Brewery: deep learning and deeper profiles for the prediction of 1D protein structure annotations

Bioinformatics. 2020 Jun 1;36(12):3897-3898. doi: 10.1093/bioinformatics/btaa204.

Abstract

Motivation: Protein structural annotations (PSAs) are essential abstractions to deal with the prediction of protein structures. Many increasingly sophisticated PSAs have been devised in the last few decades. However, the need for annotations that are easy to compute, process and predict has not diminished. This is especially true for protein structures that are hardest to predict, such as novel folds.

Results: We propose Brewery, a suite of ab initio predictors of 1D PSAs. Brewery uses multiple sources of evolutionary information to achieve state-of-the-art predictions of secondary structure, structural motifs, relative solvent accessibility and contact density.

Availability and implementation: The web server, standalone program, Docker image and training sets of Brewery are available at http://distilldeep.ucd.ie/brewery/.

Contact: gianluca.pollastri@ucd.ie.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology
  • Deep Learning*
  • Protein Structure, Secondary
  • Proteins
  • Solvents

Substances

  • Proteins
  • Solvents