Set up

To run Efitter you need a parameter file in Python language format that specifies:
- input structures to fit
- EM map
- fitting parameters
- optionally, options for execution on a computer cluster

For this tutorial, the parameter file is already prepared in the Elongator folder:

efitter_params.py:

which contains:

from efitter import Map
from string import Template

method='chimera'
dry_run = False # Dry run would only print commands it is going to run
run_crashed_only = False # Only run the jobs that have not delivered output
master_outdir = 'fits' # relative path to the output, it will be created in the running directory

MAPS = [
    Map('EM_data/emd_4151_binned.mrc', threshold=0.01, resolution=25),
]

models_dir = 'in_pdbs'

PDB_FILES = [
    'Elp1_NTD_1st_propeller.pdb',
    'Elp1_NTD_2nd_propeller.pdb',
    'Elp1.CTD.on5cqs.5cqr.model_ElNemo_mode7.pdb',
    'Elp2.pdb',
    'Elp3.mono.pdb',
]

CA_only = False # Calculate the fitting scores using Calpha atoms only?
backbone_only = False # Calculate the fitting scores using backbone atoms only?
move_to_center = True # Move the PDB structure to the center of the map?

# Each element of fitmap_args is a dictionary specifying parameters for a run
# If multiple dictionaries are specified,
# the script will run a seperate run for each dictionary for each map-structure combination.
# E.g. if two maps, three structures, and two paramaters dictionaries are specified,
# the script will run 2 x 3 x 2 = 12 runs.
fitmap_args = [
    # Parameters for main runs (https://www.cgl.ucsf.edu/chimera/docs/UsersGuide/midas/fitmap.html)
    {
        'template': Template("""
            map $map
            map_threshold $threshold
            fitmap_args resolution $resolution metric cam maxSteps 100 envelope true search 100000 placement sr clusterAngle 1 clusterShift 1.0 radius 200 inside .60
            saveFiles False
            """),
        'config_prefix': 'search100000_metric_cam_inside0.6' # some name informative of the fitmap_args parameters
        }
]

# Adjust the parameters below to run on a cluster or standalone workstation

#For example, for a cluster with Slurm submission system, use:
cluster_submission_command = 'sbatch'
run_script_templ = Template("""#!/bin/bash
#
#SBATCH --job-name=$job_name
#SBATCH --time=1-00:00:00
#SBATCH --error $pdb_outdir/log_err.txt
#SBATCH --output $pdb_outdir/log_out.txt
#SBATCH --mem=1000

$cmd
""")
# The run_script_templ is template for you cluster submission script (using Python string.Template formatting)


#On a standalone computer
#1. Remove or comment out the cluster_submission_command and run_script_templ
#2. Uncomment the following lines
# run_script_templ = Template("""#!/bin/bash
# #
# echo $job_name
# $cmd &>$pdb_outdir/log&
# """)

Based on the above parameter file, Efitter will run five fitting runs - one for each structure. You can run these as five independent jobs on a computer cluster or standalone workstation.
To run on a computer cluster, adjust the cluster_submission_command and run_script_templ to the queuing system on your cluster (the provided example would work only on a Slurm cluster). It is important that you include $job_name, $pdb_outdir, and $cmd in your script template.
To run on a standalone workstation, remove or comment out cluster_submission_command and replace the run_script_templ with
run_script_templ = Template("""#!/bin/bash # echo $job_name $cmd &>$pdb_outdir/log& """)