New strategy for drug discovery by large-scale association analysis of molecular networks of different species

Bo Zhang, Yingxue Fu, Chao Huang, Chunli Zheng, Ziyin Wu, Wenjuan Zhang, Xiaoyan Yang, Fukai Gong, Yuerong Li, Xiaoyu Chen, Shuo Gao, Xuetong Chen, Yan Li, Aiping LYU, Yonghua Wang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

The development of modern omics technology has not significantly improved the efficiency of drug development. Rather precise and targeted drug discovery remains unsolved. Here a large-scale cross-species molecular network association (CSMNA) approach for targeted drug screening from natural sources is presented. The algorithm integrates molecular network omics data from humans and 267 plants and microbes, establishing the biological relationships between them and extracting evolutionarily convergent chemicals. This technique allows the researcher to assess targeted drugs for specific human diseases based on specific plant or microbe pathways. In a perspective validation, connections between the plant Halliwell-Asada (HA) cycle and the human Nrf2-ARE pathway were verified and the manner by which the HA cycle molecules act on the human Nrf2-ARE pathway as antioxidants was determined. This shows the potential applicability of this approach in drug discovery. The current method integrates disparate evolutionary species into chemico-biologically coherent circuits, suggesting a new cross-species omics analysis strategy for rational drug development.

Original languageEnglish
Article number21872
JournalScientific Reports
Volume6
DOIs
Publication statusPublished - 25 Feb 2016

Scopus Subject Areas

  • General

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