditional Chinese medicine Xinbao Pill in treating heart failure with preserved ejection fraction (HFpEF).
Screened active ingredients of Xinbao Pill from the TCMSP and SwissADME databases using predefined pharmacokinetic criteria (oral bioavailability ≥ 30%, drug-likeness ≥ 0.18).
Analyzed three Gene Expression Omnibus datasets (GSE180065, GSE240400, GSE269053) to detect differentially expressed genes (|log2FC| > 0.585, adjusted P < 0.05) and refined overlapping drug-disease targets using Elastic Net regression.
Predicted binding modes using molecular docking and evaluated complex structural stability via 100 ns all-atom molecular dynamics simulations.
Screening identified 32 active compounds and 1,368 HFpEF-related differentially expressed genes, yielding 23 overlapping targets.
Elastic Net regression refined these to 11 key genes: Clk1, Comt, Drd2, Ephx2, Fgr, Hcn2, Mme, Pparg, Ptgds, Slc27a1, and Vdr.
Molecular docking demonstrated top binding affinities for Withanolide D-VDR (-12.0 kcal/mol) and 12-Deoxywithastramonolide-EPHX2 (-11.5 kcal/mol), with 100 ns molecular dynamics simulations confirming structural stability, low RMSD values, and stable free energy minima.

Structured PICO

P

Population

In silico network pharmacology analysis incorporating transcriptomic data from 35 mice across three HFpEF and control RNA-seq datasets (GSE180065, GSE240400, GSE269053).

I

Intervention

Xinbao Pill (a traditional Chinese medicine formulation composed of Panax notoginseng, Datura metel, Panax ginseng, and Borneolum syntheticum), specifically 32 screened active compounds evaluated via network pharmacology, molecular docking, and 100 ns molecular dynamics simulations.

C

Comparator

Control groups in the transcriptomic datasets (mice fed standard diet or receiving null vector, total n=14 across three datasets); native co-crystal ligands used for redocking validation.

O

Outcome

Identification of intersecting HFpEF-related differentially expressed genes (|log2FC| > 0.585 and adjusted P < 0.05) and Xinbao Pill target genes refined by Elastic Net regression, alongside predicted binding affinities (kcal/mol) and 100 ns structural stability (RMSD, RMSF, Rg, free energy landscapes) of compound-target complexes.surrogate

This computational network pharmacology study identifies 32 bioactive compounds in Xinbao Pill and 11 candidate gene targets (notably VDR and EPHX2) that may mediate therapeutic effects in HFpEF, providing a basis for future experimental validation.

Limitations

All analyses are computational and require in-vitro and in-vivo experimental verification.
The three GEO datasets were small and generated from different mouse HFpEF models, increasing the risk of model-specific false positives.
All transcriptomic datasets originated from mouse models, which may limit translation to human HFpEF.
Molecular docking used a rigid-receptor approximation, and molecular dynamics simulations were limited in scope and timescale (100 ns).
In-silico computational study requiring further experimental validation

Implication

Does not support Xinbao Pill use in HFpEF; leaves open experimental validation of identified targets.

Abstract

Background: Heart failure with preserved ejection fraction (HFpEF) accounts for approximately half of all heart failure cases and lacks effective targeted therapy. Traditional Chinese medicine formulas, such as Xinbao Pill, have shown potential cardiovascular benefits; however, their molecular mechanisms are not yet fully understood. Objectives: This study aimed to systematically explore the multi-compound, multi-target mechanism of Xinbao Pill in the treatment of HFpEF using a network pharmacology approach. Methods: Active ingredients of Xinbao Pill were identified from the TCMSP database according to predefined pharmacokinetic criteria. Three GEO datasets (GSE180065, GSE240400 and GSE269053) were analyzed to identify differentially expressed genes associated with HFpEF. Elastic Net regression was used to refine the intersecting targets. Molecular docking and 100 ns all-atom molecular dynamics simulations were used to predict and validate the structural stability of compound-target interactions. Results: A total of 32 active compounds were identified. Differential expression analysis identified 1,368 HFpEF-related genes across the three datasets, including 23 overlapping targets. Elastic Net regression further selected 11 key genes (Clk1, Comt, Drd2, Ephx2, Fgr, Hcn2, Mme, Pparg, Ptgds, Slc27a1, Vdr). Molecular docking predicted strong binding affinities for several compound-target pairs, including Withanolide D-VDR (-12.0 kcal/mol) and 12-Deoxywithastramonolide-EPHX2 (-11.5 kcal/mol). Molecular dynamics simulations confirmed the structural stability of both top-ranked complexes over 100 ns, with low RMSD values and well-defined free energy minima. Conclusions: This in-silico study identified candidate targets and bioactive compounds that may be associated with the potential effects of the Xinbao Pill in HFpEF. The identified key targets and compounds may serve as promising candidates for further experimental validation and therapeutic development.

Discussion

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Cite This Study

Jianmin Shao (2026) studied Heart failure with preserved ejection fraction (HFpEF) (n=35). Xinbao Pill vs. Control group (in transcriptomic datasets) was evaluated on Identification of candidate active compounds, key intersecting target genes, and molecular docking binding affinities. Xinbao Pill network pharmacology identified 32 active compounds and 11 key HFpEF target genes, with top binding affinities for Withanolide D-VDR (-12.0 kcal/mol) and 12-Deoxywithastramonolide-EPHX2 (-11.5 kcal/mol).

synapsesocial.com/papers/6ae28e38cbadf70daf6c40ba https://doi.org/10.36721/pjps/2026.40.16875.1

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Network pharmacology analysis of Xinbao Pill against heart failure with preserved ejection fraction

Key Points

Structured PICO

Limitations

Implication

Abstract

Discussion

Cite This Study

Network pharmacology analysis of Xinbao Pill against heart failure with preserved ejection fraction

Key Points

Structured PICO

Limitations

Implication

Abstract

Discussion

Cite This Study

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