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[modeller_usage] question about unusual bond length, bond angle, Chirality deviations



 Dear Modeller users

I generated the dimer by Modeller.
Fasta sequence number of model(400) is 70 less than Fasta sequence number of template(470).
Sequence identity between template and model is 24%.

after selecting the template, I aligned them, and then I did loop modeling. (I attached the code at the bottom.) Finally I got final pdb structure, but when I checked my model, I found the below warning message.

"Unusual bond length, unusual bond angle, Chirality deviations "

I am a beginner, so I don't what should I do to correct above warning message.
Please help me, Any suggestions or comments are welcomed.
Thanks.

Hyun.



---align2d.py----
from modeller import *

env = environ()
aln = alignment(env)
mdl = model(env, file='****', model_segment=('FIRST:A','LAST:B'))
aln.append_model(mdl, align_codes='******', atom_files='*****')
aln.append(file='******.ali', align_codes='*****')
aln.align2d()
aln.write(file='**************.ali', alignment_format='PIR')
aln.write(file='**************.pap', alignment_format='PAP')

---model-loop.py-----
# Homology modeling by the automodel class
from modeller import *
from modeller.automodel import *    # Load the automodel class

log.verbose()
env = environ()

# directories for input atom files
env.io.atom_files_directory = ['.', '../atom_files']

a = loopmodel(env,
              alnfile  = '***************.ali',     # alignment filename
              knowns   = '*******',              # codes of the templates
              sequence = '******')              # code of the target
a.starting_model= 1                 # index of the first model
a.ending_model  = 1                 # index of the last model
                                    # (determines how many models to calculate)
a.md_level = None                   # No refinement of model

a.loop.starting_model = 1           # First loop model
a.loop.ending_model   = 50           # Last loop model
a.loop.md_level       = refine.fast # Loop model refinement level

a.make()                            # do homology modeling