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J Biomol Struct Dyn. 2018 Dec;36(16):4338-4351. doi: 10.1080/07391102.2017.1415822. Epub 2017 Dec 27.

Sequence fingerprints distinguish erroneous from correct predictions of intrinsically disordered protein regions.

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a Centre of Advanced Study in Crystallography & Biophysics , University of Madras , Guindy Campus, Chennai 600 025 , Tamilnadu , India.
b Centre for Computational Biology and Bioinformatics , Indiana University School of Medicine , Indianapolis , IN , USA.
c Institute of Mathematical Sciences , CIT Campus, Tharamani , Chennai 600 113 , Tamilnadu , India.


More than 60 prediction methods for intrinsically disordered proteins (IDPs) have been developed over the years, many of which are accessible on the World Wide Web. Nearly, all of these predictors give balanced accuracies in the ~65%-~80% range. Since predictors are not perfect, further studies are required to uncover the role of amino acid residues in native IDP as compared to predicted IDP regions. In the present work, we make use of sequences of 100% predicted IDP regions, false positive disorder predictions, and experimentally determined IDP regions to distinguish the characteristics of native versus predicted IDP regions. A higher occurrence of asparagine is observed in sequences of native IDP regions but not in sequences of false positive predictions of IDP regions. The occurrences of certain combinations of amino acids at the pentapeptide level provide a distinguishing feature in the IDPs with respect to globular proteins. The distinguishing features presented in this paper provide insights into the sequence fingerprints of amino acid residues in experimentally determined as compared to predicted IDP regions. These observations and additional work along these lines should enable the development of improvements in the accuracy of disorder prediction algorithm.


dipeptide analysis; native intrinsic disorder; predicted intrinsic disorder; secondary structure prediction; sequence fingerprint

[Indexed for MEDLINE]

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