DeepRLI: a multi-objective framework for universal protein–ligand interaction prediction
DeepRLI is a multi-objective deep learning framework for universal protein–ligand interaction prediction, applicable to binding affinity prediction, molecular docking, and virtual screening tasks, offering better guidance for drug discovery.
Authors
- Jianfeng Pei (ORCID: https://orcid.org/0000-0002-8482-1185)
- Haoyu Lin (ORCID: https://orcid.org/0000-0002-6664-6985)
- Luhua Lai (ORCID: https://orcid.org/0000-0002-8343-7587)
- Shiwei Wang (ORCID: https://orcid.org/0000-0002-6836-8229)
- Yibo Li (ORCID: https://orcid.org/0000-0001-6105-1969)
- Jintao Zhu (ORCID: https://orcid.org/0000-0002-7136-3314)
Institutions
- Peking University (CN)
- Beijing National Laboratory for Molecular Sciences (CN)
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d4dd00403e
- Citations
- 4
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 6.02