Haipeng Gong

Nov 11, 2024 | nature.com | Yunxin Xu |Boxue Tian |Haipeng Gong |David R. Liu |Christopher A. Voigt |B. W. Thuronyi

AbstractDesigning proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here we establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions.

Dec 14, 2023 | biorxiv.org | Yuyang Zhang |Haipeng Gong

AbstractThe de novo design of protein structures is an intriguing research topic in the field of protein engineering. Recent breakthroughs in diffusion-based generative models have demonstrated substantial promise in tackling this task, notably in the generation of diverse and realistic protein structures.