LIGHTHOUSE illuminates therapeutics for a variety of diseases including COVID-19

Hideyuki Shimizu, Manabu Kodama, Masaki Matsumoto, Yasuko Orba, Michihito Sasaki, Akihiko Sato, Hirofumi Sawa, Keiichi I. Nakayama

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number105314
JournaliScience
Volume25
Issue number11
DOIs
Publication statusPublished - Nov 18 2022

All Science Journal Classification (ASJC) codes

  • General

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