ArticleiScience2022
LIGHTHOUSE illuminates therapeutics for a variety of diseases including COVID-19.
Article in iScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Generative artificial intelligence in drug discovery: basic framework, recent advances, challenges, and opportunities.Frontiers in pharmacology · 2024Review
- Molecular Mechanism of Chronic Viral and Non-Viral Liver Diseases.International journal of molecular sciences · 2023Article
- Drug Screening for Hepatitis A Virus (HAV): Nicotinamide Inhibits c-Jun Expression and HAV Replication.Journal of virology · 2023Article
- Artificial intelligence-assisted drug repurposing via "chemical-induced gene expression ranking".Patterns (New York, N.Y.) · 2022Article
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Authors and funding
8 authors.
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Abstract
One of the bottlenecks in the application of basic research findings to patients is the enormous cost, time, and effort required for high-throughput screening of potential drugs for given therapeutic targets. Here we have developed LIGHTHOUSE, a graph-based deep learning approach for discovery of the hidden principles underlying the association of small-molecule compounds with target proteins. Without any 3D structural information for proteins or chemicals, LIGHTHOUSE estimates protein-compound scores that incorporate known evolutionary relations and available experimental data. It identified therapeutics for cancer, lifestyle related disease, and bacterial infection. Moreover, LIGHTHOUSE predicted ethoxzolamide as a therapeutic for coronavirus disease 2019 (COVID-19), and this agent was indeed effective against alpha, beta, gamma, and delta variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that are rampant worldwide. We envision that LIGHTHOUSE will help accelerate drug discovery and fill the gap between bench side and bedside.
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