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Heterogeneous network propagation for herb target identification.

Kuo Yang1, Guangming Liu1, Ning Wang1

  • 1School of Computer and Information Technology and Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, 100044, China.

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|March 29, 2018
PubMed
Summary
This summary is machine-generated.

A new computational method, heNetRW, effectively predicts herb targets by analyzing heterogeneous networks. This approach improves upon existing methods, aiding in understanding herbal drug mechanisms.

Keywords:
Herb target identificationHeterogeneous herb-target networkRandom walk

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Area of Science:

  • Computational biology
  • Pharmacology
  • Traditional Chinese Medicine

Background:

  • Identifying herb targets is crucial for understanding Traditional Chinese Medicine (TCM) pharmacology.
  • Experimental target identification is challenging and time-consuming.
  • Computational methods offer an efficient alternative, but maximizing heterogeneous network data remains a challenge.

Purpose of the Study:

  • To propose a novel computational method, heNetRW, for identifying herb targets.
  • To leverage heterogeneous herb-target network data for improved prediction performance.

Main Methods:

  • Developed a random walk algorithm on a heterogeneous herb-target network (heNetRW).
  • Constructed a network integrating herbs, targets, and their interactions.
  • Simulated random walks to predict candidate herb targets.

Main Results:

  • heNetRW demonstrated superior performance compared to the PRINCE algorithm in target prediction.
  • Significant improvements in F1-score and Hit@1 were observed in validation settings.
  • Identified novel candidate targets for Rhizoma Coptidis and Turmeric, valuable for further research.

Conclusions:

  • heNetRW effectively fuses known information, including herb-target associations and pathway similarities, to enhance prediction accuracy.
  • The method outperforms PRINCE, offering a valuable tool for guiding herb target selection.
  • Predictions can facilitate the elucidation of molecular mechanisms underlying herbal drugs.