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English(EN) Molecular Lead Optimization via Agentic Tool Planning

AI Agent TRACE 增强药物发现先导优化

研究人员开发了 TRACE,这是一种利用 LLM 推理进行药物发现中分子先导优化的新型代理。与之前一次性优化的方法不同,TRACE 将工具选择视为一个顺序决策问题,从而能够进行前瞻性优化并考虑结构约束。实验表明,与现有模型相比,TRACE 在保持分子相似性的同时,实现了更高的优化成功率、更大的属性改进和更高的有效性。 AI

影响 该 AI Agent 能够通过更有效地优化分子结构,显著加快药物发现的速度并提高其效率。

排序理由 这是一篇详细介绍用于特定科学任务的新型 AI Agent 的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

AI Agent TRACE 增强药物发现先导优化

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这是一篇详细介绍用于特定科学任务的新型 AI Agent 的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Lingxiao Li, Haobo Zhang, Ruohao Fan, Bin Chen, Jiayu Zhou ·

    分子先导化合物优化通过Agentic工具规划

    arXiv:2605.28862v1 Announce Type: new Abstract: Drug discovery is a lengthy and resource-intensive process composed of multiple stages. Among these stages, lead optimization plays a critical role in transforming early hit compounds into viable drug candidates. This stage requires…