Discovery of novel A2AR antagonists through deep learning-based virtual screening

Abstract

The A2A adenosine receptor (A2AR) is emerging as a promising drug target for cancer immunotherapy. Novel A2AR 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 A2AR 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 A2AR antagonists for an extremely large molecular library were found successfully.

Keywords

• Deep learning
• Virtual screening
• A2AR antagonist
• Drug discovery
• Molecular docking