MobiDB-lite: fast and highly specific consensus prediction of intrinsic disorder in proteins

Abstract

Abstract Motivation Intrinsic disorder (ID) is established as an important feature of protein sequences. Its use in proteome annotation is however hampered by the availability of many methods with similar performance at the single residue level, which have mostly not been optimized to predict long ID regions of size comparable to domains. Results Here, we have focused on providing a single consensus-based prediction, MobiDB-lite, optimized for highly specific (i.e. few false positive) predictions of long disorder. The method uses eight different predictors to derive a consensus which is then filtered for spurious short predictions. Consensus prediction is shown to outperform the single methods when annotating long ID regions. MobiDB-lite can be useful in large-scale annotation scenarios and has indeed already been integrated in the MobiDB, DisProt and InterPro databases. Availability and Implementation MobiDB-lite is available as part of the MobiDB database from URL: http://mobidb.bio.unipd.it/. An executable can be downloaded from URL: http://protein.bio.unipd.it/mobidblite/. Supplementary information Supplementary data are available at Bioinformatics online.

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Affiliated Institutions

• Fondazione Edmund Mach IT
• University of Padua IT
• Hungarian Academy of Sciences HU
• Eötvös Loránd University HU
• HUN-REN Research Centre for Natural Sciences HU
• Neuroscience Institute IT
• Institute of Molecular Life Sciences HU

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