Recent Progress of Deep Learning in Drug Discovery
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Updated: Nov 19, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
Published on: February 23, 2024
Feng Wang1, XiaoMin Diao1, Shan Chang2
1College of Information Science and Engineering, Huaide College of Changzhou University, Taizhou 214500, China.
Abstract:
Deep learning, an emerging field of artificial intelligence based on neural networks in machine learning, has been applied in various fields and is highly valued. Herein, we mainly review several mainstream architectures in deep learning, including deep neural networks, convolutional neural networks and recurrent neural networks in the field of drug discovery. The applications of these architectures in molecular de novo design, property prediction, biomedical imaging and synthetic planning have also been explored. Apart from that, we further discuss the future direction of the deep learning approaches and the main challenges we need to address.
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