蛋白质设计
生物传感器
合成生物学
计算生物学
计算机科学
纳米技术
蛋白质工程
折叠(DSP实现)
生成语法
配体(生物化学)
分子识别
设计要素和原则
生物
化学
合理设计
生成模型
蛋白质结构
蛋白质折叠
功能(生物学)
分子生物物理学
工程类
生物系统
钥匙(锁)
生成设计
开发(拓扑)
小分子
生命系统
人工智能
作者
Yanzhe Zhang,Yitao Ke,Rui Zhi,Qihan Jin,Yiqin Feng,Chentong Wang,Minchao Fang,Jinyang Liao,Dachuan Chen,Jiao Liu,Longxing Cao
出处
期刊:
[Cold Spring Harbor Laboratory]
日期:2026-07-14
标识
DOI:10.64898/2026.07.13.738243
摘要
Abstract The de novo design of ligand-binding proteins has tremendous potential to revolutionize biosensor technology, yet converting these designs into functional sensors remains a major challenge due to the need for ligand-induced conformational changes or modulation of protein–protein interactions. Here, we introduce a physics-based generative approach for the de novo creation of proteins that bind small molecules and metal ions. Our method achieves customizable ligand-binding pocket formation in parallel with simulated protein folding, allowing for precise architectural control of the protein–ligand complex and facilitating the development of biosensors based on either ligand-triggered protein reassociation via split-protein reassembly or ligand-induced protein folding. We demonstrate the versatility of our computational method through successful designs targeting five small molecules, including the very small neurotransmitters serotonin and dopamine, and two metal ions. Biophysical characterization confirmed correct ligand binding, and crystal structures closely matched computational models. We demonstrated the biosensor engineering potential of these designs by constructing serotonin and dopamine sensors using a split protein strategy and explored several approaches to enhance sensor activity. Additionally, we developed a zinc sensor through a zinc-induced protein folding mechanism. Overall, our physics-based generative approach provides a robust framework for the de novo design of ligand-binding proteins, opening new avenues for the development of ligand-responsive biosensors.
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