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Prediction of Intrinsically Unstructured Proteins (protein disorder) from amino acid sequence only.
Intrinsically unstructured proteins (IUPs) known also as unfolded proteins or disordered proteins are proteins characterized by lack of stable tertiary structure under physiological conditions. Moreover, such unfolded proteins remain functional. The intrinsic flexibility of disorder allows to form multiple interactions with various proteins by the same disordered protein. The prediction of protein disorder is important as IUPs are connected with many diseases (many key oncogens have large unstructured regions, e.g. p53 and BRCA1).
Metadisorder is one of the best predictors of protein disorder (evaluated during independent tests - CASP8 and CASP9)
Before running the method (it is quite expensive in case of time and resources) you may want to see exemplary graphical output or text output.
Usually, single run takes few hours.
Note:
- The maximal sequence length is set to 1000 amino acids.
- Input should be in plain text.
- All non-amino acid characters will be removed from the sequence.
- Input can be upper or lower case.
- Input should be in on letter amino acid code.
- Link to results will be sent via email. Alternativelly, you can bookmark result page, it will be automatically refreshed.
Metadisorder web service consists of four parts:
- metadisorder (the weighted consensus is build using 13 primary disorder methods: DisEMBL (3 versions), DISOPRED2, DISpro, Globplot, iPDA, IUPred (2 versions), Pdisorder, Poodle-s, Poodle-l, PrDOS, Spritz (2 versions), and RONN), this component was tested during CASP8 on which it proves to be the best method.
- metadisorder3d (this component uses fold recognition methods (PSI-BLAST, FFAS, HHsearch, Phyre, Pcons, MGenThreader) to find similar sequences. Genetic algorithm is used to infer protein disorder using gaps in the alignments.
- metadisordermd (combines two previous components into new meta method. Again, genetic algorithm is used to optimize components integration.
- metadisordermd2 (variant of metadisordermd for which different scoring function was used during genetic algorithm optimization step).
Contact: Lukasz Kozlowski
If you have more than 100 sequences for prediction, please send me the fasta file via email and I will add them to queue.
If you find MetaDisorder useful, please consider citing the reference that describes this work:
Kozlowski LP, Bujnicki JM. MetaDisorder: a meta-server for the prediction of intrinsic disorder in proteins. BMC Bioinformatics. 2012 May 24;13(1):111.
Export reference: BibTeX RIS (EndNote, ProCite, RefMan)
Tweet Follow @metadisorder
This work was supported by Polish Ministry of Science and Higher Education (grant NN301 190139).
My other projects:
- Proteome-pI 2.0 - Proteome Isoelectric Point Database 2.0 - predicted isoelectric point for ~61 million proteins accross 20,115 organisms
- IPC 2.0 - prediction of isoelectric point and pKa dissociation constants
- IPC - protein Isoelectric Point Calculator - isoelectric point and molecular weight from protein sequence
- Proteome-pI - Proteome Isoelectric Point Database - predicted isoelectric point for ~21 million proteins across 5,029 organisms
- GeneSilico fold recognition server - development and maintenance (over 100 bioinformatics tools integrated, 3000 registered users)
- CompaRNA - continuous benchmarking of RNA structure prediction methods
- GDFuzz3D - protein contact map to 3D structure retrieval service
- Shannon entropy calculator - Real example how to calculate and interpret information entropy
- RNA metaserver - Meta-tool for prediction of RNA secondary structure
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