Answers.Body: <p>Unfortunately you do in general increase your chance of success by going to the 50k range of models or higher. Projects like <a href="https://boinc.bakerlab.org/rosetta" rel="nofollow noreferrer">Rosetta@home</a> exist because even large research groups can't access as much compute power as they'd like. In this case the long time arises from the combinatorial explosion of possible fragment combinations that need to be explored.</p>
  
  <p>Success is rather protein dependent though - sometimes the right structure falls out after only a few models, other times your fragment library does not cover the protein adequately and you could run Rosetta forever without getting a good structure. Have a look at your 1,500 models and see how similar they look.</p>
  
  <p>382 residues is rather long for Rosetta. Another factor to consider is whether you are using predicted contacts as part of the folding process (e.g. in the <a href="https://www.ncbi.nlm.nih.gov/pubmed/25161237" rel="nofollow noreferrer">PconsFold</a> protocol), which will greatly improve the chances of getting a good model and reduce the number of models you need. In fact the PconsFold group switched to CONFOLD for PconsFold2, I think mainly because it was much faster, so you are not alone in finding Rosetta runs long.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-09-23T09:53:42.803Z
Answers.Text: I did look at the generated 2100 decoys (rosetta ab initio run is still in progress) and plotted the RMSD vs ENERGY plot and it looks like this: https://ibb.co/LgQPz0L . Please let me know of your comments. I think there is still a long way to convergence? And, all structures are similar? Thanks
Answers.UserDisplayName: DanielSebas
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Answers.CreationDate: 2019-09-23T10:14:28.310Z
Answers.Text: The RMSD is zero for all models, indicating something is wrong. Do you have the native structure for this protein? The RMSD on an RMSD v. energy plot should be between the the model and the native structure.
Answers.UserDisplayName: jgreener
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Answers.CreationDate: 2019-09-23T10:41:32.797Z
Answers.Text: There is no native structure as this is an ab initio prediction. Could you please let me know about your comments?  Command line is this: "mpiexec -np 16 /main/source/bin/AbinitioRelax.mpi.linuxgccrelease -database /main/database/ @options -mpi_tracer_to_file log > log1.log &". "Options" file looks like this: https://ibb.co/V9VrQHV
Answers.UserDisplayName: DanielSebas
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Answers.Text: I will answer where you have asked this as a question: https://bioinformatics.stackexchange.com/questions/10453/rosetta-ab-initio-run-gives-0-00-rmsd-for-generated-2000-models-run-still-in-p
Answers.UserDisplayName: jgreener
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Body: <p>How many models should be generated by rosetta for de novo protein structure prediction of a 382 long sequence? In <a href="https://www.rosettacommons.org/demos/latest/tutorials/denovo_structure_prediction/Denovo_structure_prediction" rel="nofollow noreferrer">the tutorial</a>, it says 50,000 models but practically it takes a lot of time (weeks) to generate this number. For instance, I am currently running rosetta on a 382 long sequence and in a week it has generated 1500 models; I am using 16 cpus with Openmpi.</p>
  
Tags: <protein-structure><computational-biochemistry><rosetta>
Title: How many models should be generated by rosetta for denovo protein structure prediction?
ThreadText: # How many models should be generated by rosetta for denovo protein structure prediction?
  
  (Asked by: username_0 on 2019-09-19)
  
  How many models should be generated by rosetta for de novo protein structure prediction of a 382 long sequence? In [the tutorial](https://www.rosettacommons.org/demos/latest/tutorials/denovo_structure_prediction/Denovo_structure_prediction), it says 50,000 models but practically it takes a lot of time (weeks) to generate this number. For instance, I am currently running rosetta on a 382 long sequence and in a week it has generated 1500 models; I am using 16 cpus with Openmpi.
  
  **Tags:** protein-structure, computational-biochemistry, rosetta
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2019-09-19. Score: 2 | Accepted answer
  
  Unfortunately you do in general increase your chance of success by going to the 50k range of models or higher. Projects like [Rosetta@home](https://boinc.bakerlab.org/rosetta) exist because even large research groups can't access as much compute power as they'd like. In this case the long time arises from the combinatorial explosion of possible fragment combinations that need to be explored.
  
  Success is rather protein dependent though - sometimes the right structure falls out after only a few models, other times your fragment library does not cover the protein adequately and you could run Rosetta forever without getting a good structure. Have a look at your 1,500 models and see how similar they look.
  
  382 residues is rather long for Rosetta. Another factor to consider is whether you are using predicted contacts as part of the folding process (e.g. in the [PconsFold](https://www.ncbi.nlm.nih.gov/pubmed/25161237) protocol), which will greatly improve the chances of getting a good model and reduce the number of models you need. In fact the PconsFold group switched to CONFOLD for PconsFold2, I think mainly because it was much faster, so you are not alone in finding Rosetta runs long.
  
  > **Comments:**
  > **username_0**: I did look at the generated 2100 decoys (rosetta ab initio run is still in progress) and plotted the RMSD vs ENERGY plot and it looks like this: https://ibb.co/LgQPz0L . Please let me know of your comments. I think there is still a long way to convergence? And, all structures are similar? Thanks  
  > **username_1**: The RMSD is zero for all models, indicating something is wrong. Do you have the native structure for this protein? The RMSD on an RMSD v. energy plot should be between the the model and the native structure.  
  > **username_0**: There is no native structure as this is an ab initio prediction. Could you please let me know about your comments?  Command line is this: "mpiexec -np 16 /main/source/bin/AbinitioRelax.mpi.linuxgccrelease -database /main/database/ @options -mpi_tracer_to_file log > log1.log &". "Options" file looks like this: https://ibb.co/V9VrQHV  
  > **username_1**: I will answer where you have asked this as a question: https://bioinformatics.stackexchange.com/questions/10453/rosetta-ab-initio-run-gives-0-00-rmsd-for-generated-2000-models-run-still-in-p  
  
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