ProQ3: Model Quality Assessment

ProQ3/ProQ3D: Improved model quality assessment

To run ProQ3D that uses deep learning, please check the option "Using deep learning"

Paste your model in PDB format (up to 10 MB) :

Or, upload the model file (up to 10 MB):

Paste the amino acid sequence of your model in FASTA format (recommended, up to 10 KB).
Note that only one sequence is allowed:

Or, upload your sequence file (up to 10 KB):

Length of target (optional):

Job name (optional):

Email (recommended):

Perform side chain repacking:

Method for quality measurement:

Using deep learning:

Force run (do not use cached profiles):

Reference

ProQ3: [Please cite this paper if you find ProQ3 useful in your research]
ProQ3: Improved model quality assessments using Rosetta energy terms. Karolis Uziela, Nanjiang Shu, Björn Wallner and Arne Elofsson. Scientific Reports, 33509. [PubMed]

ProQ3D: [Please cite this paper if you find ProQ3D useful in your research]
ProQ3D: Improved model quality assessments using Deep Learning. Karolis Uziela, David Menéndez Hurtado, Nanjiang Shu, Björn Wallner and Arne Elofsson. Bioinformatics. 2017 May 15;33(10):1578-1580 [PubMed]

Others:
Improved protein model quality assessments by changing the target function. Karolis Uziela, David Menéndez Hurtado, Nanjiang Shu, Björn Wallner and Arne Elofsson. Proteins. 2018 Jun;86(6):654-663. [PubMed]

Resource provider

This work used the EGI infrastructure with the support of IN2P3-IRES, INFN-CLOUD-BARI and TR-FC1-ULAKBIM.