Clustering multiple fits in a cryoEM map
A. Input files:
1. EM
density map (xplor or mrc format).
2. A file that contains the list of the pdb files representing different fits for scoring and clustering. For example: “list_pdbs.txt”.
3. A
sub-directory that contains all the
above pdb files representing different fits (for example: "final").
4. Download the following
scripts:
B. Edit the following files:
run_score.py (below INPUT PARAMETERS):
1. Set the input parameters of
the EM map (MRC or XPLOR format). Make sure that the origin is specified in Å.
2.
Specify the path of your work directory.
3.
Specify the name of your results directory (eg, results_dir
= 'final/').
C.
Scoring:
Score the different fits using MODELLER/Mod-EM
(CCF, stereo-chemical and
non-bonded interactions terms) by running the following
command:
mod9v7 run_score.py > runs_score.log
D. Processing:
Prepare the file used for clustering (list_pdb_score):
python process.py
output files:
- score_sum.txt - a
complete summary
of the scores
- list_pdb_score - a
reduced list of
the scores
E.
Clustering:
Cluster the fits based on Cα
RMSD (starting from the best scoring model)
using the following command:
mod9v7 cluster.py list_pdb_score cutoff_rmsd score_column
Parameters to set:
- cutoff_rmsd - the Cα
RMSD cutoff based on which you want to cluster the solutions. For
example ‘3.5’ (for 3.5 Å).
- score_column - the column in
"list_pdb_score" based on which we order the clustering
(use ‘2’ for total energy or ‘6’ for CCF only). For
example:
mod9v7
cluster.py list_pdb_score 3.5 2
output file:
classes.txt
- the file is self
explanatory (the lrms
column is the Cα
RMSD of each fit from the first fit
in its class).