Evidence map›Paper›PMID 27833111›Full record

ArticleScientific reports2016

Herb-target interaction network analysis helps to disclose molecular mechanism of traditional Chinese medicine.

Hao Liang, Hao Ruan, Qi Ouyang, Luhua Lai

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
5.4field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 39 citations in OpenAlex.

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  19. Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective.Evidence-based complementary and alternative medicine : eCAM · 2017
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 4 institutions in 1 country.

Hao LiangPeking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.
Hao RuanBeijing National Laboratory for Molecular Sciences, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China.
Qi OuyangPeking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.
Luhua LaiPeking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.
Beijing National Laboratory for Molecular Sciences · CNCenter for Life Sciences · CNPeking University · CNState Key Laboratory for Structural Chemistry of Unstable and Stable Species

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Though many studies have been performed to elucidate molecular mechanism of traditional Chinese medicines (TCMs) by identifying protein-compound interactions, no systematic analysis at herb level was reported. TCMs are prescribed by herbs and all compounds from a certain herb should be considered as a whole, thus studies at herb level may provide comprehensive understanding of TCMs. Here, we proposed a computational strategy to study molecular mechanism of TCM at herb level and used it to analyze a TCM anti-HIV formula. Herb-target network analysis was carried out between 17 HIV-related proteins and SH formula as well as three control groups based on systematic docking. Inhibitory herbs were identified and active compounds enrichment was found to contribute to the therapeutic effectiveness of herbs. Our study demonstrates that computational analysis of TCMs at herb level can catch the rationale of TCM formulation and serve as guidance for novel TCM formula design.

Indexed as

Anti-HIV AgentsDrug Evaluation, PreclinicalDrugs, Chinese HerbalHIV-1HIV InfectionsHuman Immunodeficiency Virus ProteinsHumansMedicine, Chinese TraditionalMolecular Docking SimulationProtein BindingVirus ReplicationAnti-HIV AgentsDrugs, Chinese HerbalHuman Immunodeficiency Virus Proteins

Identifiers

PMID27833111
PMCPMC5105066
OpenAlexW2555886195

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.