Format

Send to

Choose Destination
Int J Mol Sci. 2015 Jun 16;16(6):13829-49. doi: 10.3390/ijms160613829.

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

Author information

1
Department of Physics, University of South Florida, Tampa, FL 33620, USA. aidan1@mail.usf.edu.
2
Department of Cell Biology, Microbiology, and Molecular Biology, School of Natural Sciences and Mathematics, College of Arts and Sciences, University of South Florida, Tampa, FL 33620, USA. bornea@mail.usf.edu.
3
Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL 33620, USA. vuversky@health.usf.edu.
4
Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow Region 142290, Russian. vuversky@health.usf.edu.
5
Department of Biology, Faculty of Science, King Abdulaziz University, P.O. Box 80203, Jeddah 21589, Saudi Arabia. vuversky@health.usf.edu.
6
Laboratory of Structural Dynamics, Stability and Folding of Proteins, Institute of Cytology, Russian Academy of Sciences, St. Petersburg 194064, Russian. vuversky@health.usf.edu.
7
Department of Cell Biology, Microbiology, and Molecular Biology, School of Natural Sciences and Mathematics, College of Arts and Sciences, University of South Florida, Tampa, FL 33620, USA. binxue@usf.edu.

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).

KEYWORDS:

disorder pattern; dynamic programming; dynamic time warping; intrinsic disorder; structural flexibility

PMID:
26086829
PMCID:
PMC4490526
DOI:
10.3390/ijms160613829
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Multidisciplinary Digital Publishing Institute (MDPI) Icon for PubMed Central
Loading ...
Support Center