GASP

Glycosyltransferase Acceptor Specificity Prediction (GASP). Pan-specific prediction of reactivity between any Glycosyltransferase Superfamily 1 (GT1) and chemical acceptor.

The install instructions here are thorough in order to allow for reproducing any of the work. The main randomforest train and test script is src/randomforest.py.

REQUIREMENTS

• Unix shell with zsh.
• R.
• Java runtime for some chemical feature generation. E.g. install with homebrew on Mac: brew install adoptopenjdk8
• pip.
• miniconda for python 3, e.g. use ./install_conda.sh
• julia for
  • adding new chemicals to an already established E3FP MDS (chemical features).
  • Feature selection (v1.8.5 used)

INSTALL

• Modify $PATH and $PYTHONPATH to easily access code. Assuming zsh this is done by running ./PATHS.sh >> ~/.zshrc or by copy-pasting the output of ./PATHS.sh to somewhere in ~/.zshrc.
• Run ./install.sh. It will install python packages to environment "GT". Activate env with conda activate GT. install.sh also defines command git root and calls ./install.R which installs R packages.
• Miller, e.g. with homebrew on mac: brew install miller
• Pymol in order to run chemical feature generation pipeline. E.g. install free open source pymol for linux, mac, or windows. With homebrew on mac: brew install brewsci/bio/pymol

RUN

• Adding new acceptors: see results/5-chemicalFeatures/
• Adding new enzymes: see results/6-unaligned/ and/or results/7-align/
• encode_features.py --help and randomforest.py --help for instructions.