- modeller_usage - salilab.org

Alignment of the sequences
by piyush diyora 12 Apr '10

12 Apr '10

Hi, I am new to modeller. Before building a model, we have to first modify the sequence present in the PIR file. PDB file and PIR file may have few different sequences. So is there any way or software which can align both the sequences (from PDB file and PIR file) so that the sequence present in PIR can be modified. Thank you, Piyush Diyora

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generated models superimposition
by Белалов Илья 12 Apr '10

12 Apr '10

Dear Modeller Caretaker and Modeller users, I want Modeller to fit generated models by dope_loopmodel class. But only structures derived from the same IL000* file are superimposed to it. Also templates are aligned, but not to generated models. Thanks in advance, Ilya. I used following: class MyModel(dope_loopmodel): def special_patches(self, aln): self.patch(residue_type='DISU', residues=(self.residues['21'], self.residues['92'])) log.very_verbose() env = environ() env.io.atom_files_directory = ['.', '../'] a = MyModel(env, alnfile='../mulalignment.ali', knowns=('1', '2','3'), sequence='d6', assess_methods=assess.DOPE, loop_assess_methods=assess.DOPE) a.starting_model = 1 a.ending_model = 3 a.md_level = refine.very_fast a.loop.starting_model = 1 a.loop.ending_model = 3 a.loop.md_level = refine.very_fast a.final_malign3d = True a.make()

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dihedral phi psi restraint
by Armin Meier 12 Apr '10

12 Apr '10

Hi, in a Modeller-generated .rsr file, I have lines like this one: R 9 3 4 25 8 18 2 5 4 4 7 9 10 12 9 10 12 14 0.1295 0.3250 0.5455 -1.0908 -0.7138 -1.1903 2.5360 -2.3 3880 387 2.5656 0.0908 0.1065 0.2059 0.2164 0.5271 0.3072 -0.2541 3880 -0.4199 -0.6670 I suppose it's a restraint on phi-psi angles, but I cant find a description for Feature "4" (third number in first line) in the Modeller documentation (http://salilab.org/modeller/manual/node447.html) Moreover, why are there two features for this restraint (numb_feat=2) and what does Modal2 = 5 stand for? Are restraints of this type (i.e. Group=25, dihedral) always generated by default (Modeller version >= 9.5)? Thanks a lot in advance Armin Meier

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evaluation of a region with DOPE z-score
by Thomas Evangelidis 12 Apr '10

12 Apr '10

Dear Modeller Caretaker, I have generated several models with different template combinations and want select the best with regard to some regions of interest (i.e. the ATP binding site). In the case of the binding site my residue selection is not contiguous (roughly all residues within 10 A. from the ATP). Does the resulting score make sense? Also if you look into the profile plot you will notice that the line is also curved in regions outside the binding cavity, and that happens even if the residue selection is conti. I think DOPE score is affected by neighboring atoms. If that's true what's the best way to assess a model region? thanks, Tom PS: the class to evaluate the cavity is pasted below. from modeller import * from modeller.parallel import task from modeller.scripts import complete_pdb import os class Evaluate_Cavity(task): """A task to evaluate a model with the DOPEHR method""" def run(self, template_combination, i): log.minimal() # request minimal output env = environ() env.libs.topology.read(file='$(LIB)/top_heav.lib') # read topology env.libs.parameters.read(file='$(LIB)/par.lib') # read parameters # read model file mdl = complete_pdb(env, "/home/thomas2/Documents/PfMDR1_AAA1/new_alignment_"+template_combination+"/modeller/target.B999900"+str(i)+".pdb") # Select all residues except for the loop s = selection(mdl.residue_range('8', '20'), mdl.residue_range('34', '53'), mdl.residue_range('210', '212'), mdl.residue_range('242', '244'), mdl.residue_range('258', '261')) # Assess with DOPE: os.chdir("/home/thomas2/Documents/PfMDR1_AAA1/new_alignment_"+template_combination+"/modeller/") score = s.assess_dopehr(output='ENERGY_PROFILE NO_REPORT', file="model_"+str(i)+"_"+template_combination+".profile", normalize_profile=True, smoothing_window=15) return [str(i), score]

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Error when reading the alignment PIR file.
by Daniel Fernandez 12 Apr '10

12 Apr '10

Hi, Please help me if possible, I have been stuck few days by now :-( I am trying a very basic approach to use modeller, but in this case I am using my own global alignment from clustalW. I am trying a very basic protein, target: 1aho, and only one template 2kbh_A ClustalW outputs the alignment in PIR format ( http://www.bioinformatics.nl/tools/crab_pir.html) but is a different PIR format than the one required by modeller. Actually the main difference is that clustalW does not provide the *start residue*:*start chain code*:*endresidue :end chain code: parts.* I do not know how to get that information and modeller apparently does not know either. Here I copy and paste the clustalW PIR format, the PIR modeller format and the errors I get from the model_simple.log. *CLUSTALW PIR format - sequencealn.pir* >P1;1AHO_A|PDBID|CHAIN|SEQUENCE VKDGYIVDDVNCTYFCGRNAYCNEECTKLKGESGYCQWASPYGNACYCYK LPDHVRTKGPGRCH-- * >P1;2KBH_A|PDBID|CHAIN|SEQUENCE VKDGYIADDRNCPYFCGRNAYCDGECKKNRAESGYCQWASKYGNACWCYK LPDDARIMKPGRCNGG * *MODELLER INPUT (does not work, not sure why)* >P1;1aho sequence:1aho: : : : ::: 0.00: 0.0 VKDGYIVDDVNCTYFCGRNAYCNEECTKLKGESGYCQWASPYGNACYCYK LPDHVRTKGPGRCH--* >P1;2kbhA structureX:2kbh.pdb: : : : ::: 0.00: 0.0 VKDGYIADDRNCPYFCGRNAYCDGECKKNRAESGYCQWASKYGNACWCYK LPDDARIMKPGRCNGG* *ERROR MODELLER GIVES ME:* get_ran_648E> Alignment sequence not found in PDB file: 1 2kbh.pdb (You didn't specify the starting and ending residue numbers and chain IDs in the alignment, so Modeller tried to guess these fr the PDB file.) Suggestion: put in the residue numbers and chain IDs (see the manual) and run again for more detailed diagnostics. You could also try running with allow_alternates=True to accept alternate one-letter code matches (e.g. B to N, Z to Q). Traceback (most recent call last): File "hoModeller-clustalaln.py", line 14, in <module> a.make() # do the homollogy modelling File "/n/sw/modeller-9v7/modlib/modeller/automodel/automodel.py", line 98, self.homcsr(exit_stage) File "/n/sw/modeller-9v7/modlib/modeller/automodel/automodel.py", line 411, aln = self.read_alignment() File "/n/sw/modeller-9v7/modlib/modeller/automodel/automodel.py", line 401, aln.append(file=self.alnfile, align_codes=self.knowns+[self.sequence]) File "/n/sw/modeller-9v7/modlib/modeller/alignment.py", line 79, in append allow_alternates) _modeller.SequenceMismatchError: get_ran_648E> Alignment sequence not found i I am aware that the error advice me to put the start and ending residues numbers but I am still not sure how to solve the issue. Any help will be strongly appreciated, I need to use modeller as soon as possible to do some progress in my research. Best, -- Daniel F. Department of Statistics, Harvard University 1 Oxford Street, Cambridge, MA 02138

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Re: [modeller_usage] evaluation of a region with DOPE z-score
by Jan H. Löhr 12 Apr '10

12 Apr '10

Dear Tom, I am not sure if I understood your problem correctly, but I guess what you are referring to is the smoothing option (s.assess_dopehr (... smoothing_window=15)). I would try turning it off, so the displayed DOPEHR-value of a specific residue is not "affected by neighboring atoms". Hope this helps, Jan -----Ursprüngliche Nachricht----- Von: modeller_usage-bounces(a)salilab.org [mailto:modeller_usage-bounces@salilab.org] Im Auftrag von modeller_usage-request(a)salilab.org Gesendet: Montag, 12. April 2010 09:09 An: modeller_usage(a)salilab.org Betreff: modeller_usage Digest, Vol 9, Issue 52 Send modeller_usage mailing list submissions to modeller_usage(a)salilab.org To subscribe or unsubscribe via the World Wide Web, visit https://salilab.org/mailman/listinfo/modeller_usage or, via email, send a message with subject or body 'help' to modeller_usage-request(a)salilab.org You can reach the person managing the list at modeller_usage-owner(a)salilab.org When replying, please edit your Subject line so it is more specific than "Re: Contents of modeller_usage digest..." Today's Topics: 1. evaluation of a region with DOPE z-score (Thomas Evangelidis) 2. .aln files. (Daniel Fernandez) 3. Error when reading the alignment PIR file. (Daniel Fernandez) ---------------------------------------------------------------------- Message: 1 Date: Fri, 9 Apr 2010 14:31:35 +0100 From: Thomas Evangelidis <tevang3(a)gmail.com> Subject: [modeller_usage] evaluation of a region with DOPE z-score To: modeller_usage(a)salilab.org Message-ID: <r2p833e1faf1004090631n974f1e63j3c927a306ca71ebd(a)mail.gmail.com> Content-Type: text/plain; charset="iso-8859-1" Dear Modeller Caretaker, I have generated several models with different template combinations and want select the best with regard to some regions of interest (i.e. the ATP binding site). In the case of the binding site my residue selection is not contiguous (roughly all residues within 10 A. from the ATP). Does the resulting score make sense? Also if you look into the profile plot you will notice that the line is also curved in regions outside the binding cavity, and that happens even if the residue selection is conti. I think DOPE score is affected by neighboring atoms. If that's true what's the best way to assess a model region? thanks, Tom PS: the class to evaluate the cavity is pasted below. from modeller import * from modeller.parallel import task from modeller.scripts import complete_pdb import os class Evaluate_Cavity(task): """A task to evaluate a model with the DOPEHR method""" def run(self, template_combination, i): log.minimal() # request minimal output env = environ() env.libs.topology.read(file='$(LIB)/top_heav.lib') # read topology env.libs.parameters.read(file='$(LIB)/par.lib') # read parameters # read model file mdl = complete_pdb(env, "/home/thomas2/Documents/PfMDR1_AAA1/new_alignment_"+template_combination+"/ modeller/target.B999900"+str(i)+".pdb") # Select all residues except for the loop s = selection(mdl.residue_range('8', '20'), mdl.residue_range('34', '53'), mdl.residue_range('210', '212'), mdl.residue_range('242', '244'), mdl.residue_range('258', '261')) # Assess with DOPE: os.chdir("/home/thomas2/Documents/PfMDR1_AAA1/new_alignment_"+template_combi nation+"/modeller/") score = s.assess_dopehr(output='ENERGY_PROFILE NO_REPORT', file="model_"+str(i)+"_"+template_combination+".profile", normalize_profile=True, smoothing_window=15) return [str(i), score]

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.aln files.
by Daniel Fernandez 09 Apr '10

09 Apr '10

Hi, I am doing blastp to get the fasta sequences and then clustalW to do the alignment but clustalW gives me the alignment in .aln format. do you know how to give it to modeller. I think modeller only accepts PIR format. Thanks, -- Daniel F.

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build short 1000 olioopeptid from fasta file
by Knut J Bjuland 08 Apr '10

08 Apr '10

I have 1000 or more short peptid seqeunce which are 4 amino acid long. Can I use modeller to build them just as a linear structure without any 3d structure. Knut J

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Terminal Oxygens and Nitrogens
by abdullah ahmed 08 Apr '10

08 Apr '10

Dear Modeller users, I am using a modification of the optimize.py script to optimize a molecule. The original molecule does not have charged Nitrogens and oxygens at the terminals. The optimization procedure, however, seems to add charges to them. I would like to know if there is a way to optimize the structure and keep the terminals uncharged. Thank you in advance, Abdullah _________________________________________________________________ Hotmail: Trusted email with powerful SPAM protection. https://signup.live.com/signup.aspx?id=60969

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Restraints
by Offord, Victoria 08 Apr '10

08 Apr '10

Hi everybody, I am really hoping that I am not asking a dumb question but I cannot seem to get the restraints to work on my protein. To try and get to grips with this I am using a target-template sequence identity of 100%. I have set the secondary structure as is in the known structure but cannot seem to 'force' the restraints through onto the target. I have posted the script below. Any help on this would be very much appreciated! Many thanks in advance, Tory from modeller import * from modeller.automodel import * class MyModel(automodel): def special_restraints(self, aln): rsr = self.restraints # Addition of 3 disulphides: self.patch(residue_type='DISU', residues=(self.residues['43'],self.residues['62'])) #Residues 20 through 30 should be an alpha helix: rsr.add(secondary_structure.alpha(self.residue_range('20:', '37:'))) rsr.add(secondary_structure.alpha(self.residue_range('54:', '65:'))) rsr.add(secondary_structure.alpha(self.residue_range('75:', '89:'))) rsr.add(secondary_structure.alpha(self.residue_range('111:', '115:'))) rsr.add(secondary_structure.alpha(self.residue_range('119:', '128:'))) rsr.add(secondary_structure.alpha(self.residue_range('137:', '154:'))) #Two beta-strands: rsr.add(secondary_structure.strand(self.residue_range('13:', '18:'))) rsr.add(secondary_structure.strand(self.residue_range('42:', '43:'))) rsr.add(secondary_structure.strand(self.residue_range('66:', '73:'))) rsr.add(secondary_structure.strand(self.residue_range('102:', '106:'))) rsr.add(secondary_structure.strand(self.residue_range('132:', '133:'))) log.verbose() env = environ() # directories for input atom files env.io.atom_files_directory = ['.', '../../atom_files'] a = MyModel(env, alnfile='../tlr1_tir_template.ali', knowns='1fyv', sequence='hTLR1TIR', assess_methods=(assess.DOPE, assess.normalized_dope, assess.DOPEHR, assess.GA341)) a.starting_model = 1 a.ending_model = 100 # Very thorough VTFM optimization: a.library_schedule = autosched.slow a.max_var_iterations = 300 # Thorough MD optimization: a.md_level = refine.very_slow # Repeat the whole cycle 2 times and do not stop unless obj.func. > 1E6 a.repeat_optimization = 5 a.max_molpdf = 1e6 a.make() # Get a list of all successfully built models from a.outputs ok_models = filter(lambda x: x['failure'] is None, a.outputs) # Rank the models by DOPE score key = 'DOPE score' ok_models.sort(lambda a,b: cmp(a[key], b[key])) # Get top model m = ok_models[0] print "Top model 1: %s (DOPE score %.3f)" % (m['name'], m[key]) m = ok_models[1] print "Top model 2: %s (DOPE score %.3f)" % (m['name'], m[key]) m = ok_models[2] print "Top model 3: %s (DOPE score %.3f)" % (m['name'], m[key]) m = ok_models[3] print "Top model 4: %s (DOPE score %.3f)" % (m['name'], m[key]) m = ok_models[4] print "Top model 5: %s (DOPE score %.3f)" % (m['name'], m[key])

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