- modeller_usage - salilab.org

How to override the build_seq() command in loopmodel class
by Abhijit Muley 21 Mar '14

21 Mar '14

I am having knots in my structure, same problem as this person had- http://salilab.org/archives/modeller_usage/2005/msg00394.html I went through the manual but could not find any specific part where such instructions have been mentioned (althought they could have been in some section I have missed). Can anyone please direct me to the appropriate resources to solve this problem?

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(no subject)
by Ankita Nagpal 17 Mar '14

17 Mar '14

hi I have just started using modeller with the help of tutorial example.In the aligning step when iam aligning 1bdm with TvLDH IAM getting error only 317 residue out of 318 contain atom of type CA .Can you plz help me out what is going wro <http://wrong.it/>ng

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Use some local alignments
by fakharian 15 Mar '14

15 Mar '14

Hi I want to build a model for my target protein base on a known template structure. And I have some target-template local alignments. I want to use(and force) these local alignments on known regions; and align other regions of target by MODELLER alignment functions such as align2d or salign. Can anyone suggest a method to perform this? Thank you.

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Select and remove atoms from automodel
by Ignacio Ibarra 04 Mar '14

04 Mar '14

Hello, Currently I am generating nucleic acid models using the MODELLER suite. I would like to remove the initial phosphate group declared in the first residue of each nucleic acid chain. Those atoms should not be present in real structures. I would like to do it without writing new text in the .lib files that are into the modlib folder I read about a pick_atoms() method in an older version of MODELLER, but it is not commented in the 9v11 manual ( http://binf.gmu.edu/software/MODELLER/node131.html) Is there something similar currently available for removing atoms from the model in the automodel or another class? Regards, Ignacio

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Alignment missing
by Paul Zair Leyva Miranda 25 Feb '14

25 Feb '14

Dear Modeller team, I need your quick suggestions and corrections on my scripts that I have been using to run on multiple computers. I am not getting any errors when I run the script3.py. But, when I compare the files .pap and .ali with other alignment servers like muscle, there are aminoacids missing in the alignment with Modeller. I don`t know where is the problem, if it is related to the alignmet with Modeller or if there is a problem in the script.py. Best regards. Paul Zair Leyva Miranda Laboratory of Molecular Modeling ESM-IPN

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Best workflow to modeling a disordered loop in a complicated structure
by Zachary W Carpenter 19 Feb '14

19 Feb '14

Hello, I have used modeller to attempt to model a loop region in a tetrameric structure. To speed up computational time I've started with just the dimer ( which I think also makes sense biologically ) and ran the following script with an .ali file I created. The region of interest is a disordered loop AA~399-417. Following this I used the evaluate model script to pick the best model, which I then used as the template input for the loop.py script. I run the loop.py script at many iterations and then when it finishes I take the top 20 models (out of 1000) by DOPE score and attempt to analyze them. Any advice on how I could improve my method would be great.. I really am at the edge of my understanding here. I've edited the name of the protein. I can include it as soon as I can verify that this can stay anonymous. Thanks!!! Scripts +files : First )using a template pdb and .ali file I made myself of the Dimer (BIO_headers in chimera and deletion of one dimer of the tetramer) Input : >P1;ABCD structureX:ABCD.pdb: 3 :A:+990:B:::-1.00:-1.00 --TSWSDRLQNAADMPANMDKHALKKYRREAYHRVFVNRSLAMEKIKCFGFNMDYTLAVYKSPEYESLGFELTVE RLVSIGYPQELLSFAYDSTFPTRGLVFDTLYGNLLKVDAYGNLLVCAHGFNFIRGPETREQYPNKFIQRDDTERF YILNTLFNLPETYLLACLVDFFTNCPRYTSCETGFKDGDLFMSYRSMFQDVRDAVDWVHYKGSLKEKTVENLEKY VVKDGKLPLLLSRMKEVGKVFLATNSDYKYTDKIMTYLFDFPHGPKPGSSHRPWQSYFDLILVDARKPLFFGEGT VLRQVDTKTGKLKIGTYTGPLQHGIVYSGGSSDTICDLLGAKGKDILYIGDHIFGDILKSKKRQGWRTFLVIPEL AQELHVWTDKSSLFEELQSLDIFLAS----------------SIQRRIKKVTHDMDMCYGMMGSLFRSGSRQTLF ASQVMRYADLYAASFINLLYYPFSYLFRAAHVLMPHES/--TSWSDRLQNAADMPANMDKHALKKYRREAYHRVFVNRSLAMEKIKCFGFNMDYTLAVYKSPEYESLGFELTVE RLVSIGYPQELLSFAYDSTFPTRGLVFDTLYGNLLKVDAYGNLLVCAHGFNFIRGPETREQYPNKFIQRDDTERF YILNTLFNLPETYLLACLVDFFTNCPRYTSCETGFKDGDLFMSYRSMFQDVRDAVDWVHYKGSLKEKTVENLEKY VVKDGKLPLLLSRMKEVGKVFLATNSDYKYTDKIMTYLFDFPHGPKPGSSHRPWQSYFDLILVDARKPLFFGEGT VLRQVDTKTGKLKIGTYTGPLQHGIVYSGGSSDTICDLLGAKGKDILYIGDHIFGDILKSKKRQGWRTFLVIPEL AQELHVWTDKSSLFEELQSLDIFLAS----------------SIQRRIKKVTHDMDMCYGMMGSLFRSGSRQTLF ASQVMRYADLYAASFINLLYYPFSYLFRAAHVLMPHES* >P1;X sequence:ABCD: : : : ::: 0.00: 0.00 MSTSWSDRLQNAADMPANMDKHALKKYRREAYHRVFVNRSLAMEKIKCFGFDMDYTLAVYKSPEYESLGFELTVE RLVSIGYPQELLSFAYDSTFPTRGLVFDTLYGNLLKVDAYGNLLVCAHGFNFIRGPETREQYPNKFIQRDDTERF YILNTLFNLPETYLLACLVDFFTNCPRYTSCETGFKDGDLFMSYRSMFQDVRDAVDWVHYKGSLKEKTVENLEKY VVKDGKLPLLLSRMKEVGKVFLATNSDYKYTDKIMTYLFDFPHGPKPGSSHRPWQSYFDLILVDARKPLFFGEGT VLRQVDTKTGKLKIGTYTGPLQHGIVYSGGSSDTICDLLGAKGKDILYIGDHIFGDILKSKKRQGWRTFLVIPEF AQELHVWTDKSSLFEELQSLDIFLAELYKHLDSSSNERPDISSIQRRIKKVTHDMDMCYGMMGSLFRSGSRQTLF ASQVMRYADLYAASFINLLYYPFSYLFRAAHVLMPHES/MSTSWSDRLQNAADMPANMDKHALKKYRREAYHRVFVNRSLAMEKIKCFGFDMDYTLAVYKSPEYESLGFELTVE RLVSIGYPQELLSFAYDSTFPTRGLVFDTLYGNLLKVDAYGNLLVCAHGFNFIRGPETREQYPNKFIQRDDTERF YILNTLFNLPETYLLACLVDFFTNCPRYTSCETGFKDGDLFMSYRSMFQDVRDAVDWVHYKGSLKEKTVENLEKY VVKDGKLPLLLSRMKEVGKVFLATNSDYKYTDKIMTYLFDFPHGPKPGSSHRPWQSYFDLILVDARKPLFFGEGT VLRQVDTKTGKLKIGTYTGPLQHGIVYSGGSSDTICDLLGAKGKDILYIGDHIFGDILKSKKRQGWRTFLVIPEF AQELHVWTDKSSLFEELQSLDIFLAELYKHLDSSSNERPDISSIQRRIKKVTHDMDMCYGMMGSLFRSGSRQTLF ASQVMRYADLYAASFINLLYYPFSYLFRAAHVLMPHES* # Homology modeling by the automodel class # # Demonstrates how to build multi-chain models, and symmetry restraints # from modeller import * from modeller.automodel import * # Load the automodel class log.verbose() # Override the 'special_restraints' and 'user_after_single_model' methods: class MyModel(automodel): def special_restraints(self, aln): # Constrain the A, B, C and D chains to be identical s1 = selection(self.chains['A']).only_atom_types('CA') s2 = selection(self.chains['B']).only_atom_types('CA') self.restraints.symmetry.append(symmetry(s1, s2, 1)) def user_after_single_model(self): # Report on symmetry violations greater than 1A after building # each model: self.restraints.symmetry.report(1) 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 = 'WT_dimer_NoCterm.ali' , # alignment filename knowns = 'ABCD', # codes of the templates sequence = 'ABCD') # 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.make() # do homology modeling # # class MyModel(automodel): 2nd) Run eval model and pick top model to use as input for the loop.py script 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('399:A', '417:A')) m = MyLoop(env, inimodel='ABCD_Top_Model.pdb', # initial model of the target sequence='ABCD') # code of the target m.loop.starting_model= 1 # index of the first loop model m.loop.ending_model = 1000 # index of the last loop model m.loop.md_level = refine.slow # loop refinement method; this yields # models quickly but of low quality; # use refine.slow for better models m.make() 3rd) Run model_energies script Then I rank them using this perl one liner ( just cats and displays the dope and the file ) can run in any unix terminal. cat model*.log |perl -lane' print if /DOPE\ score/ || /ABCD.BL/'| perl -pe 's/ +/\t/g'|perl -pe 's/:\t//g' |cut -f3,4|perl -pe 's/\n/\t/'|perl -pe 's/(\d)\t(ABCD)/$1\n$2/g'|sort -k2,2n|head -20 4) Take top 20 models and analyze Any help with where I'm doing things wrong or how I can improve would be awesome. How many models in loop.py would you recommend to get a good answer? Is there away to interpret the models created as a whole ....for example say something like "60% of the time residue A is next to residue B and 20% of the time its over in this pocket , therefor".... etc My major aim is to compare different ligand bound crystal states, or mutation states, and show that the models created are different between them. Then use this to design wet lab experiments to test. Thanks again

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Run Modeller on multiple cpu
by Lalith Kumar 17 Feb '14

17 Feb '14

Dear Modeller team, I need your quick suggestions and corrections on my scripts that I have been using to run on multiple cpus. I am not getting any errors, when I run the script parallel-task.py with python. But it is not utilizing multiple cpus. Can you please look in to the attached scripts and let me know where I might have went wrong. Please... Thank you lot Regards, Lalith

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Modeller 9.13 release
by Modeller Caretaker 12 Feb '14

12 Feb '14

The new version of Modeller, 9.13, is now available for download! Please see the download page at http://salilab.org/modeller/ for more information. If you have a license key for Modeller 8 or 9, there is no need to reregister for Modeller 9.13 - the same license key will work. (It won't do any harm to reregister if you want to, though!) 9.13 is primarily a bugfix release relative to the last public release (9.12). Major user-visible changes include: # Modeller now includes a variety of SOAP (statistically optimized atomic potential) scores for assessing proteins, loops, and interfaces. # The Lennard-Jones interaction energy is now artificially truncated at very short distance; this makes simulations with poor starting conditions much less likely to 'blow up'. # model.get_insertions(), model.get_deletions() and model.loops() now have an include_termini option; if False, residue ranges that include chain termini are excluded from the output. See the Modeller manual for a full change log: http://salilab.org/modeller/9.13/manual/node39.html If you encounter bugs in Modeller 9.13, please see http://salilab.org/modeller/9.13/manual/node10.html for information on how to report them. Note: you are receiving this email either because you subscribed to the modeller_usage mailing list, or you provided this address when you requested a Modeller license and you ticked the "notify me of new releases" box. In the latter case, if you no longer wish to receive announcements of new Modeller releases, simply reply to this email and let us know. Ben Webb, Modeller Caretaker -- modeller-care(a)salilab.org http://www.salilab.org/modeller/ Modeller mail list: http://salilab.org/mailman/listinfo/modeller_usage

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Reading heteroatoms
by Lucas 12 Feb '14

12 Feb '14

Dear all, I'm willing to model a protein containing zinc atoms, something I've done successfully before using earlier versions of modeller. The template has protein and two zinc ions in chain A, and so I added two dots in the end of my alignment sequences, but I get the "Number of residues in the alignment and pdb files are different" message (the difference is actually the two additional residues). The FAQ (question #17) suggests running a simple script to see what Modeller is reading from the PDB and, running it on PDB 1HRA, I get this: >P1;1hra structureX:1hra: 1 :A:+80 :A:MOL_ID 1; MOLECULE RETINOIC ACID RECEPTOR; CHAIN A; ENGINEERED YES:MOL_ID 1; ORGANISM_SCIENTIFIC HOMO SAPIENS; ORGANISM_COMMON HUMAN; ORGANISM_TAXID 9606:-1.00: -1.00 MPRVYKPCFVCQDKSSGYHYGVSACEGCKGFFRRSIQKNMIYTCHRDKNCVINKVTRNRCQYCRLQKCFEVGMSK ESVRN* I.e., for some reason modeller only reads the amino acids and not the two zinc ions, and the last two dots are missing. What should I do to read the heteroatoms? Lucas

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Best workflow to modeling a disordered loop in a complicated structure
by Zachary W Carpenter 11 Feb '14

11 Feb '14

Hello, I have used modeller to attempt to model a loop region in a tetrameric structure. To speed up computational time I've started with just the dimer ( which I think also makes sense biologically ) and ran the following script with an .ali file I created. The region of interest is a disordered loop AA~399-417. Following this I used the evaluate model script to pick the best model, which I then used as the template input for the loop.py script. I run the loop.py script at many iterations and then when it finishes I take the top 20 models (out of 1000) by DOPE score and attempt to analyze them. Any advice on how I could improve my method would be great.. I really am at the edge of my understanding here. I've edited the name of the protein. I can include it as soon as I can verify that this can stay anonymous. Thanks!!! Scripts +files : *First )using a template pdb and .ali file I made myself of the Dimer (BIO_headers in chimera and deletion of one dimer of the tetramer) * *Input : * >P1;ABCD structureX:ABCD.pdb: 3 :A:+990:B:::-1.00:-1.00 --TSWSDRLQNAADMPANMDKHALKKYRREAYHRVFVNRSLAMEKIKCFGFNMDYTLAVYKSPEYESLGFELTVE RLVSIGYPQELLSFAYDSTFPTRGLVFDTLYGNLLKVDAYGNLLVCAHGFNFIRGPETREQYPNKFIQRDDTERF YILNTLFNLPETYLLACLVDFFTNCPRYTSCETGFKDGDLFMSYRSMFQDVRDAVDWVHYKGSLKEKTVENLEKY VVKDGKLPLLLSRMKEVGKVFLATNSDYKYTDKIMTYLFDFPHGPKPGSSHRPWQSYFDLILVDARKPLFFGEGT VLRQVDTKTGKLKIGTYTGPLQHGIVYSGGSSDTICDLLGAKGKDILYIGDHIFGDILKSKKRQGWRTFLVIPEL AQELHVWTDKSSLFEELQSLDIFLAS----------------SIQRRIKKVTHDMDMCYGMMGSLFRSGSRQTLF ASQVMRYADLYAASFINLLYYPFSYLFRAAHVLMPHES/--TSWSDRLQNAADMPANMDKHALKKYRREAYHRVFVNRSLAMEKIKCFGFNMDYTLAVYKSPEYESLGFELTVE RLVSIGYPQELLSFAYDSTFPTRGLVFDTLYGNLLKVDAYGNLLVCAHGFNFIRGPETREQYPNKFIQRDDTERF YILNTLFNLPETYLLACLVDFFTNCPRYTSCETGFKDGDLFMSYRSMFQDVRDAVDWVHYKGSLKEKTVENLEKY VVKDGKLPLLLSRMKEVGKVFLATNSDYKYTDKIMTYLFDFPHGPKPGSSHRPWQSYFDLILVDARKPLFFGEGT VLRQVDTKTGKLKIGTYTGPLQHGIVYSGGSSDTICDLLGAKGKDILYIGDHIFGDILKSKKRQGWRTFLVIPEL AQELHVWTDKSSLFEELQSLDIFLAS----------------SIQRRIKKVTHDMDMCYGMMGSLFRSGSRQTLF ASQVMRYADLYAASFINLLYYPFSYLFRAAHVLMPHES* >P1;X sequence:ABCD: : : : ::: 0.00: 0.00 MSTSWSDRLQNAADMPANMDKHALKKYRREAYHRVFVNRSLAMEKIKCFGFDMDYTLAVYKSPEYESLGFELTVE RLVSIGYPQELLSFAYDSTFPTRGLVFDTLYGNLLKVDAYGNLLVCAHGFNFIRGPETREQYPNKFIQRDDTERF YILNTLFNLPETYLLACLVDFFTNCPRYTSCETGFKDGDLFMSYRSMFQDVRDAVDWVHYKGSLKEKTVENLEKY VVKDGKLPLLLSRMKEVGKVFLATNSDYKYTDKIMTYLFDFPHGPKPGSSHRPWQSYFDLILVDARKPLFFGEGT VLRQVDTKTGKLKIGTYTGPLQHGIVYSGGSSDTICDLLGAKGKDILYIGDHIFGDILKSKKRQGWRTFLVIPEF AQELHVWTDKSSLFEELQSLDIFLAELYKHLDSSSNERPDISSIQRRIKKVTHDMDMCYGMMGSLFRSGSRQTLF ASQVMRYADLYAASFINLLYYPFSYLFRAAHVLMPHES/MSTSWSDRLQNAADMPANMDKHALKKYRREAYHRVFVNRSLAMEKIKCFGFDMDYTLAVYKSPEYESLGFELTVE RLVSIGYPQELLSFAYDSTFPTRGLVFDTLYGNLLKVDAYGNLLVCAHGFNFIRGPETREQYPNKFIQRDDTERF YILNTLFNLPETYLLACLVDFFTNCPRYTSCETGFKDGDLFMSYRSMFQDVRDAVDWVHYKGSLKEKTVENLEKY VVKDGKLPLLLSRMKEVGKVFLATNSDYKYTDKIMTYLFDFPHGPKPGSSHRPWQSYFDLILVDARKPLFFGEGT VLRQVDTKTGKLKIGTYTGPLQHGIVYSGGSSDTICDLLGAKGKDILYIGDHIFGDILKSKKRQGWRTFLVIPEF AQELHVWTDKSSLFEELQSLDIFLAELYKHLDSSSNERPDISSIQRRIKKVTHDMDMCYGMMGSLFRSGSRQTLF ASQVMRYADLYAASFINLLYYPFSYLFRAAHVLMPHES* # Homology modeling by the automodel class # # Demonstrates how to build multi-chain models, and symmetry restraints # from modeller import * from modeller.automodel import * # Load the automodel class log.verbose() # Override the 'special_restraints' and 'user_after_single_model' methods: class MyModel(automodel): def special_restraints(self, aln): # Constrain the A, B, C and D chains to be identical s1 = selection(self.chains['A']).only_atom_types('CA') s2 = selection(self.chains['B']).only_atom_types('CA') self.restraints.symmetry.append(symmetry(s1, s2, 1)) def user_after_single_model(self): # Report on symmetry violations greater than 1A after building # each model: self.restraints.symmetry.report(1) 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 = 'WT_dimer_NoCterm.ali' , # alignment filename knowns = 'ABCD', # codes of the templates sequence = 'ABCD') # 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.make() # do homology modeling # # class MyModel(automodel): *2nd) Run eval model and pick top model to use as input for the loop.py script 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('399:A', '417:A')) m = MyLoop(env, inimodel='ABCD_Top_Model.pdb', # initial model of the target sequence='ABCD') # code of the target m.loop.starting_model= 1 # index of the first loop model m.loop.ending_model = 1000 # index of the last loop model m.loop.md_level = refine.slow # loop refinement method; this yields # models quickly but of low quality; # use refine.slow for better models m.make() *3rd) Run model_energies script* Then I rank them using this perl one liner ( just cats and displays the dope and the file ) can run in any unix terminal. cat model*.log |perl -lane' print if /DOPE\ score/ || /ABCD.BL/'| perl -pe 's/ +/\t/g'|perl -pe 's/:\t//g' |cut -f3,4|perl -pe 's/\n/\t/'|perl -pe 's/(\d)\t(ABCD)/$1\n$2/g'|sort -k2,2n|head -20 *4) Take top 20 models and analyze * Any help with where I'm doing things wrong or how I can improve would be awesome. How many models in loop.py would you recommend to get a good answer? Is there away to interpret the models created as a whole ....for example say something like "60% of the time residue A is next to residue B and 20% of the time its over in this pocket , therefor".... etc My major aim is to compare different ligand bound crystal states, or mutation states, and show that the models created are different between them. Then use this to design wet lab experiments to test. Thanks again

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