MolProphecy: Bridging medicinal chemists’ knowledge and molecular pre-trained models via a multi-modal framework
MolProphecy provides a generalizable framework for molecular property prediction by integrating simulated chemist expertise with structural data. Its design allows simulated input to be replaced with real chemist knowledge without retraining, establishing a pathway toward collaborative and interpretable drug discovery.
Authors
- Qian Yang (ORCID: https://orcid.org/0000-0002-2170-7086)
- Qiong Zhou (ORCID: https://orcid.org/0000-0001-5118-6683)
- Zhehao Guo
- Fengfeng Zhou (ORCID: https://orcid.org/0000-0002-8108-6007)
- Tian Wang (ORCID: https://orcid.org/0000-0001-9694-4986)
- Chang Liu (ORCID: https://orcid.org/0000-0001-7257-8563)
- Jiao Li (ORCID: https://orcid.org/0000-0003-0527-6535)
- Qi Lü (ORCID: https://orcid.org/0000-0001-6061-5478)
- Ruochi Zhang (ORCID: https://orcid.org/0000-0002-9150-5308)
- Yusi Fan (ORCID: https://orcid.org/0000-0003-2943-2221)
- Jianping Zhao (ORCID: https://orcid.org/0000-0003-2304-9862)
Institutions
- Jilin University (CN)
- Beijing Academy of Science and Technology (CN)
Publication Details
- Journal
- Journal of Advanced Research
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1016/j.jare.2025.10.035
- Citations
- 1
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 1.50