De novo design of protein binders targeting the human sweet taste receptor as potential sweet proteins

TL;DR

This study presents a computational pipeline for designing novel protein binders targeting the human sweet taste receptor, aiming to develop new protein-based sweeteners with improved stability and reduced costs.

Contribution

The paper introduces an integrated de novo design method combining diffusion models, neural network-guided sequence design, and structure-based filtering to create receptor-specific protein binders.

Findings

Designed binders showed favorable structural confidence and predicted binding energies.

Binder2 mimics brazzein-like structural features and contacts.

Binder1 exhibited the strongest predicted binding affinity.

Abstract

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.