S-PLM: Structure-Aware Protein Language Model via Contrastive Learning Between Sequence and Structure.

ABSTRACT: Proteins play an essential role in various biological and engineering processes. Large protein language models (PLMs) present excellent potential to reshape protein research by accelerating the determination of protein functions and the design of proteins with the desired functions. The prediction and design capacity of PLMs relies on the representation gained from the protein sequences. However, the lack of crucial 3D structure information in most PLMs restricts the prediction capacity of PLMs in various applications, especially those heavily dependent on 3D structures. To address this issue, S-PLM is introduced as a 3D structure-aware PLM that utilizes multi-view contrastive learning to align the sequence and 3D structure of a protein in a coordinated latent space. S-PLM applies Swin-Tra

SUBMITTER: Wang D 

PROVIDER: S-EPMC11791933 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature