Identification of nanomolar adenosine A2A receptor ligands using reinforcement learning and structure-based drug design

Identification of nanomolar adenosine A2A receptor ligands using reinforcement learning and structure-based drug design

Abstract Generative chemical language models (CLMs) have demonstrated success in learning language-based molecular representations for de novo drug design. Here, we integrate structure-based drug design (SBDD) principles with CLMs to go from protein structure to novel small-molecule ligands, without...

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Main Authors: Morgan Thomas, Pierre G. Matricon, Robert J. Gillespie, Maja Napiórkowska, Hannah Neale, Jonathan S. Mason, Jason Brown, Kaan Harwood, Charlotte Fieldhouse, Nigel A. Swain, Tian Geng, Noel M. O’Boyle, Francesca Deflorian, Andreas Bender, Chris de Graaf
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-025-60629-0
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https://doi.org/10.1038/s41467-025-60629-0

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