Run

This shows how to refine top all models, running three refinement runs for each model.

1. I you haven’t yet, activate the environment before using the software by

   source activate Assembline
   

   or depending on your computer setup:

   conda activate Assembline
   

2. Enter the main project directory

3. Setup a refinement directory to refine all 1000 models from the global optimization

   setup_refine.py \
       --scores out/all_scores.csv \
       --previous_json elongator.json \
       --refine_json_template elongator_refine_template.json \
       --refine_json_outname elongator_refine.json \
       --previous_outdir out/\
       --refine_outdir out/refinement
   

   This will create a directory out/refinement, which will contain 1000 sub-directories. Each of the subdirectories contains input files for refining each of the 1000 scoring models. The input files include PDB files oriented as in the models and JSON files for referring to those PDB files.

4. Run a test

   model_id=`ls --color=never out/refinement | head -n 1`
   assembline.py --traj --models --prefix 0000000 -o out/refinement/"$model_id"/out out/refinement/"$model_id"/elongator_refine.json params_refine.py
   rm -r out/refinement/"$model_id"/out
   

5. Refine the 1000 models, running 3 refinement runs for each model (3000 runs in total).

   For example like this:

   for model_id in `ls --color=never out/refinement`;
       do
           echo $model_id
           assembline.py --models -o out/refinement/"$model_id"/out --multi --start_idx 0 --njobs 3 --prefix refine_"$model_id" out/refinement/"$model_id"/elongator_refine.json params_refine.py
       done
   

   This will navigate to all subdirectories of the out/refinement and run the refinements there. Note no --traj option to save disk space.