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English(EN) Chamaileon: Cross-Context Binder Design with Contextualized Modeling and Mixed Sampling

Chamaileon框架支持多目标和多状态蛋白质结合剂设计

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了Chamaileon，一个旨在解决当前蛋白质结合剂设计方法局限性的新框架。与目前专注于单一目标和状态的现有方法不同，Chamaileon通过对跨上下文结合景观进行建模，实现了多目标和多状态结合剂的设计。该系统在训练范式中使用了称为In-Context Complex Co-Design (I3CD) 的方法来进行情境感知序列-结构协同建模，并在推理过程中采用Mixture-of-Paths Sampling (MoPS) 来优化跨各种情境的序列。在新的基准CROSS上的评估表明，Chamaileon可以生成适应于多样化构象景观和多目标要求的序列。 AI

影响 通过实现更通用和可编程的蛋白质结合剂设计，以应对复杂的生物学应用，从而推进蛋白质工程能力。

排序理由 该集群描述了一篇关于蛋白质结合剂设计新计算框架的最新研究论文。

在 Hugging Face Daily Papers 阅读 →

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Chamaileon框架支持多目标和多状态蛋白质结合剂设计

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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Hengyuan Cao, Shizhuo Cheng, Mingxuan Liu, Weicheng Huang, Yunhong Lu, Chenxi Cai, Yan Zhang, Min Zhang ·

    Chamaileon：具有上下文建模和混合采样的跨上下文绑定器设计

    arXiv:2607.23518v1 Announce Type: new Abstract: The rapid evolution of generative models has unlocked new potentials in protein binder design, a pivotal task in structural biology, by facilitating end-to-end generation via joint sequence-structure modeling or hallucination. Howev…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Chamaileon：具有上下文建模和混合采样的跨上下文绑定器设计

    The rapid evolution of generative models has unlocked new potentials in protein binder design, a pivotal task in structural biology, by facilitating end-to-end generation via joint sequence-structure modeling or hallucination. However, existing approaches are predominantly implem…

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