MFS domain-containing protein
AF-A0A178ZJ00-F1-v4
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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.
Start a structural similarity search to discover similar proteins.
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 | Description | Species | Sequence length | Average pLDDT |
---|---|---|---|---|
AFDB accessionAF-A0A2V1CKQ2-F1 | Description MFS transporter MFS transporter | SpeciesCadophora sp. DSE1049 Cadophora sp. DSE1049 | Sequence length 520 | Average pLDDT 88.31 |
AFDB accessionAF-A0A161VEM8-F1 | Description MFS drug efflux transporter MFS drug efflux transporter | SpeciesColletotrichum tofieldiae Colletotrichum tofieldiae | Sequence length 525 | Average pLDDT 88.19 |
AFDB accessionAF-E9CR12-F1 | Description MFS domain-containing protein MFS domain-containing protein | SpeciesCoccidioides posadasii (strain RMSCC 757 / Silveira) Coccidioides posadasii (strain RMSCC 757 / Silveira)... Coccidioides posadasii (strain RMSCC 757 / Silveira) | Sequence length 531 | Average pLDDT 87.94 |
AFDB accessionAF-A0A0J8RN12-F1 | Description AflT AflT | SpeciesCoccidioides immitis H538.4 Coccidioides immitis H538.4 | Sequence length 531 | Average pLDDT 87.56 |
AFDB accessionAF-A0A0J6YQD0-F1 | Description AflT AflT | SpeciesCoccidioides immitis RMSCC 2394 Coccidioides immitis RMSCC 2394 | Sequence length 531 | Average pLDDT 87.19 |
AFDB accessionAF-J3KLA3-F1 | Description MFS drug efflux transporter MFS drug efflux transporter | SpeciesCoccidioides immitis (strain RS) Coccidioides immitis (strain RS) | Sequence length 547 | Average pLDDT 87.12 |
AFDB accessionAF-R0KD61-F1 | Description MFS domain-containing protein MFS domain-containing protein | SpeciesSetosphaeria turcica (strain 28A) Setosphaeria turcica (strain 28A) | Sequence length 530 | Average pLDDT 87.06 |
AFDB accessionAF-A0A7U2I627-F1 | Description MFS domain-containing protein MFS domain-containing protein | SpeciesPhaeosphaeria nodorum (strain SN15 / ATCC MYA-4574 / FGSC 10173) Phaeosphaeria nodorum (strain SN15 / ATCC MYA-4574 / FGSC 10173)... Phaeosphaeria nodorum (strain SN15 / ATCC MYA-4574 / FGSC 10173) | Sequence length 542 | Average pLDDT 86.94 |
AFDB accessionAF-G9N443-F1 | Description MFS domain-containing protein MFS domain-containing protein | SpeciesHypocrea virens (strain Gv29-8 / FGSC 10586) Hypocrea virens (strain Gv29-8 / FGSC 10586)... Hypocrea virens (strain Gv29-8 / FGSC 10586) | Sequence length 527 | Average pLDDT 86.69 |
AFDB accessionAF-A0A3M7JTE0-F1 | Description MFS drug efflux transporter MFS drug efflux transporter | SpeciesAspergillus flavus Aspergillus flavus | Sequence length 534 | Average pLDDT 86.5 |
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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. 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. 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).
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:
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.
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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