CodeFP2: Ontology-Guided De Novo Functional Protein Design

*De novo* functional protein design aims to generate proteins from scratch with desired molecular activities, enabling applications such as therapeutics and biocatalysis. Protein functions are hierarchically organized, with related functions sharing higher-level functional structure. However, existing generators either condition directly on target functions or enrich them with auxiliary functional context, leaving the hierarchical structure among functions largely unexploited. To address this challenge, we propose **CodeFP2**, an ontology-guided conditioning framework for joint sequence–structure diffusion that explicitly models functional hierarchies through broad-to-specific conditioning during denoising and pairwise relation encoding based on shared ancestry. Specifically, Ontology-Annealed Function Conditioning (OAFC) anneals each target's representation over its Gene Ontology ancestors during denoising, while Common-Ancestor Relation Encoding (CARE) encodes function pairs by symmetrically composing the paths connecting them to a shared ancestor. Experiments show consistent gains over the strongest baseline, including 2.7% in F1-Macro and 8.5% in pLDDT success rate on the full-distribution benchmark, and 5.7% in per-target exact recall on OOD tests.