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Related Experiment Video

Updated: Jul 14, 2025

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
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Weighted hypergraph learning and adaptive inductive matrix completion for SARS-CoV-2 drug repositioning.

Yingjun Ma1, Junjiang Zhong1, Nenghui Zhu1

  • 1School of Mathematics and Statistics, Xiamen University of Technology, Xiamen 361024, China.

Methods (San Diego, Calif.)
|October 7, 2023
PubMed
Summary

This study introduces WHAIMC, a novel computational method for predicting virus-drug associations. WHAIMC effectively identifies potential drug repurposing candidates for viruses like SARS-CoV-2.

Keywords:
Adaptive inductive matrix completionSARS-CoV-2Virus-drug associationsWeighted hypergraph learning

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Area of Science:

  • Computational biology
  • Drug discovery
  • Virology

Background:

  • The SARS-CoV-2 pandemic highlights the need for rapid therapeutic development.
  • Drug repurposing offers a faster and more cost-effective alternative to de novo drug discovery.

Purpose of the Study:

  • To develop an advanced computational method for predicting virus-drug associations.
  • To identify potential drug candidates for repurposing against viral infections, including SARS-CoV-2.

Main Methods:

  • Proposed a weighted hypergraph learning and adaptive inductive matrix completion method (WHAIMC).
  • Integrated multi-source data including drug chemical structures, targets, virus genomes, and known associations.
  • Employed adaptive learning for similarity relations and weighted hypergraph learning for higher-order relationships.

Main Results:

  • WHAIMC demonstrated strong predictive performance for novel virus-drug associations, viruses, and drugs.
  • Successfully identified potential antiviral drugs for SARS-CoV-2 repurposing through case studies.
  • The method offers a new perspective for predicting virus-drug associations.

Conclusions:

  • WHAIMC is a powerful tool for predicting virus-drug associations and facilitating drug repurposing.
  • The study provides a valuable resource for developing new antiviral therapies.
  • The developed method and data are publicly available for further research.