modeller_usage October 2016

modeller_usage@salilab.org

8 participants
7 discussions

energy of interface between selections
by David De Sancho 02 Nov '16

02 Nov '16

Hi I’m handling a problem where it is important to evaluate energies of interfacial residues (e.g. interface residues between two helices in a protein). In order to carry out this energy evaluation with Modeller, I start by producing a model for the protein. Then I generate two selections (e.g. one for each helix). Would it be possible to calculate the energy for residues in the interface between both selections? Thanks, David

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how to make PIR file
by Nikhil Maroli 29 Oct '16

29 Oct '16

Dear all, I'm a new user of the modeller.I have a protein fast sequence and template protein PDB as well as fasta. I couldn't understand how I should make PIR file for the input? I have to make it manually by copying fasta sequence and editing required fields or is there any other method available ? -- Regards, Nikhil Maroli

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Unable to run parallel job
by Del Genio, Charo 26 Oct '16

26 Oct '16

Dear all, I'm trying to run a parallel job with modeller. The script is from modeller import * from modeller.automodel import * from modeller import soap_protein_od j = job() for i in range(16) j.append(local_slave()) log.verbose() env.io.atom_files_directory = ['.', '../atom_files'] a = dopehr_loopmodel(env, alnfile='OurAlignment.ali', knows='2p1mB', sequence='Rece', assess_methods=(assess.DOPEHR, soap_protein_od.Scorer(), assess.GA341), loop_assess_methods=assess.DOPEHR) a.starting_model = 1 a.ending_model = 16 a.loop.starting_model = 1 a.loop.ending_model = 10 a.use_parallel_job(j) a.make() However, it doesn't seem to work properly. In particular, it creates 16 slave output files containing exclusively 'import site' failed and then it hangs there, doing nothing at all, until I kill it with CTRL-C. What am I doing wrong? For sake of completeness, I'm running modeller 9.17, the distribution is Gentoo Linux, and single-CPU runs of modeller work fine without problems (so far). Thanks!

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sequence of salign/align2d
by Evelyne Deplazes 24 Oct '16

24 Oct '16

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Modeller query
by deepak kumar 24 Oct '16

24 Oct '16

Dear All, I am using modeller for the first time. Before mentioning the problems I am facing, please allow me to mention my goals to be performed by modeller. I already have a BLAST generated fasta alignment file. I need to convert the fasta alignment to PIR format, and generate the comparative model. May I please request you to let me know how this goal can be achieved. Moreover, after installing the modeller tarball package for ubuntu x86_64, when running the script to convert the fasta alignment to PIR I get this error. /media/deepak/modeller/bin/modpy.sh python modeller.py Traceback (most recent call last): File "modeller.py", line 2, in <module> from modeller import * File "/media/deepak/Nourhan/deepak_research2016/NM_005343_NM_002880_RAS_RAF/modeller.py", line 3, in <module> env = environ() NameError: name 'environ' is not defined *modeller.py*: import sys, os from modeller import * env = environ() a = alignment(env, file='NM_005343-native-protein.fasta', alignment_format='FASTA') a.write(file='NM_005343-native-protein.pir', alignment_format='PIR') Thank you so much for your time and consideration. Sincerely, Deepak _____________ Researcher, Carnegie Mellon University, Computational Biology Department

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usage of and sequence of commands for salign instead of align2d
by Evelyne Deplazes 22 Oct '16

22 Oct '16

Hi I want to make a homology model using the .pdb structure of a template and a target sequence (that is very similar to the template) I have previosly used align2d (see script align2d_old.py below) to prepare homology models. but the current sequences are very long (a pentamer with 573 aa per chain) and align2d was taking a very long time (hours). so I wanted to use salign. based on what I read in tutorials and forums I am however rather confused about the sequence of scritpts/commands to use Essentially, I have three questions: - what is the sequence of scripts / commands to use? do I first use salign to prepare an alignment and then align2d (or salign that emulates align2d). - what is the purpose of first using salign and then align2d ? - in the previous scripts of align2d the .pdb file was used as an input. in the new scripts that I used the .pdb file does not seem to be used. so how is the known structure of the template taken in to consideration for the alignment? Also, if no .pdb file is used then the generated alignment file does not contain information /reference to the structure file. consequently the scritpt model_build.py that I use will complain about not finding the structure information the scripts I have previously used (align2d_old.py) and the ones I tried to use now are below. name of template: Glinker (known sequence and structure (pdb)) name of target: GSAlinker (known sequence ) thanks Evelyne ************************************************************* # profile-profile alignment using salign # based on salign_profile_profile.py # on https://salilab.org/modeller/9v7/manual/node288.html from modeller import * log.level(1, 0, 1, 1, 1) env = environ() aln = alignment(env, file='HA1onCtermVP1dc63_Glinker_GSAlinker.fasta', alignment_format='FASTA') aln.salign(rr_file='${LIB}/blosum62.sim.mat', gap_penalties_1d=(-500, 0), output='', align_block=2, # no. of seqs. in first MSA align_what='PROFILE', alignment_type='PAIRWISE', comparison_type='PSSM', # or 'MAT' (Caution: Method NOT benchmarked # for 'MAT') similarity_flag=True, # The score matrix is not rescaled substitution=True, # The BLOSUM62 substitution values are # multiplied to the corr. coef. #write_weights=True, #output_weights_file='test.mtx', # optional, to write weight matrix smooth_prof_weight=10.0) # For mixing data with priors #write out aligned profiles (MSA) aln.write(file='HA1onCtermVP1dc63_Glinker_GSAlinker.ali', alignment_format='PIR') # Make a pairwise alignment of two sequences aln = alignment(env, file='HA1onCtermVP1dc63_Glinker_GSAlinker.ali', alignment_format='PIR', align_codes=('HA1onCtermVP1dc63_Glinker', 'HA1onCtermVP1dc63_GSAlinker')) aln.write(file='HA1onCtermVP1dc63_Glinker_GSAlinker_pair.ali', alignment_format='PIR') aln.write(file='HA1onCtermVP1dc63_Glinker_GSAlinker_pair.pap', alignment_format='PAP') ************************************************************** ************************************************************** # based on example on salign_align2d.py # on https://salilab.org/modeller/9v7/manual/node288.html # align2d/align using salign # parameters to be input by the user # 1. gap_penalties_1d # 2. gap_penalties_2d # 3. input alignment file from modeller import * log.verbose() env = environ() env.io.atom_files_directory = ['../atom_files'] aln = alignment(env, file='HA1onCtermVP1dc63_Glinker_GSAlinker_pair.ali', align_codes='all') aln.salign(rr_file='$(LIB)/as1.sim.mat', # Substitution matrix used output='', max_gap_length=20, gap_function=True, # If False then align2d not done feature_weights=(1., 0., 0., 0., 0., 0.), gap_penalties_1d=(-450, -50), gap_penalties_2d=(3.5, 3.5, 3.5, 0.2, 4.0, 6.5, 2.0, 0.0, 0.0), # d.p. score matrix #write_weights=True, output_weights_file='salign.mtx' similarity_flag=True) # Ensuring that the dynamic programming # matrix is not scaled to a difference matrix aln.write(file='HA1onCtermVP1dc63_Glinker_GSAlinker_align2d.ali', alignment_format='PIR' , alignment_features=' INDICES CONSERVATION ACCURACY HELIX BETA') aln.write(file='HA1onCtermVP1dc63_Glinker_GSAlinker_align2d.pap', alignment_format='PAP' , alignment_features=' INDICES CONSERVATION ACCURACY HELIX BETA') ************************************************************** ************************************************************** from modeller import * log.verbose() # create evironment and new alignment env = environ() aln = alignment(env) # create a model for the template HA1onCtermVP1dc63_Glinker mdl = model(env, file='HA1onCtermVP1dc63_Glinker', model_segment=('FIRST:A','LAST:E')) aln.append_model(mdl, align_codes='HA1onCtermVP1dc63_Glinker', atom_files='HA1onCtermVP1dc63_Glinker.pdb') # create a model for the target HA1onCtermVP1dc63_GSAlinker aln.append(file='HA1onCtermVP1dc63_GSAlinker.ali', align_codes='HA1onCtermVP1dc63_GSAlinker') aln.align2d() aln.write(file='HA1onCtermVP1dc63_Glinker_HA1onCtermVP1dc63_GSAlinker.ali', alignment_format='PIR') aln.write(file='HA1onCtermVP1dc63_Glinker_HA1onCtermVP1dc63_GSAlinker.pap', alignment_format='PAP') ************************************************************** ED Evelyne Deplazes Reply all| Today, 11:15 AM modeller_usage(a)salilab.org Sent Items Hi I want to make a homology model using the .pdb structure of a template and a target sequence (that is very similar to the template) I have previosly used align2d (see script align2d_old.py below) to prepare homology models. but the current sequences are very long (a pentamer with 573 aa per chain) and align2d was taking a very long time (hours). so I wanted to use salign. based on what I read in tutorials and forums I am however rather confused about the sequence of scritpts/commands to use Essentially, I have three questions: - what is the sequence of scripts / commands to use? do I first use salign to prepare an alignment and then align2d (or salign that emulates align2d). - what is the purpose of first using salign and then align2d ? - in the previous scripts of align2d the .pdb file was used as an input. in the new scripts that I used the .pdb file does not seem to be used. so how is the known structure of the template taken in to consideration for the alignment? the scripts I have previously used and the ones I now use are below. name of template: Glinker (known sequence and structure (pdb)) name of target: GSAlinker (known sequence ) thanks Evelyne ************************************************************* # profile-profile alignment using salign # based on salign_profile_profile.py # on https://salilab.org/modeller/9v7/manual/node288.html from modeller import * log.level(1, 0, 1, 1, 1) env = environ() aln = alignment(env, file='HA1onCtermVP1dc63_Glinker_GSAlinker.fasta', alignment_format='FASTA') aln.salign(rr_file='${LIB}/blosum62.sim.mat', gap_penalties_1d=(-500, 0), output='', align_block=2, # no. of seqs. in first MSA align_what='PROFILE', alignment_type='PAIRWISE', comparison_type='PSSM', # or 'MAT' (Caution: Method NOT benchmarked # for 'MAT') similarity_flag=True, # The score matrix is not rescaled substitution=True, # The BLOSUM62 substitution values are # multiplied to the corr. coef. #write_weights=True, #output_weights_file='test.mtx', # optional, to write weight matrix smooth_prof_weight=10.0) # For mixing data with priors #write out aligned profiles (MSA) aln.write(file='HA1onCtermVP1dc63_Glinker_GSAlinker.ali', alignment_format='PIR') # Make a pairwise alignment of two sequences aln = alignment(env, file='HA1onCtermVP1dc63_Glinker_GSAlinker.ali', alignment_format='PIR', align_codes=('HA1onCtermVP1dc63_Glinker', 'HA1onCtermVP1dc63_GSAlinker')) aln.write(file='HA1onCtermVP1dc63_Glinker_GSAlinker_pair.ali', alignment_format='PIR') aln.write(file='HA1onCtermVP1dc63_Glinker_GSAlinker_pair.pap', alignment_format='PAP') ************************************************************** ************************************************************** # based on example on salign_align2d.py # on https://salilab.org/modeller/9v7/manual/node288.html # align2d/align using salign # parameters to be input by the user # 1. gap_penalties_1d # 2. gap_penalties_2d # 3. input alignment file from modeller import * log.verbose() env = environ() env.io.atom_files_directory = ['../atom_files'] aln = alignment(env, file='HA1onCtermVP1dc63_Glinker_GSAlinker_pair.ali', align_codes='all') aln.salign(rr_file='$(LIB)/as1.sim.mat', # Substitution matrix used output='', max_gap_length=20, gap_function=True, # If False then align2d not done feature_weights=(1., 0., 0., 0., 0., 0.), gap_penalties_1d=(-450, -50), gap_penalties_2d=(3.5, 3.5, 3.5, 0.2, 4.0, 6.5, 2.0, 0.0, 0.0), # d.p. score matrix #write_weights=True, output_weights_file='salign.mtx' similarity_flag=True) # Ensuring that the dynamic programming # matrix is not scaled to a difference matrix aln.write(file='HA1onCtermVP1dc63_Glinker_GSAlinker_align2d.ali', alignment_format='PIR' , alignment_features=' INDICES CONSERVATION ACCURACY HELIX BETA') aln.write(file='HA1onCtermVP1dc63_Glinker_GSAlinker_align2d.pap', alignment_format='PAP' , alignment_features=' INDICES CONSERVATION ACCURACY HELIX BETA') ************************************************************** ************************************************************** #model_build.py from modeller import * from modeller.automodel import * env = environ() a = automodel(env, alnfile='HA1onCtermVP1dc63_Glinker_GSAlinker_pair.ali', knowns='HA1onCtermVP1dc63_Glinker', sequence='HA1onCtermVP1dc63_GSAlinker', assess_methods=(assess.DOPE, assess.GA341)) a.starting_model = 1 a.ending_model = 5 a.make() ************************************************************** ************************************************************** #align2d_old.py from modeller import * log.verbose() # create evironment and new alignment env = environ() aln = alignment(env) # create a model for the template HA1onCtermVP1dc63_Glinker mdl = model(env, file='HA1onCtermVP1dc63_Glinker', model_segment=('FIRST:A','LAST:E')) aln.append_model(mdl, align_codes='HA1onCtermVP1dc63_Glinker', atom_files='HA1onCtermVP1dc63_Glinker.pdb') # create a model for the target HA1onCtermVP1dc63_GSAlinker aln.append(file='HA1onCtermVP1dc63_GSAlinker.ali', align_codes='HA1onCtermVP1dc63_GSAlinker') aln.align2d() aln.write(file='HA1onCtermVP1dc63_Glinker_HA1onCtermVP1dc63_GSAlinker.ali', alignment_format='PIR') aln.write(file='HA1onCtermVP1dc63_Glinker_HA1onCtermVP1dc63_GSAlinker.pap', alignment_format='PAP') **************************************************************

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Restrain Uses in MODELLER v.91.6
by Sushil Mishra 04 Oct '16

04 Oct '16

Hi, I am trying to model a protein with certain distance restraints and disulphide bonds. I wonder why restraint does not work when I set disulphide bonds. My script looks like. --------------------------------------------- from modeller import * from modeller.automodel import * # Load the automodel class import sys log.verbose() env = environ() env.io.hetatm = True env.schedule_scale = physical.values(default=1.0, soft_sphere=0.7) # directories for input atom files env.io.atom_files_directory = ['.', '../atom_files'] class MyModel(automodel): def special_restraints(self, aln): rsr = self.restraints at = self.atoms # Residues to be an alpha helix: rsr.add(secondary_structure.alpha(self.residue_range('1:', '22:'))) rsr.add(secondary_structure.alpha(self.residue_range('26:', '32:'))) rsr.add(forms.gaussian(group=physical.xy_distance, feature=features.distance(at['CA:1'], at['CA:269']), mean=4.0, stdev=4.0)) def special_patches(self, aln): # A disulfide between residues X and Y: self.patch(residue_type='DISU', residues=(self.residues['113'], self.residues['117'])) self.patch(residue_type='DISU', residues=(self.residues['125'], self.residues['175'])) self.patch(residue_type='DISU', residues=(self.residues['313'], self.residues['337'])) self.patch(residue_type='DISU', residues=(self.residues['24'], self.residues['314']))a = MyModel(env, alnfile = 'seq.ali', # alignment filename knowns = ('XYZ','ABC'), # codes of the templates sequence = 'prot', assess_methods=(assess.DOPE, assess.GA341)) # code of the target a.starting_model= 1 # index of the first model a.ending_model = 20 # index of the last model # (determines how many models to calculate) a.library_schedule = autosched.fast # Very thorough VTFM optimization a.max_var_iterations = 100 a.md_level = refine.fast # Thorough MD optimization a.repeat_optimization = 1 # Repeat the whole cycle 2 times and.. a.max_molpdf = 1e6 # do not stop unless obj.func. > 1E6 #a.use_parallel_job(j) # Use the job for model building a.make() ------------------------------------------------------- If I comment distance restraint seems to work okay. What can be the reason that it does not work with S-S restraints. Moreover, Is there a way to control force constant for harmonic restraints in such cases ? Best, SM

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modeller_usage October 2016