GAX: Genetic Algorithm for minimum ensemble fitting of SAXS data

GAX is a method based on genetic algorithm for extracting a minimum ensemble of conformations from the pool of conformations generated by molecular dynamics simulations that fit SAXS data. GAX is implemented as a webserver and an open-source python-based software.

Installation using conda:

conda create --yes -n GAX -c conda-forge python=3.8 numpy scipy MDAnalysis MDAnalysisTests

source activate GAX

conda install imp

Running GAX:

usage: GA_wrapper.py [-h] --pdb PDB --saxs SAXS --mode MODE [--trj TRJ] [--calc_saxs CALC_SAXS] [-s S] [-r R] [-nb_gen NB_GEN] [-nb_ens NB_ENS] [-window WINDOW]

GAX has two modes:

• Using back-calculated SAXS profile from a molecular dynamics simulation (--mode yes). This file has to contain a SAXS profile for every conformation.

• Using a trajectory file from a molecular dynamics simulation (--mode no). The acceptable trajecotry formats are those readable by "MDAnalysis".

Arguments:

-h, --help show this help message and exit

--pdb PDB Protein structure file

--saxs SAXS Experimental SAXS data

--mode yes/no Do you have the back-calculated profile

--trj TRJ Trajectory file

--calc_saxs CALC_SAXS Back-calculated SAXS profile

Advanced options:

-s S Ensemble size

-r R Number of repeats

-nb_gen NB_GEN Number of generations

-nb_ens NB_ENS Number of ensembles

-window WINDOW Window size