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Deep Learning-Assisted Repurposing of Plant Compounds for Treating Vascular Calcification: An In Silico Study with

Chia-Ter Chao1,2,3, You-Tien Tsai3, Wen-Ting Lee4

  • 1Nephrology Division, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.

Oxidative Medicine and Cellular Longevity
|January 17, 2022
PubMed
Summary

Deep learning identified plant compounds like sulforaphane and daidzein for vascular calcification (VC) treatment. This computational approach aids in discovering new therapeutics for cardiovascular disease management.

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Area of Science:

  • Computational biology
  • Drug discovery
  • Cardiovascular research

Background:

  • Vascular calcification (VC) is a significant contributor to cardiovascular mortality.
  • There is an unmet need for effective therapeutics to manage VC.
  • This study explored novel therapeutic strategies for VC management.

Purpose of the Study:

  • To leverage deep learning for screening plant compounds with repurposing potential for VC.
  • To develop a computational model for identifying novel VC-associated drug candidates.
  • To uncover plant-derived compounds that can manage vascular calcification.

Main Methods:

  • Integrated diverse biological databases (CTD, DrugBank, PubChem, GO, BioGrid) for drug-disease association analysis.
  • Employed deep representation learning using graph neural networks and random forest classifiers.
  • Validated predicted compounds in an in vitro vascular calcification model.

Main Results:

  • Processed 6,790 compounds, 11,958 GO terms, 7,238 diseases, and 25,482 proteins.
  • The deep learning model effectively distinguished potential VC-treating compounds.
  • In vitro validation confirmed sulforaphane and daidzein as promising candidates against VC.

Conclusions:

  • Deep learning is a valuable tool for identifying plant-based compounds for VC treatment.
  • The developed model serves as an efficient computational screening platform for early drug discovery.
  • This approach accelerates the identification of potential therapeutics for vascular calcification.