Anthropic 生物学团队用 Claude 绘制细菌穹窿颗粒首个 3D 结构

我们正在分享我们的生物学研究团队如何与 Claude 合作，绘制出细菌生命中穹窿颗粒的首个 3D 结构。 穹窿颗粒是一个长期未解之谜。它们是桶状物体，是我们细胞中发现的最大的蛋白质结构之一。它们最早由 Leonard Rome 和 Nancy Kedersha 于 1986 年发现，但其功能仍然未知。 借助 Claude，我们找到了一些结果，可能让我们更接近解开这个谜团。 到目前为止，穹窿颗粒只在动物和植物等复杂生物的细胞中被发现。我们已经证明，来自细菌（以及感染它们的病毒）的类似蛋白质也能组装成穹窿颗粒。在這些更简单的生命形式中找到这些结构，可能使研究它们在我们自身细胞中的功能变得更容易。 对我们的生命科学团队来说，这个项目也展示了利用 AI 加速科学的潜力（以及局限性）。 在完整文章中，我们讨论了 Claude 如何能够大幅加快某些阶段——人工确定穹窿颗粒的结构原本需要数周到数月艰苦的工作，但在这里只用了几天。我们还讨论了 Claude 在此过程中犯的一些简单错误，以及我们如何与机器学习研究人员合作来解决这些问题。 阅读更多：https://t.co/KowVVCSPp8

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We’re sharing how our biology research team worked with Claude to map the first 3D structure of a vault particle from bacterial life. Vault particles are a longstanding mystery. They are barrel-shaped objects, among the largest protein structures found in our cells. They were first discovered by Leonard Rome and Nancy Kedersha in 1986, but their function remains unknown. With Claude, we’ve found results that might bring us closer to solving that mystery. Until now, vaults were only known in the cells of complex things like animals and plants. We have shown that similar proteins from bacteria (and the viruses that infect them) can also assemble into vaults. Finding the structures in these simpler forms of life may make it easier to investigate their function in our own cells. For our life sciences team, the project was also a demonstration of the potential (and the limitations) of using AI to accelerate science. In our full piece, we discuss how Claude was able to dramatically speed up some stages—manually determining the vault particle’s structure would have taken weeks to months of painstaking work, but here it took days. We also discuss how Claude made some simple mistakes along the way, and how we collaborated with our machine learning researchers to address them. Read more: https://t.co/KowVVCSPp8