<p>By far the most accurate model right now should be AlphaFold, and there are open structures across several proteomes available at <a href="https://alphafold.ebi.ac.uk/" rel="nofollow noreferrer">https://alphafold.ebi.ac.uk/</a>.</p>

CC BY-SA 4.0
2021-08-20T21:46:43.747Z
2021-08-20T21:46:43.747Z
Jonas Adler
<h2>Updated</h2>
<p>As of 2021, the <a href="https://alphafold.ebi.ac.uk/" rel="nofollow noreferrer">EBI alphaFold2</a> is the best resource. There are some caveats, which I have outlined in <a href="https://blog.matteoferla.com/2021/07/what-to-look-out-for-with-alphafold2.html" rel="nofollow noreferrer">this blog post</a>.</p>
<p>But majorly, it contains only monomeric predictions and not oligomers and complexes. As a result, for protein with a close homologue with a solved structure, it may be more handy to use a threaded structure as found in the SwissModel database (see original answer below) because it may be oligomeric and/or one can copy over ligands or binding partners if deemed suitable.</p>
<p>One can make one's own predictions with AlphaFold2, who have released a handy notebook. Also one can make complexes and oligomers with some tweaks or with the heavily improved notebooks found in <a href="http://ColabFold%20GitHub%20repo" rel="nofollow noreferrer">ColabFold GitHub repo</a>.</p>
<h2>Original Answer</h2>
<p>It is worth saying that for model organisms, Expasy <a href="https://swissmodel.expasy.org/" rel="nofollow noreferrer">Swissmodel</a> is the &quot;classical&quot; database of predicted proteome structures. It has several model organisms and gets updates regularly. The models are threaded only and the algorithm fell behind some time ago —their website however is modern and sleek. If using Rosetta afterwards, one should do a few cycles of FastRelax with a movemap preventing backbone movements or CA restrained, followed by a couple of cartesian bond/angle fixing cycles: the structure tends to blow up if energy minimised otherwise.</p>
<p>However, if one had a specific protein in mind predicting with RosettaCM, the I-Tasser server or Phyre server is by the recommended option. And actually, the Phyre server has a <a href="http://www.sbg.bio.ic.ac.uk/%7Emissense3d/dataset.html" rel="nofollow noreferrer">dataset of the precomputed human proteome</a>.</p>
<p>About the PDB, the database has been purged of all <em>in</em> <em>silico</em> models and contains only empirical structures (NMR, X-ray, neutron diffraction and cryo-EM).</p>

CC BY-SA 4.0
2021-03-10T15:32:56.317Z
2021-08-21T18:28:42.523Z
2021-08-21T18:28:42.523Z
Matteo Ferla
<p>I am using DMPfold to predict protein structure of a 382 residue protein sequence. All goes wel, and even the files are produced but during the "seq2maps.csh", I get this error in between:</p>

<pre><code>Running PSIPRED &amp; SOLVPRED
Running PSI-BLAST with sequence c600m2-tail-before-lysin-sequence.temp.fasta ...
Segmentation fault (core dumped)
[blastpgp] WARNING: Unable to open BLOSUM62
[blastpgp] WARNING: BlastScoreBlkMatFill returned non-zero status
[blastpgp] WARNING: SetUpBlastSearch failed.
BLASTP 2.2.17 [Aug-26-2007]


Reference: Altschul, Stephen F., Thomas L. Madden, Alejandro A. Schaffer, 
Jinghui Zhang, Zheng Zhang, Webb Miller, and David J. Lipman (1997), 
"Gapped BLAST and PSI-BLAST: a new generation of protein database search
programs",  Nucleic Acids Res. 25:3389-3402.


Reference for composition-based statistics:
Schaffer, Alejandro A., L. Aravind, Thomas L. Madden,
Sergei Shavirin, John L. Spouge, Yuri I. Wolf,  
Eugene V. Koonin, and Stephen F. Altschul (2001), 
"Improving the accuracy of PSI-BLAST protein database searches with 
composition-based statistics and other refinements",  Nucleic Acids Res. 29:2994-3005.

Query= C600M2_00100 tail protein [Salmonella phage BPS17S6]
         (377 letters)

Database: c600m2-tail-before-lysin-sequence.a3m 
           46,978 sequences; 11,323,713 total letters

SearchingFATAL: Error whilst running blastpgp - script terminated!
Running PSICOV
Running FreeContact
Running CCMpred
 _____ _____ _____               _ 
|     |     |     |___ ___ ___ _| |
|   --|   --| | | | . |  _| -_| . |
|_____|_____|_|_|_|  _|_| |___|___|
                  |_|              

using CPU (10 thread(s))

Reweighted 30404 sequences with threshold 0.8 to Beff=22917.9 weight mean=0.753779, min=0.0232558, max=1

Will optimize 62686429 32-bit variables

iter    eval    f(x)        ║x║         ║g║         step
1       1       1.50338e+07 152357      3.021629e+11    1.55e-06
2       1       1.47369e+07 152356      2.1447226e+11   1.18e-06
3       1       1.44292e+07 152355      1.4646483e+11   1.22e-06
4       1       1.41268e+07 152353      1.0388224e+11   1.5e-06
5       1       1.38295e+07 152358      7.337667e+10    1.92e-06
</code></pre>

<p>Can you please let me know if I need to rerun seq2maps.csh because of this error? And, how this error can be solved? Thank you!</p>

CC BY-SA 4.0
2019-09-10T11:11:41.407Z
I will answer where you have posted this as a separate question: https://bioinformatics.stackexchange.com/questions/9345/dmpfold-error-while-running-protein-structure-prediction
jgreener
CC BY-SA 4.0
2019-09-10T09:13:17.827Z
2019-09-10T09:13:17.827Z
DanielSebas
<p>There are three initiatives I know of to have a go at this:</p>
<ol>
<li><a href="http://pconsfam.bioinfo.se/" rel="nofollow noreferrer">PConsFam</a>, which collects data from <a href="https://academic.oup.com/bioinformatics/article/33/14/i23/3953955" rel="nofollow noreferrer">this paper</a>.</li>
<li>The Baker group's <a href="https://science.sciencemag.org/content/355/6322/294" rel="nofollow noreferrer">metagenomic study</a> which you mention in the question.</li>
<li>The recent <a href="https://arxiv.org/abs/1811.12355" rel="nofollow noreferrer">DMPfold</a> work from our lab. This compares its results to the above two studies and discusses the effect on various model organisms.</li>
</ol>
<p>The second and third of these don't provide a database per se, but the models are available for download and are linked to the Pfam database.</p>
<p>EDIT: things have moved on significantly since I first wrote this answer. As other answers mention, the <a href="https://alphafold.ebi.ac.uk" rel="nofollow noreferrer">AlphaFold Protein Structure Database</a> is now the best resource in this area.</p>

CC BY-SA 4.0
2019-05-24T19:58:45.437Z
`DMPfold` looks very promising. 
Hoping that the work gets published soon so we could get to use the data.
user345394
CC BY-SA 4.0
2019-05-25T21:01:12.070Z
Thanks, it's currently under review. Though all the data is already available, see https://github.com/psipred/DMPfold#data.
jgreener
CC BY-SA 4.0
2019-09-10T11:10:53.490Z
The paper is now published, see https://www.nature.com/articles/s41467-019-11994-0.
jgreener
CC BY-SA 4.0
2019-05-23T17:08:18.930Z
2022-01-10T11:56:42.923Z
2022-01-10T11:56:42.923Z
jgreener
<p>Accuracies of protein structure predictors have improved quite a lot in recent years. Algorithms such as <a href="https://www.rosettacommons.org/software" rel="nofollow noreferrer">Rosetta</a> have gotten robust enough to <a href="http://science.sciencemag.org/content/355/6322/294" rel="nofollow noreferrer">predict structures of large number of proteins</a>. However, I could't find any initiative to make a database for proteome-wide predictions of protein structures or may be integrate the predicted structures in existing databases (PDB or Uniprot).</p>

<p>If any such exists, please let me know.</p>

CC BY-SA 4.0
2019-01-25T10:05:33.830Z
So, your question is if there is a database of predicted structures? (What would be the utility of this database? How would it be up to date/updated?)
llrs
CC BY-SA 4.0
2019-01-25T14:23:07.673Z
Yes. 
There could be many uses of predicted structures of all the proteins in the proteome, given that the predictions are accurate enough. One could use that resource to make proteome wide inferences about protein structures, which we can not do now with structures of fewer than ~30% of the proteins available. 
In terms of advantage, the users would not have to run the prediction model themselves, so it would save time and effort for them.
user345394
CC BY-SA 4.0
2019-01-25T14:23:10.220Z
Regarding updation of the database, I would imagine that would a minor task if there is a prediction model available. Its just about rerunning the updated prediction model again.
user345394
CC BY-SA 4.0
2019-01-25T15:05:38.337Z
I'm not sure that the accuracy is "good enough". Enough for what? Also the folding of a protein changes with the environment. If it seems so easy and no one have done it there might be some "hidden" problems on it. Perhaps the computational cost of those predictions is too expensive for any single (or a consortium) group to try.
llrs
<database><proteins><protein-structure>
Database for proteome-wide predictions of protein structures
# Database for proteome-wide predictions of protein structures

(Asked by: username_0 on 2019-01-24)

Accuracies of protein structure predictors have improved quite a lot in recent years. Algorithms such as [Rosetta](https://www.rosettacommons.org/software) have gotten robust enough to [predict structures of large number of proteins](http://science.sciencemag.org/content/355/6322/294). However, I could't find any initiative to make a database for proteome-wide predictions of protein structures or may be integrate the predicted structures in existing databases (PDB or Uniprot).

If any such exists, please let me know.

**Tags:** database, proteins, protein-structure
> **Comments:**
> **username_1**: So, your question is if there is a database of predicted structures? (What would be the utility of this database? How would it be up to date/updated?)  
> **username_0**: Yes.  There could be many uses of predicted structures of all the proteins in the proteome, given that the predictions are accurate enough. One could use that resource to make proteome wide inferences about protein structures, which we can not do now with structures of fewer than ~30% of the proteins available.  In terms of advantage, the users would not have to run the prediction model themselves, so it would save time and effort for them.  
> **username_0**: Regarding updation of the database, I would imagine that would a minor task if there is a prediction model available. Its just about rerunning the updated prediction model again.  
> **username_1**: I'm not sure that the accuracy is "good enough". Enough for what? Also the folding of a protein changes with the environment. If it seems so easy and no one have done it there might be some "hidden" problems on it. Perhaps the computational cost of those predictions is too expensive for any single (or a consortium) group to try.  

---

## 4 answers

### Answer by username_5 on 2019-05-23. Score: 4 | Accepted answer

There are three initiatives I know of to have a go at this:

1. [PConsFam](http://pconsfam.bioinfo.se/), which collects data from [this paper](https://academic.oup.com/bioinformatics/article/33/14/i23/3953955).
2. The Baker group's [metagenomic study](https://science.sciencemag.org/content/355/6322/294) which you mention in the question.
3. The recent [DMPfold](https://arxiv.org/abs/1811.12355) work from our lab. This compares its results to the above two studies and discusses the effect on various model organisms.

The second and third of these don't provide a database per se, but the models are available for download and are linked to the Pfam database.

EDIT: things have moved on significantly since I first wrote this answer. As other answers mention, the [AlphaFold Protein Structure Database](https://alphafold.ebi.ac.uk) is now the best resource in this area.

> **Comments:**
> **username_0**: `DMPfold` looks very promising.  Hoping that the work gets published soon so we could get to use the data.  
> **username_5**: Thanks, it's currently under review. Though all the data is already available, see https://github.com/psipred/DMPfold#data.  
> **username_5**: The paper is now published, see https://www.nature.com/articles/s41467-019-11994-0.  

---

### Answer by username_2 on 2021-08-20. Score: 4

By far the most accurate model right now should be AlphaFold, and there are open structures across several proteomes available at <https://alphafold.ebi.ac.uk/>.


---

### Answer by username_3 on 2021-03-10. Score: 3

## Updated

As of 2021, the [EBI alphaFold2](https://alphafold.ebi.ac.uk/) is the best resource. There are some caveats, which I have outlined in [this blog post](https://blog.matteoferla.com/2021/07/what-to-look-out-for-with-alphafold2.html).

But majorly, it contains only monomeric predictions and not oligomers and complexes. As a result, for protein with a close homologue with a solved structure, it may be more handy to use a threaded structure as found in the SwissModel database (see original answer below) because it may be oligomeric and/or one can copy over ligands or binding partners if deemed suitable.

One can make one's own predictions with AlphaFold2, who have released a handy notebook. Also one can make complexes and oligomers with some tweaks or with the heavily improved notebooks found in [ColabFold GitHub repo](http://ColabFold%20GitHub%20repo).

## Original Answer

It is worth saying that for model organisms, Expasy [Swissmodel](https://swissmodel.expasy.org/) is the "classical" database of predicted proteome structures. It has several model organisms and gets updates regularly. The models are threaded only and the algorithm fell behind some time ago —their website however is modern and sleek. If using Rosetta afterwards, one should do a few cycles of FastRelax with a movemap preventing backbone movements or CA restrained, followed by a couple of cartesian bond/angle fixing cycles: the structure tends to blow up if energy minimised otherwise.

However, if one had a specific protein in mind predicting with RosettaCM, the I-Tasser server or Phyre server is by the recommended option. And actually, the Phyre server has a [dataset of the precomputed human proteome](http://www.sbg.bio.ic.ac.uk/%7Emissense3d/dataset.html).

About the PDB, the database has been purged of all *in* *silico* models and contains only empirical structures (NMR, X-ray, neutron diffraction and cryo-EM).


---

### Answer by username_4 on 2019-09-10. Score: 1

I am using DMPfold to predict protein structure of a 382 residue protein sequence. All goes wel, and even the files are produced but during the "seq2maps.csh", I get this error in between:
Running PSIPRED & SOLVPRED
Running PSI-BLAST with sequence c600m2-tail-before-lysin-sequence.temp.fasta ...
Segmentation fault (core dumped)
[blastpgp] WARNING: Unable to open BLOSUM62
[blastpgp] WARNING: BlastScoreBlkMatFill returned non-zero status
[blastpgp] WARNING: SetUpBlastSearch failed.
BLASTP 2.2.17 [Aug-26-2007]


Reference: Altschul, Stephen F., Thomas L. Madden, Alejandro A. Schaffer, 
Jinghui Zhang, Zheng Zhang, Webb Miller, and David J. Lipman (1997), 
"Gapped BLAST and PSI-BLAST: a new generation of protein database search
programs",  Nucleic Acids Res. 25:3389-3402.


Reference for composition-based statistics:
Schaffer, Alejandro A., L. Aravind, Thomas L. Madden,
Sergei Shavirin, John L. Spouge, Yuri I. Wolf,  
Eugene V. Koonin, and Stephen F. Altschul (2001), 
"Improving the accuracy of PSI-BLAST protein database searches with 
composition-based statistics and other refinements",  Nucleic Acids Res. 29:2994-3005.

Query= C600M2_00100 tail protein [Salmonella phage BPS17S6]
         (377 letters)

Database: c600m2-tail-before-lysin-sequence.a3m 
           46,978 sequences; 11,323,713 total letters

SearchingFATAL: Error whilst running blastpgp - script terminated!
Running PSICOV
Running FreeContact
Running CCMpred
 _____ _____ _____               _ 
|     |     |     |___ ___ ___ _| |
|   --|   --| | | | . |  _| -_| . |
|_____|_____|_|_|_|  _|_| |___|___|
                  |_|              

using CPU (10 thread(s))

Reweighted 30404 sequences with threshold 0.8 to Beff=22917.9 weight mean=0.753779, min=0.0232558, max=1

Will optimize 62686429 32-bit variables

iter    eval    f(x)        ║x║         ║g║         step
1       1       1.50338e+07 152357      3.021629e+11    1.55e-06
2       1       1.47369e+07 152356      2.1447226e+11   1.18e-06
3       1       1.44292e+07 152355      1.4646483e+11   1.22e-06
4       1       1.41268e+07 152353      1.0388224e+11   1.5e-06
5       1       1.38295e+07 152358      7.337667e+10    1.92e-06

Can you please let me know if I need to rerun seq2maps.csh because of this error? And, how this error can be solved? Thank you!

> **Comments:**
> **username_5**: I will answer where you have posted this as a separate question: https://bioinformatics.stackexchange.com/questions/9345/dmpfold-error-while-running-protein-structure-prediction  

---

