title: How to Predict Disorder in a Protein of Interest.
abstract: Currently available computational tools, which are many, provide a researcher with the multitude of options for prediction of intrinsic disorder in a protein of interest and for finding at least some of its disorder-based functions. This chapter provides a highly subjective guideline on how not to be lost in the "dark forest" of available tools for the analysis of intrinsic disorder. By no means it gives a unique pathway through this forest, but simply presents some of the tools the author uses in his everyday research.
authors: Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, 33612, USA. vuversky@health.usf.edu.|Institute for Biological Instrumentation, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russian Federation. vuversky@health.usf.edu.|Laboratory of Structural Dynamics, Stability and Folding of Proteins, Institute of Cytology, Russian Academy of Sciences, St. Petersburg, Russian Federation. vuversky@health.usf.edu.
authors: Vladimir N
authors: VN
authors: Uversky
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence / Q000235:genetics; D019295:Computational Biology; D030562:Databases, Protein; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry / Q000235:genetics*; D020539:Sequence Analysis, Protein; D012984:Software
chemical_list: D011506:Proteins
keywords: Intrinsically disordered protein; Posttranslational modification; Prediction; Protein function; Protein–protein interaction