Protein-DNA binding sites prediction based on pre-trained protein language model and contrastive learning.

ABSTRACT: Protein-DNA interaction is critical for life activities such as replication, transcription and splicing. Identifying protein-DNA binding residues is essential for modeling their interaction and downstream studies. However, developing accurate and efficient computational methods for this task remains challenging. Improvements in this area have the potential to drive novel applications in biotechnology and drug design. In this study, we propose a novel approach called Contrastive Learning And Pre-trained Encoder (CLAPE), which combines a pre-trained protein language model and the contrastive learning method to predict DNA binding residues. We trained the CLAPE-DB model on the protein-DNA binding sites dataset and evaluated the model performance and generalization ability through various expe

SUBMITTER: Liu Y 

PROVIDER: S-EPMC10782905 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature