Tpgen: a language model for stable protein design with a specific topology structure.

ABSTRACT:

Background

Natural proteins occupy a small portion of the protein sequence space, whereas artificial proteins can explore a wider range of possibilities within the sequence space. However, specific requirements may not be met when generating sequences blindly. Research indicates that small proteins have notable advantages, including high stability, accurate resolution prediction, and facile specificity modification.

Results

This study involves the construction of a neural network model named TopoProGenerator(TPGen) using a transformer decoder. The model is trained with sequences consisting of a maximum of 65 amino acids. The training process of TopoProGenerator incorporates reinforcement learning and adversarial learning, for fine-tuning. Additionally, it encompasses a stabi

SUBMITTER: Min X 

PROVIDER: S-EPMC10804651 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature