NDLI: Identifying Similar Patterns of Structural Flexibility in Proteins by Disorder Prediction and Dynamic Programming

Content Provider	PubMed Central
Author	Petrovich, Aidan Borne, Adam Uversky, Vladimir N. Xue, Bin
Editor	Kurgan, Lukasz
Copyright Year	2015
Abstract	Computational methods are prevailing in identifying protein intrinsic disorder. The results from predictors are often given as per-residue disorder scores. The scores describe the disorder propensity of amino acids of a protein and can be further represented as a disorder curve. Many proteins share similar patterns in their disorder curves. The similar patterns are often associated with similar functions and evolutionary origins. Therefore, finding and characterizing specific patterns of disorder curves provides a unique and attractive perspective of studying the function of intrinsically disordered proteins. In this study, we developed a new computational tool named IDalign using dynamic programming. This tool is able to identify similar patterns among disorder curves, as well as to present the distribution of intrinsic disorder in query proteins. The disorder-based information generated by IDalign is significantly different from the information retrieved from classical sequence alignments. This tool can also be used to infer functions of disordered regions and disordered proteins. The web server of IDalign is available at (http://labs.cas.usf.edu/bioinfo/service.html).
Related Links	http://dx.doi.org/10.3390/ijms160613829
Ending Page	13849
Page Count	21
Starting Page	13829
File Format	PDF
ISSN	14220067
e-ISSN	14220067
Journal	International Journal of Molecular Sciences
Issue Number	6
Volume Number	16
Language	English
Publisher	MDPI
Publisher Date	2015-06-01
Access Restriction	Open
Rights Holder	MDPI
Subject Keyword	Physical and Theoretical Chemistry Inorganic Chemistry Organic Chemistry Spectroscopy Molecular Biology Catalysis Computer Science Applications Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Spectroscopy Organic Chemistry Medicine Molecular Biology Physical and Theoretical Chemistry Catalysis Inorganic Chemistry Computer Science Applications

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