3. Refinement

Refine the top-scoring models from previous modelling modes/runs

1. Enter your main project directory (where your X_config.json is)

2. Prepare a template JSON file for refinement

   gen_refinement_template.py --out_json refine_template.json --params params.py X_config.json
   

3. Modify the template according to your needs, e.g.:

   1. Add restraints specific for the refinement

   2. Change weights of restraints

   3. Re-define the rigid bodies

   4. Add extra subunits and their PDB files

   See JSON setup in the Elongator tutorial for an example.

4. Create a params_refine.py file as in Parameter file but now with the refine protocol and adjusting the scoring function and other settings, as appropriate for your case.

   See params set up in the Elongator tutorial for an example.

Refine a single model

1. Set up a refinement directory

   model_id=0014032model
   setup_refine.py \
       --model $model_id \
       --previous_json X_config.json \
       --refine_json_template refine_template.json \
       --refine_json_outname refine.json \
       --previous_outdir <output directory of the denovo run>/\
       --refine_outdir <desired output directory for the refinement, e.g. out/refinement>
   

   The script will create a new refinement directory and copy all input files there.

2. Perform test run

   mkdir -p <desired output directory for the refinement>/$model_id/testout
   assembline.py \
       --traj \
       --models \
       -o <desired output directory for the refinement>/$model_id/testout \
       --prefix refine_"$model_id"_000000 \
       <desired output directory for the refinement>/$model_id/refine.json \
       params_refine.py
   

3. Run

   assembline.py \
       --traj \
       --models \
       -o <desired output directory for the refinement>/$model_id/out \
       --multi \
       --start_idx 0 \
       --njobs 3 \
       --prefix refine_"$model_id" \
       <desired output directory for the refinement>/$model_id/refine.json \
       params_refine.py
   

Refine multiple models

1. Set up a refinement directory

   setup_refine.py \
       --top 10 \
       --scores <output directory of the denovo run>/all_scores_uniq.csv \
       --previous_json X_config.json \
       --refine_json_template refine_template.json \
       --refine_json_outname refine.json \
       --previous_outdir <output directory of the denovo run>/\
       --refine_outdir <desired output directory for the refinement, e.g. out/refinement>
   

2. Run recursively:

   If the output directory for the refinement was defined above as out/refinement:

   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"/refine.json \
               params_refine.py
       done