Molecular-evaluated and explainable drug repurposing for COVID-19 using ensemble knowledge graph embedding.

ABSTRACT: The search for an effective drug is still urgent for COVID-19 as no drug with proven clinical efficacy is available. Finding the new purpose of an approved or investigational drug, known as drug repurposing, has become increasingly popular in recent years. We propose here a new drug repurposing approach for COVID-19, based on knowledge graph (KG) embeddings. Our approach learns "ensemble embeddings" of entities and relations in a COVID-19 centric KG, in order to get a better latent representation of the graph elements. Ensemble KG-embeddings are subsequently used in a deep neural network trained for discovering potential drugs for COVID-19. Compared to related works, we retrieve more in-trial drugs among our top-ranked predictions, thus giving greater confidence in our prediction for out-o

SUBMITTER: Islam MK 

PROVIDER: S-EPMC9985643 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature