从头设计靶向人类甜味受体的蛋白质结合物作为潜在甜蛋白
De novo design of protein binders targeting the human sweet taste receptor as potential sweet proteins
AI总结：
本研究通过从头设计蛋白质结合物，模拟天然甜蛋白的功能特性，为开发新一代基于蛋白质的甜味剂提供了计算框架。
摘要：
过量摄入饮食糖分是代谢紊乱的主要贡献者，推动了寻找具有较低热量影响的替代甜味剂的全球兴趣。天然甜蛋白，如 brazzein，提供极高的甜度强度，同时热量贡献很小。然而，其广泛应用受限于自然多样性有限、稳定性差和生产成本高。最近结构生物学和从头蛋白质设计的进步为通过理性工程克服这些限制提供了新机会。在本研究中，我们报告了一种整合的计算流程，用于从头设计靶向人类甜味受体亚基 TAS1R2 的蛋白质结合物，这是异二聚体类 C G 蛋白偶联受体的关键组成部分，介导甜味感知。该工作流程结合了基于扩散的主链生成（RFdiffusion）、神经网络引导的序列设计（ProteinMPNN）、基于结构的过滤使用 Boltz-1，以及通过 MM/GBSA 计算评估结合能。利用最近解析的 TAS1R2 受体冷冻电镜结构，设计了针对 TAS1R2 的 Venus Flytrap 域和富含半胱氨酸域的蛋白质结合物。少数设计的结合物表现出有利的结构信心和预测的结合能量。特别是，Binder2 通过特定的短程 CRD 接触表现出类似 brazzein 的结构可能性，而 Binder1 显示出最强的预测结合亲和力。结合物-受体复合物的结构分析揭示了设计中的不同结合模式和二级结构轮廓。本研究证明了从头设计蛋白质结合物以模拟天然甜蛋白关键功能性质的可行性，建立了一种计算框架，用于理性开发下一代基于蛋白质的甜味剂。
英文摘要：
Excessive consumption of dietary sugars is a major contributor to metabolic disorders, driving global interest in finding alternative sweeteners with reduced caloric impact. Natural sweet proteins, such as brazzein, offer exceptional sweetness intensity with little caloric contribution. However, their widespread use is limited by restricted natural diversity, low stability, and high production costs. Recent advances in structural biology and de novo protein design provide new opportunities to overcome these limitations through rational engineering. In this study, we report an integrated computational pipeline for the de novo design of protein binders targeting the human sweet taste receptor subunit TAS1R2, a key component of the heterodimeric class C G protein-coupled receptor mediating sweetness perception. The workflow combines diffusion-based backbone generation (RFdiffusion), neural network-guided sequence design (ProteinMPNN), structure-based filtering using Boltz-1, and binding energy evaluation via MM/GBSA calculations. Using the recently resolved cryo-EM structure of the TAS1R2 receptor, protein binders were designed to target both the Venus Flytrap Domain and the cysteine-rich domain of TAS1R2. A few designed binders exhibited favorable structural confidence and predicted binding energetics. In particular, Binder2 exhibited brazzein-like structural plausibility through specific short-range CRD contacts, while Binder1 displayed the strongest predicted binding affinity. Structural analyses of the binder-receptor complex revealed distinct binding modes and secondary structure profiles among the designs. This study demonstrates the feasibility of de novo designing protein binders that emulate key functional properties of natural sweet proteins, establishing a computational framework for the rational development of next-generation protein-based sweeteners.
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