This Collection supports and amplifies research related to SDG 3.
With the rapid development of artificial intelligence (AI) and machine learning (ML) techniques, their transformative impact on modern drug design is inevitable. AI and ML enable new applications that address the limitations of structure-based and ligand-based drug design (SBDD and LBDD). This collection invites cutting-edge research on the development and application of AI and ML technologies in small-molecule drug design. These technologies have the potential to revolutionize drug discovery by enhancing efficiency, accuracy, and innovation in identifying and optimizing small-molecule therapeutics while also reducing the time and cost of discovery. We welcome original research articles, perspectives, and reviews that explore various aspects of AI and ML in small-molecule drug design, including but not limited to:
- Generative AI for small molecule design and optimization
- AI models to assess small molecule-target interactions
- Assessment of AI models in prediction of druglike properties
- Integration of AI models with other ligand- or structure-based drug design approaches
- AI and ML for accelerating high-throughput virtual screening
This is the second volume of the AI and Small-Molecule Drug Discovery Collection.