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-Structure paper
| タイトル | Deep contrastive learning enables genome-wide virtual screening. |
|---|---|
| ジャーナル・号・ページ | Science, Vol. 391, Issue 6781, Page eads9530, Year 2026 |
| 掲載日 | 2026年1月8日 |
著者 | Yinjun Jia / Bowen Gao / Jiaxin Tan / Jiqing Zheng / Xin Hong / Wenyu Zhu / Haichuan Tan / Yuan Xiao / Liping Tan / Hongyi Cai / Yanwen Huang / Zhiheng Deng / Xiangwei Wu / Yue Jin / Yafei Yuan / Jiekang Tian / Wei He / Weiying Ma / Yaqin Zhang / Lei Liu / Chuangye Yan / Wei Zhang / Yanyan Lan / ![]() |
| PubMed 要旨 | Recent breakthroughs in protein structure prediction have opened new avenues for genome-wide drug discovery, yet existing virtual screening methods remain computationally prohibitive. We present ...Recent breakthroughs in protein structure prediction have opened new avenues for genome-wide drug discovery, yet existing virtual screening methods remain computationally prohibitive. We present DrugCLIP, a contrastive learning framework that achieves ultrafast and accurate virtual screening, up to 10 million times faster than docking, while consistently outperforming various baselines on in silico benchmarks. In wet-lab validations, DrugCLIP achieved a 15% hit rate for norepinephrine transporter, and structures of two identified inhibitors were determined in complex with the target protein. For thyroid hormone receptor interactor 12, a target that lacks holo structures and small-molecule binders, DrugCLIP achieved a 17.5% hit rate using only AlphaFold2-predicted structures. Finally, we released GenomeScreenDB, an open-access database providing precomputed results for ~10,000 human proteins screened against 500 million compounds, pioneering a drug discovery paradigm in the post-AlphaFold era. |
リンク | Science / PubMed:41505557 |
| 手法 | EM (単粒子) |
| 解像度 | 2.87 - 2.98 Å |
| 構造データ | EMDB-61420, PDB-9jel: EMDB-61426, PDB-9jf3: |
| 化合物 | ![]() PDB-1ebn: ![]() ChemComp-CL: ![]() ChemComp-HOH: ![]() PDB-1ebo: |
| 由来 |
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キーワード | MEMBRANE PROTEIN / norepinephrine transporter / noradrenaline transporter |
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