EPISODE · Feb 13, 2026 · 16 MIN
501-DrugCLIP：深度对比学习驱动的全基因组超快速虚拟筛选
from 聊聊Sci
这项研究介绍了一种名为 DrugCLIP 的超快速全基因组虚拟筛选方法，旨在解决传统药物研发中计算成本过高的问题。研究人员利用深度对比学习技术，将蛋白质口袋与小分子药物映射到同一向量空间，实现了比传统分子对接快千万倍的筛选速度。为了提升对未知结构蛋白的预测精度，他们还开发了 GenPack 策略来优化 AlphaFold 预测的蛋白质形态。通过湿实验验证，该团队成功发现了针对 TRIP12 等难治靶点的有效抑制剂，证明了该模型的实用价值。最终，该研究完成了覆盖约 20,000 个人类蛋白口袋的万亿级筛选，并建立了公开数据库以推动全球新药研发。References: Jia Y, Gao B, Tan J, et al. Deep contrastive learning enables genome-wide virtual screening[J]. Science, 2026, 391(6781): eads9530.前往小宇宙评论区与主播互动
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501-DrugCLIP：深度对比学习驱动的全基因组超快速虚拟筛选
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