DDGun

INTRODUCTION

DDGun is an untrained method for predicting the stability change upon mutation

LICENSE

Copyright (C) 2019 Ludovica Montanucci, Emidio Capriotti and Piero Fariselli

This program and all program in this package are free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

CITATION

Montanucci L, Capriotti E, Frank Y, Ben-Tal N, Fariselli P. (2019). DDGun: an untrained method for the prediction of protein stability changes upon single and multiple point variations. BMC Bioinformatics. 20 (Suppl 14): 335. PMID:31266447.
Supplementary Files are available at: https://doi.org/10.5281/zenodo.4613881

• models.tar.gz: Models of protein mutants used for the predictions.
• predictions.tar.gz: ΔΔG predictions by using DDGun and DDGun3D methods.
• uniprot20_2016_02.tgz: Original DB for hhblits.
• uniclust30_2018_08_hhsuite.tar.gz: New DB for hhblits.

INSTALLATION

 # Prerequired packages
   - numpy
   - biopython

 # Automatic Installation
   git clone https://github.com/biofold/ddgun
   cd ddgun
   python setup.py

 # Manual Installation
 1) Download DDGun
    git clone https://github.com/biofold/ddgun

 2) Install hhblits
    cd ddgun/utils
    git clone https://github.com/soedinglab/hh-suite.git
    mkdir -p hh-suite/build && cd hh-suite/build
    cmake -DCMAKE_INSTALL_PREFIX=.. ..
    make -j 4 && make install

 3) Download uniclust30_2018_08_hhsuite (~25Gb)
    cd ../../../data
    wget http://wwwuser.gwdg.de/~compbiol/uniclust/2018_08/uniclust30_2018_08_hhsuite.tar.gz

 4) untar uniclust30_2018_08_hhsuite.tar.gz
    tar -xzvf uniclust30_2018_08_hhsuite.tar.gz
    cd ../

USAGE

- Run DDGun 3D:
    ./ddgun_3d.py test/1aar.pdb A test/1aar.muts

    #PDBFILE        CHAIN   VARIANT S_DDG[3D]       T_DDG[3D]       STABILITY[3D]
    1aar.pdb        A       K6A     0.4     0.4     Increase
    1aar.pdb        A       K6E     -0.0    -0.0    Neutral
    1aar.pdb        A       T7Q     -0.3    -0.3    Decrease
    1aar.pdb        A       T9A,G10A        -0.1,-0.1       -0.1    Decrease
    1aar.pdb        A       Y59W    -0.4    -0.4    Decrease


- Run DDGun Seq:
    ./ddgun_seq.py test/1aar.pdb.A.fasta test/1aar.muts

    #SEQFILE        VARIANT S_DDG[SEQ]      T_DDG[SEQ]      STABILITY[SEQ]
    1aarA.fasta        K6A     0.3     0.3     Increase
    1aarA.fasta        K6E     0.0     0.0     Neutral
    1aarA.fasta        T7Q     -0.6    -0.6    Decrease
    1aarA.fasta        T9A,G10A        -0.7,-0.6       -0.6    Decrease
    1aarA.fasta        Y59W    -0.6    -0.6    Decrease


- Output Legend:
    PDBFILE:   Inoput PDB File.
    CHAIN:     Input PDB File Chain.
    SEQFILE:   Input Sequence File.
    VARIANT:   Comma-separated protein variant in the format XPOSY 
               (X=Wild-Type Residue, POS=Position, Y=Mutant Residue).
    S_DDG:     Comma-separated predicted DDG of unfolding for single mutants.
    T_DDG:     Final predicted DDG of unfolding. For multiple mutant is 
               obtained as a combination of the single mutant predictions.
    STABILITY: Stability change: Decrease/Increase/Neutral
    [SEQ/3D]:  Sequence/Structure-based predictions