Discovery of novel A2AR antagonists through deep learning-based virtual screening
Miru Tang, Chang Wen, Lin Jie, Hongming Chen, Ting Ran
Abstract
The A 2A adenosine receptor (A 2A R) is emerging as a promising drug target for cancer immunotherapy. Novel A 2A R antagonists are highly demanded due to few candidates entering clinic trials specific for cancer treatment. Structure-based virtual screening has made a great contribution to discover novel A 2A R antagonists, but most depended on inefficient molecular docking on relatively small molecular databases. In this work, a deep learning strategy was applied to accelerate docking-based virtual screening, through which new structural types of A 2A R antagonists for an extremely large molecular library were found successfully.
Topics & Concepts
Virtual screeningComputer scienceArtificial intelligenceMedicineDrug discoveryBioinformaticsBiologyComputational Drug Discovery MethodsReceptor Mechanisms and SignalingSARS-CoV-2 and COVID-19 Research