Semantical and geometrical protein encoding toward enhanced bioactivity and thermostability.

ABSTRACT: Protein engineering is a pivotal aspect of synthetic biology, involving the modification of amino acids within existing protein sequences to achieve novel or enhanced functionalities and physical properties. Accurate prediction of protein variant effects requires a thorough understanding of protein sequence, structure, and function. Deep learning methods have demonstrated remarkable performance in guiding protein modification for improved functionality. However, existing approaches predominantly rely on protein sequences, which face challenges in efficiently encoding the geometric aspects of amino acids' local environment and often fall short in capturing crucial details related to protein folding stability, internal molecular interactions, and bio-functions. Furthermore, there lacks a fun

SUBMITTER: Tan Y 

PROVIDER: S-EPMC12048155 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature