File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1016/j.apsb.2025.09.036
- Find via

Supplementary
-
Citations:
- Appears in Collections:
Article: PhenoModel: A Multimodal Phenotypic Drug Design Foundation Model for Discovering Novel Potential Inhibitors of Multiple Cancer Cells
| Title | PhenoModel: A Multimodal Phenotypic Drug Design Foundation Model for Discovering Novel Potential Inhibitors of Multiple Cancer Cells |
|---|---|
| Authors | |
| Issue Date | 24-Sep-2025 |
| Publisher | Elsevier |
| Citation | Acta Pharmaceutica Sinica B, 2025 How to Cite? |
| Abstract | Phenotypic drug discovery (PDD) focuses on the observable traits or phenotype of cells or organisms in response to drug treatment, rather than relying primarily on specific molecular targets. Drugs discovered through this approach may have better therapeutic relevance, as they are tested in conditions that closely mimic human disease. In this study, we present PhenoModel, a multimodal molecular foundation model developed using our unique dual-space contrastive learning framework. This model effectively connects molecular structures with phenotypic information. PhenoModel is applicable to a range of downstream drug discovery tasks, including molecular property prediction and active molecule screening based on targets, phenotypes, and ligands. Our results demonstrate that PhenoModel outperforms baseline methods in these areas. Building from this model, PhenoScreen is developed to successfully identify several phenotypically bioactive compounds against osteosarcoma and rhabdomyosarcoma cell lines. These findings highlight the versatility of PhenoModel and its potential to accelerate drug discovery by uncovering novel therapeutic pathways and expanding the diversity of viable drug candidates. |
| Persistent Identifier | http://hdl.handle.net/10722/366483 |
| ISSN | 2023 Impact Factor: 14.7 2023 SCImago Journal Rankings: 3.035 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Wang, Shihang | - |
| dc.contributor.author | Han, Qilei | - |
| dc.contributor.author | Qin, Weichen | - |
| dc.contributor.author | Wang, Lin | - |
| dc.contributor.author | Yuan, Junhong | - |
| dc.contributor.author | Cai, Fengyu | - |
| dc.contributor.author | Zhao, Yiqun | - |
| dc.contributor.author | Ren, Pengxuan | - |
| dc.contributor.author | Zhang, Yunze | - |
| dc.contributor.author | Tang, Yilin | - |
| dc.contributor.author | Li, Ruifeng | - |
| dc.contributor.author | Li, Zongquan | - |
| dc.contributor.author | Zhang, Wenchao | - |
| dc.contributor.author | Gao, Shenghua | - |
| dc.contributor.author | Bai, Fang | - |
| dc.date.accessioned | 2025-11-25T04:19:39Z | - |
| dc.date.available | 2025-11-25T04:19:39Z | - |
| dc.date.issued | 2025-09-24 | - |
| dc.identifier.citation | Acta Pharmaceutica Sinica B, 2025 | - |
| dc.identifier.issn | 2211-3835 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/366483 | - |
| dc.description.abstract | <p>Phenotypic drug discovery (PDD) focuses on the observable traits or phenotype of cells or organisms in response to drug treatment, rather than relying primarily on specific molecular targets. Drugs discovered through this approach may have better therapeutic relevance, as they are tested in conditions that closely mimic human disease. In this study, we present PhenoModel, a multimodal molecular foundation model developed using our unique dual-space contrastive learning framework. This model effectively connects molecular structures with phenotypic information. PhenoModel is applicable to a range of downstream drug discovery tasks, including molecular property prediction and active molecule screening based on targets, phenotypes, and ligands. Our results demonstrate that PhenoModel outperforms baseline methods in these areas. Building from this model, PhenoScreen is developed to successfully identify several phenotypically bioactive compounds against osteosarcoma and rhabdomyosarcoma cell lines. These findings highlight the versatility of PhenoModel and its potential to accelerate drug discovery by uncovering novel therapeutic pathways and expanding the diversity of viable drug candidates. <br></p> | - |
| dc.language | eng | - |
| dc.publisher | Elsevier | - |
| dc.relation.ispartof | Acta Pharmaceutica Sinica B | - |
| dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
| dc.title | PhenoModel: A Multimodal Phenotypic Drug Design Foundation Model for Discovering Novel Potential Inhibitors of Multiple Cancer Cells | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1016/j.apsb.2025.09.036 | - |
| dc.identifier.eissn | 2211-3843 | - |
| dc.identifier.issnl | 2211-3835 | - |
