In order to generate hundreds of PDBs, I submit multiple jobs to the cluster. The input template is the same for all the jobs. For each job (i.e. each batch), 10 PDBs are generated. The 10 PDBs within the same batch are different in their "Objective Function" in the PDB remark. But the PDBs between the batches have the same "Objective Function".
) the 3rd PDB in Batch 1 has the same "Objective Function" as the 3rd PDB in Batch 5
) the 6th PDB in Batch 2 has the same "Objective Function" as the 6th PDB in Batch 10
So it seems that all the jobs are started from a same "seed". Is there a way to randomise the seed?
from modeller import *
from modeller.automodel import * # Load the automodel class
log.verbose()
class MyModel(automodel):
def special_patches(self, aln):
# Rename both chains and renumber the residues in each
self.rename_segments(segment_ids=['A', 'B', 'C', 'D','E', 'F','G', 'H','I', 'J','K', 'L','N', 'O','M', 'P','Q', 'R','S', 'U','V', '1','2', '3','4', '5','6', '7','8', '9',],
renumber_residues=[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
# Another way to label individual chains:
self.chains[0].name = 'A'
self.chains[1].name = 'B'
self.chains[2].name = 'C'
self.chains[3].name = 'D'
self.chains[4].name = 'E'
self.chains[5].name = 'F'
self.chains[6].name = 'G'
self.chains[7].name = 'H'
self.chains[8].name = 'I'
self.chains[9].name = 'J'
self.chains[10].name = 'K'
self.chains[11].name = 'L'
self.chains[12].name = 'N'
self.chains[13].name = 'O'
self.chains[14].name = 'M'
self.chains[15].name = 'P'
self.chains[16].name = 'Q'
self.chains[17].name = 'R'
self.chains[18].name = 'S'
self.chains[19].name = 'U'
self.chains[20].name = 'V'
self.chains[21].name = '1'
self.chains[22].name = '2'
self.chains[23].name = '3'
self.chains[24].name = '4'
self.chains[25].name = '5'
self.chains[26].name = '6'
self.chains[27].name = '7'
self.chains[28].name = '8'
self.chains[29].name = '9'
env = environ()
# directories for input atom files
env.io.atom_files_directory = ['.', '../atom_files']
# Be sure to use 'MyModel' rather than 'automodel' here!
a = MyModel(env,
alnfile = '../../1_raw/JN254802-5tx1.ali' , # alignment filename
knowns = '5tx1', # codes of the templates
sequence = 'JN254802') # code of the target
a.starting_model= 1 # index of the first model
a.ending_model = 10 # index of the last model
# (determines how many models to calculate)
a.make() # do comparative modeling