An AI-enabled proteome-scale framework for identifying sustainable protein alternatives for future food systems

Identifying sustainable alternatives to animal proteins is a central challenge for global food system transformation. Replacing animal proteins requires preserving food functionalities—such as gelation, foaming, and emulsification—that arise from the collective behavior of heterogeneous protein mixtures within food matrices. While these properties are assessed experimentally at the ingredient level, systematically comparing the vast diversity of natural proteins remains difficult, and most artificial intelligence (AI)-based protein models focus on individual proteins rather than proteome-level behavior. Here, we present AlterProtX, an AI-enabled framework that integrates molecular- and proteome-scale features to guide alternative protein discovery. AlterProtX predicts protein thermal stability, a processing-relevant property, and integrates it with six intermolecular interaction attributes into distribution-based proteome representations. This multiscale approach enables mechanistic comparison between animal and non-animal proteomes, revealing molecular features underlying functional similarity and divergence. By integrating allergenic potential and nutritional adequacy, AlterProtX supports early-stage prioritization of candidate protein sources and provides an interpretable platform for proteome-level evaluation of food proteins.