Repository for publicly available deep learning models developed in Rosetta community

trRosetta2

This package contains deep learning models and related scripts used by Baker group in CASP14.

Installation

Linux/Mac

1. clone the package

   git clone https://github.com/RosettaCommons/trRosetta2
   cd trRosetta2

2. create conda environment using one of the .yml files: casp14-baker-linux-cpu.yml, casp14-baker-linux-gpu.yml, casp14-baker-mac-cpu.yml

   conda env create -f casp14-baker-linux-gpu.yml
   conda activate casp14-baker

3. download network weights [1.1G]

   wget https://files.ipd.uw.edu/pub/trRosetta2/weights.tar.bz2
   tar xf weights.tar.bz2

4. download and install third-party software

   ./install_dependencies.sh

5. download sequence and structure databases

   wget http://wwwuser.gwdg.de/~compbiol/uniclust/2020_06/UniRef30_2020_06_hhsuite.tar.gz
   mkdir -p UniRef30_2020_06
   tar xf UniRef30_2020_06_hhsuite.tar.gz -C ./UniRef30_2020_06

   wget https://files.ipd.uw.edu/pub/trRosetta2/pdb100_2020Mar11.tar.gz
   tar xf pdb100_2020Mar11.tar.gz

Obtain a PyRosetta licence and install the package in the newly created casp14-baker conda environment (link).

Usage

mkdir -p examples/T1078
./run_pipeline.sh example/T1078.fa example/T1078

GitHub

https://github.com/RosettaCommons/trRosetta2