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Protein COFACTOR ASSEMBLY OF COMPLEX C SUBUNIT B CCB2, chloroplastic

Reviewed
Reference proteome

AF-Q9FJ81-F1-v4

DownloadPDB file mmCIF file Predicted aligned error

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Information

Structure viewer
Model Confidence
pLDDT corresponds to the model’s prediction of its score on the local Distance Difference Test (lDDT-Cα). It is a measure of local accuracy - for interpreting larger scale features like relative domain positions see the “predicted aligned error” plot and corresponding tutorial. Confidence bands are used to colour-code the residues in the 3D viewer. The exact pLDDT value is shown when you mouseover the structure or the sequence. It can also be found in the B-factor fields of the downloadable coordinate files.

 Very high (pLDDT > 90)
 High (90 > pLDDT > 70)
 Low (70 > pLDDT > 50)
 Very low (pLDDT < 50)
AlphaFold produces a per-residue model confidence score (pLDDT) between 0 and 100. Some regions below 50 pLDDT may be unstructured in isolation.

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SequenceNo structure available
Structure Tools
  • 14:30:46
    Mol* Plugin 4.5.0 [8/22/2024, 2:35:37 PM]
Model Confidence
pLDDT corresponds to the model’s prediction of its score on the local Distance Difference Test (lDDT-Cα). It is a measure of local accuracy - for interpreting larger scale features like relative domain positions see the “predicted aligned error” plot and corresponding tutorial. Confidence bands are used to colour-code the residues in the 3D viewer. The exact pLDDT value is shown when you mouseover the structure or the sequence. It can also be found in the B-factor fields of the downloadable coordinate files.
 Very high (pLDDT > 90)
 High (90 > pLDDT > 70)
 Low (70 > pLDDT > 50)
 Very low (pLDDT < 50)
AlphaFold produces a per-residue model confidence score (pLDDT) between 0 and 100. Some regions below 50 pLDDT may be unstructured in isolation.
Scored residueAligned residue
050100150200250050100150200250
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Expected position error (Ångströms)

Predicted aligned error (PAE)

Click and drag a box on the PAE viewer to select regions of the structure and highlight them on the 3D viewer.

PAE data is useful for assessing inter-domain accuracy – go to Help section below for more information.

Similar structures Discover similar structures from the Protein Data Bank (PDB) and the AlphaFold Database clustered to 50% sequence identity (AFDB50) using Foldseek.
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Structure similarity clusterPredicted structures in the AlphaFold Protein Structure Database clustered using MMseqs2 and Foldseek. This data is provided by the AFDB Clusters.

AlphaFold database protein sequences clustered by the MMseqs2 algorithm (Steinegger M. and Soeding J., Nat. Commun. 9, 2018). Each cluster is comprised of sequences that fulfil two criteria: maintaining a maximum sequence identity of 50% and achieving a 90% bi-directional sequence overlap with the longest sequence of the cluster representative.

AFDB accession DescriptionSpecies
Sequence length
Average pLDDT
AFDB accessionAF-A0A446IXF5-F1
Unreviewed
Reference proteome
Description Uncharacterized protein
Uncharacterized protein
SpeciesTriticum turgidum subsp. durum
Triticum turgidum subsp. durum
Sequence length 242 Average pLDDT 72.69
AFDB accessionAF-M7YAU1-F1
Unreviewed
Reference proteome
Description Uncharacterized protein
Uncharacterized protein
SpeciesTriticum urartu
Triticum urartu
Sequence length 242 Average pLDDT 72.62
AFDB accessionAF-F2CTT4-F1
Unreviewed
Description Predicted protein
Predicted protein
SpeciesHordeum vulgare subsp. vulgare
Hordeum vulgare subsp. vulgare
Sequence length 289 Average pLDDT 71.81
AFDB accessionAF-V4LTU4-F1
Unreviewed
Reference proteome
Description Uncharacterized protein
Uncharacterized protein
SpeciesEutrema salsugineum
Eutrema salsugineum
Sequence length 279 Average pLDDT 71.56
AFDB accessionAF-A0A397ZW04-F1
Unreviewed
Reference proteome
Description Uncharacterized protein
Uncharacterized protein
SpeciesBrassica campestris
Brassica campestris
Sequence length 276 Average pLDDT 71.56
AFDB accessionAF-R0GD44-F1
Unreviewed
Description Uncharacterized protein
Uncharacterized protein
SpeciesCapsella rubella
Capsella rubella
Sequence length 279 Average pLDDT 71.56
AFDB accessionAF-A0A3B5XZP8-F1
Unreviewed
Reference proteome
Description Uncharacterized protein
Uncharacterized protein
SpeciesTriticum aestivum
Triticum aestivum
Sequence length 289 Average pLDDT 71.31
AFDB accessionAF-D7MRM9-F1
Unreviewed
Reference proteome
Description Uncharacterized protein
Uncharacterized protein
SpeciesArabidopsis lyrata subsp. lyrata
Arabidopsis lyrata subsp. lyrata
Sequence length 272 Average pLDDT 71.06
AFDB accessionAF-A0A3N6U5J6-F1
Unreviewed
Reference proteome
Description Uncharacterized protein
Uncharacterized protein
SpeciesBrassica cretica
Brassica cretica
Sequence length 276 Average pLDDT 70.94
AFDB accessionAF-A0A0D3B3V5-F1
Unreviewed
Reference proteome
Description Uncharacterized protein
Uncharacterized protein
SpeciesBrassica oleracea var. oleracea
Brassica oleracea var. oleracea
Sequence length 276 Average pLDDT 70.88
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Help

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How to interpret the Predicted Aligned Error

 

The Predicted Aligned Error (PAE) measures the confidence in the relative position of two residues within the predicted structure, providing insight into the reliability of relative position and orientations of different domains. Consider the human protein encoded by the gene GNE (Q9Y223).

GNE has two distinct domains according to experimentally determined structures in the Protein Data Bank (PDBe-KB). Does AlphaFold confidently predict their relative positions? We can use the interactive Predicted Aligned Error (PAE) plot to answer this question.

The PAE plot is not an inter-residue distance map or a contact map. Instead, the shade of green indicates the expected distance error in Ångströms (Å), ranging from 0 Å to an arbitrary cut-off of 31 Å. The colour at (x, y) corresponds to the expected distance error in the residue x’s position when the predicted and the true structures are aligned on residue y.

A dark green tile corresponds to a good prediction (low error), whereas a light green tile indicates poor prediction (high error). For example, when aligning on residue 300:

  • We’re confident in the relative position of residue 200
  • We’re not confident in the relative position of residue 600

The two low-error, dark green squares correspond to the two domains. By clicking and dragging, you can highlight these squares on the structure. If you want to remove the highlighting, click the cross icon.

When selecting an off-diagonal region, the plot visually represents the relationship between the selected ranges on the sequence and structure. The x range corresponds to the selection for scored residues, highlighted in orange, while the y range of aligned residues is highlighted in emerald green.

The high PAE values across the whole inter-domain region indicate that for this particular protein, AlphaFold does not reliably predict the relative position of the domains.

Let’s consider another inter-domain example, the human protein encoded by DIP2B (Q9P265).

In this case, we have confidence in the relative position of scored residues around 1450 when aligned with residues around 850, suggesting a packing between the small central domains.

Note that the PAE scores are asymmetrical, meaning there might be variations in PAE values between (x,y) and (y,x) positions. This is particularly relevant for loop regions with highly uncertain orientations, as seen on the DNA topoisomerase 3 (Q8T2T7).

 


Last updated

Last updated in AlphaFold DB version 2022-11-01, created with the AlphaFold Monomer v2.0 pipeline.

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If you make use of an AlphaFold prediction, please cite the following papers:
Jumper, J et al. Highly accurate protein structure prediction with AlphaFold. Nature (2021).
Varadi, M et al. AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences. Nucleic Acids Research (2024).
If you use data from AlphaMissense in your work, please cite the following paper:
Cheng, J et al. Accurate proteome-wide missense variant effect prediction with AlphaMissense. Science (2023).

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AlphaMissense Copyright (2023) DeepMind Technologies Limited.

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