让用户用对话方式与蛋白质实时互动，快速获取结构与功能证据。
Speak to a Protein: An Interactive Multimodal Co-Scientist for Protein Analysis
- 通过语言对话整合文献、结构与配体数据，实时生成3D可视化。
- 支持动态标注、代码运行与结果解释，实现问题到答案的即时响应。
- 适合生物学家、药理研究者，降低结构分析技术门槛。
构建蛋白质的完整认知模型通常需要数周时间阅读文献、交叉比对晶体与预测结构，并分析配体复合物，过程缓慢且依赖专业计算技能。我们提出「Speak to a Protein」，一种将蛋白质分析转化为与专家级智能体进行多模态交互对话的新能力。该系统可检索并融合相关文献、结构与配体数据，在实时3D场景中呈现答案；支持高亮、注释、操作与可视化反馈。必要时可自动生成并运行代码，以文本和图形形式解释结果。我们在多个关键蛋白质上验证了其能力，通过提问结合位点、构象变化或结构-活性关系，实现实时假设检验。该系统显著缩短从提问到获取证据的时间，降低高级结构分析门槛，通过语言、代码与3D结构的紧密耦合，推动科学假设生成。系统免费开放：https://open.playmolecule.org。
原文摘要 · Abstract (English)
Building a working mental model of a protein typically requires weeks of reading, cross-referencing crystal and predicted structures, and inspecting ligand complexes, an effort that is slow, unevenly accessible, and often requires specialized computational skills. We introduce \emph{Speak to a Protein}, a new capability that turns protein analysis into an interactive, multimodal dialogue with an expert co-scientist. The AI system retrieves and synthesizes relevant literature, structures, and ligand data; grounds answers in a live 3D scene; and can highlight, annotate, manipulate and see the visualization. It also generates and runs code when needed, explaining results in both text and graphics. We demonstrate these capabilities on relevant proteins, posing questions about binding pockets, conformational changes, or structure-activity relationships to test ideas in real-time. \emph{Speak to a Protein} reduces the time from question to evidence, lowers the barrier to advanced structural analysis, and enables hypothesis generation by tightly coupling language, code, and 3D structures. \emph{Speak to a Protein} is freely accessible at https://open.playmolecule.org.
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