Enhancing Biosecurity with Watermarked Protein Design

Abstract

The biosecurity issue arises as the capability of deep learning-based protein design has rapidly increased in recent years. To address this problem, we propose a new general framework for adding watermarks to protein sequences designed by various sampling-based deep learning models. Compared to currently proposed protein design regulation procedures, watermarks ensure robust traceability and maintain the privacy of protein sequences. Moreover, using our framework does not decrease the performance or accessibility of the protein design tools.