Hello Ben thank you for your kind update: ). In my case which tutorial should I follow for this loop refinement: 1. ) Modeling with cryo-EM Step 7: Refine models with loop modeling or, 2. ) Loop refining The loop optimization method relies on
Hello Ben thank you for your kind update:).
In my case which tutorial should I follow for this loop refinement:
1.)
Modeling with cryo-EM
Step 7: Refine models with loop modeling
or,
2.)
Loop refining
The loop optimization method relies on a scoring function and optimization schedule adapted for loop modeling. It is used automatically to refine comparative models if you use the LoopModel class rather than AutoModel; see the example below.# Loop refinement of an existing model
from modeller import *
from modeller.automodel import *
log.verbose()
env = Environ()
# directories for input atom files
env.io.atom_files_directory = ['.', '../atom_files']
# Create a new class based on 'LoopModel' so that we can redefine
# select_loop_atoms (necessary)
class MyLoop(LoopModel):
# This routine picks the residues to be refined by loop modeling
def select_loop_atoms(self):
# 10 residue insertion
return Selection(self.residue_range('273:A', '283:A'))
m = MyLoop(env,
inimodel='TvLDH-mult.pdb', # initial model of the target
sequence='TvLDH') # code of the target
m.loop.starting_model= 1 # index of the first loop model
m.loop.ending_model = 10 # index of the last loop model
m.loop.md_level = refine.very_fast # loop refinement method; this yields
# models quickly but of low quality;
# use refine.slow for better models
m.make() or should I try both?
Thanks:)
Joel 🚀