Generation of a high confidence set of domain-domain interface types to guide protein complex structure predictions by AlphaFold.

ABSTRACT:

Motivation

While the release of AlphaFold (AF) represented a breakthrough for the prediction of protein complex structures, its sensitivity, especially when using full length protein sequences, still remains limited. Modeling success rates might increase if AF predictions were guided by likely interacting protein fragments. This approach requires available sets of highly confident protein-protein interface types. Computational resources, such as 3did, infer interacting globular domain types from observed contacts in protein structures. Assessing the accuracy of these predicted interface types is difficult because we lack hand-curated reference sets of verified domain-domain interface (DDI) types.

Results

To improve protein complex modeling of DDIs by AF, we manually inspecte

SUBMITTER: Geist JL 

PROVIDER: S-EPMC11361816 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature