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Chinese Medicine
Published in: Chinese Medicine 1/2016

Open Access 01-12-2016 | Research

In silico profiling for secondary metabolites from Lepidium meyenii (maca) by the pharmacophore and ligand-shape-based joint approach

Authors: Fan Yi, Xiao-lei Tan, Xin Yan, Hai-bo Liu

Published in: Chinese Medicine | Issue 1/2016

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Abstract

Background

Lepidium meyenii Walpers (maca) is an herb known as a traditional nutritional supplement and widely used in Peru, North America, and Europe to enhance human fertility and treat osteoporosis. The secondary metabolites of maca, namely, maca alkaloids, macaenes, and macamides, are bioactive compounds, but their targets are undefined.

Methods

The pharmacophore-based PharmaDB targets database screening joint the ligand shape similarity-based WEGA validation approach is proposed to predict the targets of these unique constituents and was performed using Discovery Studio 4.5 and PharmaDB. A compounds–targets–diseases network was established using Cytoscape 3.2. These suitable targets and their genes were calculated and analyzed using ingenuity pathway analysis and GeneMANIA.

Results

Certain targets were identified in osteoporosis (8 targets), prostate cancer (9 targets), and kidney diseases (11 targets). This was the first study to identify the targets of these bioactive compounds in maca for cardiovascular diseases (29 targets). The compound with the most targets (46) was an amide alkaloid (MA-24).

Conclusion

In silico target fishing identified maca’s traditional effects on treatment and prevention of osteoporosis, prostate cancer, and kidney diseases, and its potential function of treating cardiovascular diseases, as the most important of this herb’s possible activities.
Appendix
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Metadata
Title
In silico profiling for secondary metabolites from Lepidium meyenii (maca) by the pharmacophore and ligand-shape-based joint approach
Authors
Fan Yi
Xiao-lei Tan
Xin Yan
Hai-bo Liu
Publication date
01-12-2016
Publisher
BioMed Central
Published in
Chinese Medicine / Issue 1/2016
Electronic ISSN: 1749-8546
DOI
https://doi.org/10.1186/s13020-016-0112-y

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