Freeprotmap: waiting-free prediction method for protein distance map.

ABSTRACT:

Background

Protein residue-residue distance maps are used for remote homology detection, protein information estimation, and protein structure research. However, existing prediction approaches are time-consuming, and hundreds of millions of proteins are discovered each year, necessitating the development of a rapid and reliable prediction method for protein residue-residue distances. Moreover, because many proteins lack known homologous sequences, a waiting-free and alignment-free deep learning method is needed.

Result

In this study, we propose a learning framework named FreeProtMap. In terms of protein representation processing, the proposed group pooling in FreeProtMap effectively mitigates issues arising from high-dimensional sparseness in protein representation. In terms

SUBMITTER: Huang J 

PROVIDER: S-EPMC11069170 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature