SAINT-Angle: self-attention augmented inception-inside-inception network and transfer learning improve protein backbone torsion angle prediction.

ABSTRACT:

Motivation

Protein structure provides insight into how proteins interact with one another as well as their functions in living organisms. Protein backbone torsion angles ( ϕ and ψ ) prediction is a key sub-problem in predicting protein structures. However, reliable determination of backbone torsion angles using conventional experimental methods is slow and expensive. Therefore, considerable effort is being put into developing computational methods for predicting backbone angles.

Results

We present SAINT-Angle, a highly accurate method for predicting protein backbone torsion angles using a self-attention-based deep learning network called SAINT, which was previously developed for the protein secondary structure prediction. We extended and improved the existing SAINT architect

SUBMITTER: Hasan AKMM 

PROVIDER: S-EPMC10115468 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature