Structure-based drug design with geometric deep learning
Open accessAbstract
Structure-based drug design uses three-dimensional geometric information of macromolecules, such as proteins or nucleic acids, to identify suitable ligands. Geometric deep learning, an emerging concept of neural-network-based machine learning, has been applied to macromolecular structures. This review provides an overview of the recent applications of geometric deep learning in bioorganic and medicinal chemistry, highlighting its potential for structure-based drug discovery and design. Emphasis is placed on molecular property prediction, ligand binding site and pose prediction, and structure-based de novo molecular design. The current challenges and opportunities are highlighted, and a forecast of the future of geometric deep learning for drug discovery is presented.
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- Authors
- Isert, C., Atz, K., & Schneider, G.
- Affiliations
- ETH Zurich (CH)
- Corresponding author
- Schneider, Gisbert
- Venue
- Current Opinion in Structural Biology
- Publisher
- Elsevier BV
- Published
- 2023-04
- Volume
- 79
- Pages
- 102548
- ISSN
- 0959-440X (ISSN-L)
- OpenAlex
- W4321769975
- Cited by
- 182
- References
- 5
- Citations by year
- 2026: 43 · 2025: 51 · 2024: 65 · 2023: 23
- FWCI
- 3.06
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Current Opinion in Structural Biology (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- National Science Foundation
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (182176)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Degradation and Inhibitors
- Keywords
- structure-based drug design, geometric deep learning, molecular property prediction, ligand binding site prediction, binding pose prediction, de novo molecular design, macromolecular structure, proteins, nucleic acids
- MeSH terms
- Machine Learning, Deep Learning, Ligands, Drug Design, Neural Networks, Computer, Drug Discovery
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