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Predicting herb-disease associations using network-based measures in human protein interactome.

Seunghyun Wang1, Hyun Chang Lee2, Sunjae Lee3

  • 1Department of Bio and Brain Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea.

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|June 6, 2024
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Summary

This study introduces a computational method to predict herb-disease associations, considering multi-compound multi-target effects. The network-based approach, Weighted Average Closest Path (WACP), successfully identifies potential relationships, modernizing herbal medicine with scientific evidence.

Keywords:
Human protein interactomeMulti-compound multi-target (MCMT)Natural herb

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Area of Science:

  • Computational biology
  • Pharmacology
  • Systems biology

Background:

  • Natural herbs are widely used for disease treatment, yet often lack scientific validation.
  • Current research often focuses on single compounds, neglecting the multi-compound multi-target (MCMT) nature of herbal medicine.
  • There is a need for evidence-based computational approaches to predict herb-disease associations.

Purpose of the Study:

  • To develop and validate a network-based computational method for predicting herb-disease associations.
  • To incorporate multi-compound and multi-target effects into the prediction model.
  • To provide scientific evidence for the efficacy of natural herbs.

Main Methods:

  • A novel network-based measure, Weighted Average Closest Path (WACP), was devised.
  • The method quantifies proximity between herb-related and disease-related genes, considering herb compound composition.
  • Predictions were validated using the human protein interactome.

Main Results:

  • The WACP method demonstrated successful prediction of herb-disease associations with an AUROC of 0.777.
  • The WACP method outperformed simpler network-based proximity measures.
  • Case studies, including Brassica oleracea var. italica, were analyzed, and novel potential herb-disease pairs were suggested.

Conclusions:

  • The proposed computational method offers a promising approach to modernize herbal medicine.
  • It provides scientific evidence for molecular associations between herbs and diseases.
  • This method can facilitate the discovery of new therapeutic applications for natural herbs.