- modeller_usage - salilab.org

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 21 Oct '16

21 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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Re: [modeller_usage] (no subject)
by Markus Heller 28 Sep '16

28 Sep '16

Ah, ok, makes sense.. Thanks for the exmplanation! Markus -----Original Message----- From: Modeller Caretaker [mailto:modeller-care@salilab.org] Sent: Wednesday, September 28, 2016 12:05 PM To: Markus Heller Subject: Re: [modeller_usage] (no subject) On 9/28/16 10:43 AM, Markus Heller wrote: > 3. $ python calc_model.py > console_output.txt Modeller numbers residues starting from 1; it doesn't reset the counter to 1 at the start of a new chain, so your residues are numbered 1:A through 470:A and 471:B through 940:B (see the .ini file). If you want to also renumber the residues, use the renumber_residues argument to rename_segments(): https://salilab.org/modeller/9.17/manual/node191.html Ben Webb, Modeller Caretaker -- modeller-care(a)salilab.org https://salilab.org/modeller/ Modeller mail list: https://salilab.org/mailman/listinfo/modeller_usage

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(no subject)
by Markus Heller 27 Sep '16

27 Sep '16

Hi, I'm trying to model two missing loops in a homo-dimeric protein, following the example on the web: https://salilab.org/modeller/wiki/Missing%20residues I have saved chains A and C (forming the dimer) as pdb, and then extracted the sequence using get_seq.py (see below). Then I created an alignment file and inserted the missing residues to give the alignment file shown below. When I try to do the modeling, I get a "KeyError: 'No such residue: 346:B'" (see calc_model.py below). I've tried to rename the chains in my script. What's my mistake? Thanks and Cheers Markus %%%%%%%%%%%%%%%%%%%%%% calc_model.py %%%%%%%%%%%%%%%%% 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'] class MyModel(automodel): def special_patches(self, aln): # Rename both chains self.rename_segments(segment_ids=['A', 'B']) def select_atoms(self): return selection(self.residue_range('346:A', '350:A'), self.residue_range('346:B', '348:B')) a = MyModel(env, alnfile = 'alignment.ali', knowns = '4yng_AC', sequence = '4yng_AC_fill') a.starting_model= 1 a.ending_model = 5 a.make() %%%%%%%%%%%%%%%%%%%%%% end of calc_model.py %%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%% alignment.ali %%%%%%%%%%%%%%%%% >P1;4yng_AC structureX:4yng_AC: 1 :A:+932 :C:MOL_ID 1; MOLECULE PYRUVATE KINASE I; CHAIN A, B, C, D, E, F, G, H; SYNONYM PK-1; EC 2.7.1.40; ENGINEERED YES:MOL_ID 1; ORGANISM_SCIENTIFIC ESCHERICHIA COLI; ORGANISM_TAXID 562; GENE PYKF, Z2704, ECS2383; EXPRESSION_SYSTEM ESCHERICHIA COLI BL21(DE3); EXPRESSION_SYSTEM_TAXID 469008: 2.28: 0.22 MKKTKIVCTIGPKTESEEMLAKMLDAGMNVMRLNFSHGDYAEHGQRIQNLRNVMSKTGKTAAILLDTKGPEIRTM KLEGGNDVSLKAGQTFTFTTDKSVIGNSEMVAVTYEGFTTDLSVGNTVLVDDGLIGMEVTAIEGNKVICKVLNNG DLGENKGVNLPGVSIALPALAEKDKQDLIFGCEQGVDFVAASFIRKRSDVIEIREHLKAHGGENIHIISKIENQE GLNNFDEILEASDGIMVARGDLGVEIPVEEVIFAQKMMIEKCIRARKVVITATQMLDSMIKNPRPTRAEAGDVAN AILDGTDAVMLSGESAKGKYPLEAVSIMATICERTDRVMNSRLEF-----KLRITEAVCRGAVETAEKLDAPLIV VATQGGKSARAVRKYFPDATILALTTNEKTAHQLVLSKGVVPQLVKEITSTDDFYRLGKELALQSGLAHKGDVVV MVSGALVPSGTTNTASVHVL/MKKTKIVCTIGPKTESEEMLAKMLDAGMNVMRLNFSHGDYAEHGQRIQNLRNVM SKTGKTAAILLDTKGPEIRTMKLEGGNDVSLKAGQTFTFTTDKSVIGNSEMVAVTYEGFTTDLSVGNTVLVDDGL IGMEVTAIEGNKVICKVLNNGDLGENKGVNLPGVSIALPALAEKDKQDLIFGCEQGVDFVAASFIRKRSDVIEIR EHLKAHGGENIHIISKIENQEGLNNFDEILEASDGIMVARGDLGVEIPVEEVIFAQKMMIEKCIRARKVVITATQ MLDSMIKNPRPTRAEAGDVANAILDGTDAVMLSGESAKGKYPLEAVSIMATICERTDRVMNSRLEF---NRKLRI TEAVCRGAVETAEKLDAPLIVVATQGGKSARAVRKYFPDATILALTTNEKTAHQLVLSKGVVPQLVKEITSTDDF YRLGKELALQSGLAHKGDVVVMVSGALVPSGTTNTASVHVL* >P1;4yng_AC_fill sequence::::::::: MKKTKIVCTIGPKTESEEMLAKMLDAGMNVMRLNFSHGDYAEHGQRIQNLRNVMSKTGKTAAILLDTKGPEIRTM KLEGGNDVSLKAGQTFTFTTDKSVIGNSEMVAVTYEGFTTDLSVGNTVLVDDGLIGMEVTAIEGNKVICKVLNNG DLGENKGVNLPGVSIALPALAEKDKQDLIFGCEQGVDFVAASFIRKRSDVIEIREHLKAHGGENIHIISKIENQE GLNNFDEILEASDGIMVARGDLGVEIPVEEVIFAQKMMIEKCIRARKVVITATQMLDSMIKNPRPTRAEAGDVAN AILDGTDAVMLSGESAKGKYPLEAVSIMATICERTDRVMNSRLEFNNDNRKLRITEAVCRGAVETAEKLDAPLIV VATQGGKSARAVRKYFPDATILALTTNEKTAHQLVLSKGVVPQLVKEITSTDDFYRLGKELALQSGLAHKGDVVV MVSGALVPSGTTNTASVHVL/MKKTKIVCTIGPKTESEEMLAKMLDAGMNVMRLNFSHGDYAEHGQRIQNLRNVM SKTGKTAAILLDTKGPEIRTMKLEGGNDVSLKAGQTFTFTTDKSVIGNSEMVAVTYEGFTTDLSVGNTVLVDDGL IGMEVTAIEGNKVICKVLNNGDLGENKGVNLPGVSIALPALAEKDKQDLIFGCEQGVDFVAASFIRKRSDVIEIR EHLKAHGGENIHIISKIENQEGLNNFDEILEASDGIMVARGDLGVEIPVEEVIFAQKMMIEKCIRARKVVITATQ MLDSMIKNPRPTRAEAGDVANAILDGTDAVMLSGESAKGKYPLEAVSIMATICERTDRVMNSRLEFNNDNRKLRI TEAVCRGAVETAEKLDAPLIVVATQGGKSARAVRKYFPDATILALTTNEKTAHQLVLSKGVVPQLVKEITSTDDF YRLGKELALQSGLAHKGDVVVMVSGALVPSGTTNTASVHVL* %%%%%%%%%%%%%%%%%%%%%% end of alignment.ali %%%%%%%%%%%%%%%%%

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Conda package not working on windows (32 bit?) and python 3.5
by Ajasja Ljubetič 16 Sep '16

16 Sep '16

Hi! If I install modeller via conda: export KEY_MODELLER=XXXX conda install -c salilab modeller Then I get an error when importing modeller Python 3.5.2 |Anaconda 4.1.1 (32-bit)| (default, Jul 5 2016, 11:45:57) [MSC v.1900 32 bit (Intel)] on win32 Type "help", "copyright", "credits" or "license" for more information. >>> import modeller Traceback (most recent call last): File "<stdin>", line 1, in <module> File "C:\Anaconda3\Library\modeller\modlib\modeller\__init__.py", line 93, in <module> import _modeller ImportError: DLL load failed: The specified module could not be found. >>> I tried copying around the file _modeller.pyd to folders in the PATH, but that did not solve the problem. The installed version is modeller 9.17 py35_1 salilab But if I install from the stand-alone installer everything works fine. Best, Ajasja

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First time running modeller, multiple errors
by Maryam Faridounnia 27 Aug '16

27 Aug '16

Dear Modeller team, I'm trying to get the format right for a multiple alignment, I did in HHpred server to use as input to modeller. I don't understand the error messages. I don't know if the errors are related to the PDB file since I have not changed anything in original PDB unless the extension. I would appreciate very much your advice. Thanks in advance for your help! Maryam ***The input python script: # Comparative modeling by the automodel class from modeller import * # Load standard Modeller classes from modeller.automodel import * # Load the automodel class log.verbose() # request verbose output env = environ() # create a new MODELLER environment to build this model in # directories for input atom files env.io.atom_files_directory = ['.', '../atom_files'] a = automodel(env, alnfile = 'XPF_nuc.ali', # alignment filename knowns = '1j23','4bxo', # codes of the templates sequence = 'XPF') # 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.make() # do the actual comparative modeling ***The run command: mod9.11 model_test1.py ***atom_files: $ ls -l total 952 -rw-r--r-- 1 mfaridou users 121905 Aug 25 23:07 1j23.atm -rw-r--r-- 1 mfaridou users 121905 Aug 25 23:08 1j23.pdb -rw-r--r-- 1 mfaridou users 362313 Aug 25 23:08 4bxo.atm -rw-r--r-- 1 mfaridou users 362313 Aug 25 23:08 4bxo.pdb *** input file XPF_nuc.ali >P1;1j23 structurex:1j23:5:A:125:A:HEFnuclease:Pyrococcus furiosus:1.78:0.248 QEGVKVVVDSRELRSEVVKRLKLLGVKLEVKTLDVGDYIISEDVAIERKSANDLIQSIIDGGLFDQVKRLKEAYSRPIMIVEGS-LY---------GIRNVHPNAIRGAIAAVTVDF-GVPIIFSSTPEETAQYI* >P1;4bxo structurex:4bxo:1:A:151:A:FANCMprotein:Homo sapiens:2.15:0.255 GSGSRPHLAGTHTSLRLPQEGKGTCILVGGHEITSGLEVISSLRAIHGLQVEVCPLNGCDYIVSNRMVVERRSQSEMLNSVNKNKFIEQIQHLQSMFERICVIVEKDREKTGD------TSRMFRRTKSYDSLLTTLIGA-GIRILFSSCQEETADLL* >P1;XPF sequence:XPF:.:.:156:.::0.00: 0.00 RGTASADVSTDTRKAGGQEQNGTQQSIVVDMREFRSELPSLIHRRGIDIEPVTLEVGDYILTPEMCVERKSISDLIGSLNNGRLYSQCISMSRYYKRPVLLIEFDPSKPFSLTSRGALFQEISSNDISSKLTLLTLHFPRLRILWCPSPHATAELF* ***The runtime messages: 'import site' failed; use -v for traceback Traceback (most recent call last): File "model_test1.py", line 18, in ? a.make() # do the actual comparative modeling File "/home/software/software//modeller_v9.11/modlib/modeller/automodel/automodel.py", line 96, in make self.homcsr(exit_stage) File "/home/software/software//modeller_v9.11/modlib/modeller/automodel/automodel.py", line 423, in homcsr self.check_alignment(aln) File "/home/software/software//modeller_v9.11/modlib/modeller/automodel/automodel.py", line 405, in check_alignment aln.check() File "/home/software/software//modeller_v9.11/modlib/modeller/alignment.py", line 197, in check self.check_structure_structure(io=io) File "/home/software/software//modeller_v9.11/modlib/modeller/alignment.py", line 206, in check_structure_structure return f(self.modpt, io.modpt, self.env.libs.modpt, eqvdst) _modeller.SequenceMismatchError: read_te_291E> Sequence difference between alignment and pdb :

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Best practices in point mutation
by Lucas 26 Jul '16

26 Jul '16

I've noticed Sali and Fiser have a 2007 article on point mutations (Modeling mutations in protein structures, Protein Science 16:2030-2041). I couldn't find the modeller script for that protocol, though. Is it available somewhere? Would the protocol at the wiki ( http://salilab.org/modeller/wiki/Mutate%20model ) be the most reliable approach these days? Cheers, Lucas

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How to write a dope score for selected region of optimized atoms along with whole model?
by Mahesh Velusamy 25 Jul '16

25 Jul '16

Dear All, I have tried generate a models for single point mutation along with own optimization and refinement criteria on the selected region of atoms around the mutated residue which works fine but the problem is in dope score. I thing modeler generate DOPE score only for selected region of optimized atoms but I want to write the dope score for optimized region of atoms along with whole structure. Is it possible to do the same? Here is my script used for select part of region from model and perform optimization: class MyModel(automodel): def select_atoms(self): s = selection(self.atoms['CA:'+"275"+':'+"A"].select_sphere(5)).by_residue() self.restraints.unpick_all() self.restraints.pick(s) s.energy() s.randomize_xyz(deviation=4) return s def optimize(s, sched): for step in sched: step.optimize(s, max_iterations=200, min_atom_shift=0.001) refine(s) cg = conjugate_gradients() cg.optimize(s, max_iterations=200, min_atom_shift=0.001) def refine(self,s,actions): md = molecular_dynamics(cap_atom_shift=0.39, md_time_step=4.0, md_return='FINAL') init_vel = True for (its, equil, temps) in ((200, 20, (150.0, 250.0, 400.0, 700.0, 1000.0)), (200, 600, (1000.0, 800.0, 600.0, 500.0, 400.0, 300.0))): for temp in temps: md.optimize(s, init_velocities=init_vel, temperature=temp, max_iterations=its, equilibrate=equil) init_vel = False Thanking you in advance With Regards Mahesh V

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loop modeling and hydrogen atoms
by flavio seixas 25 Jul '16

25 Jul '16

Hi, I generated a model with all hydrogens using allhmodel. Now I want to refine a loop in this model using the script below. However, the hydrogens are being removed in the generated models. Would you help me? from modeller import * from modeller.automodel import * log.verbose() env = environ() env.io.atom_files_directory = ['.', '../atom_files'] # Read in HETATM records from template PDBs env.io.hetatm = True env.io.water = True env.io.hydrogen = True # Create a new class based on 'loopmodel' so that we can redefine # select_loop_atoms class MyLoop(loopmodel): # This routine picks the residues to be refined by loop modeling def select_loop_atoms(self): # Two residue ranges (both will be refined simultaneously) return selection(self.residue_range('399:', '406:')) m = MyLoop(env, inimodel='Model172.pdb', sequence='protein', loop_assess_methods=(assess.DOPE, assess.GA341)) m.loop.starting_model= 1 # index of the first loop model m.loop.ending_model = 200 # index of the last loop model m.loop.md_level = refine.very_fast # loop refinement method m.make() # Get a list of all successfully built models from m.loop.outputs ok_models = filter(lambda x: x['failure'] is None, m.loop.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]) ------------------------------------- Flavio Augusto Vicente Seixas Laboratory of Structural Biochemistry Department of Biochemistry Universidade Estadual de Maringá, PR, Brazil http://www.uem.br

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