TT3D: Leveraging precomputed protein 3D sequence models to predict protein-protein interactions.

ABSTRACT:

Motivation

High-quality computational structural models are now precomputed and available for nearly every protein in UniProt. However, the best way to leverage these models to predict which pairs of proteins interact in a high-throughput manner is not immediately clear. The recent Foldseek method of van Kempen et al. encodes the structural information of distances and angles along the protein backbone into a linear string of the same length as the protein string, using tokens from a 21-letter discretized structural alphabet (3Di).

Results

We show that using both the amino acid sequence and the 3Di sequence generated by Foldseek as inputs to our recent deep-learning method, Topsy-Turvy, substantially improves the performance of predicting protein-protein interactions cross-s

SUBMITTER: Sledzieski S 

PROVIDER: S-EPMC10640393 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature