CFP-Gen: Combinatorial Functional Protein Generation via Diffusion Language Models

Understand

Existing PLMs generate protein sequences based on a single-condition constraint from a specific modality, struggling to simultaneously satisfy multiple constraints across different modalities.

• In this work, we introduce CFP-Gen, a novel diffusion language model for Combinatorial Functional Protein GENeration.
• CFP-Gen facilitates the de novo protein design by integrating multimodal conditions with functional, sequence, and structural constraints.
• Specifically, an Annotation-Guided Feature Modulation (AGFM) module is introduced to dynamically adjust the protein feature distribution based on composable functional annotations, e.g., GO terms, IPR domains and EC numbers.