Utilization of protein intrinsic disorder knowledge in structural proteomics |
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Authors: | Christopher J. Oldfield Bin Xue Ya-Yue Van Eldon L. Ulrich John L. Markley A. Keith Dunker Vladimir N. Uversky |
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Affiliation: | 1. Center for Computational Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana 46202, USA;2. Department of Molecular Medicine, College of Medicine, University of South Florida, Tampa, Florida 33612, USA;3. Molecular Kinetics, 6201 La Pas Trail, Indianapolis, Indiana 46268, USA;4. Center for Eukaryotic Structural Genomics, University of Wisconsin-Madison, 433 Babcock Drive, Madison, Wisconsin 53706-1549, USA;5. Byrd Alzheimer''s Research Institute, College of Medicine, University of South Florida, Tampa, FL 33612, USA;6. Institute for Biological Instrumentation, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia |
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Abstract: | Intrinsically disordered proteins (IDPs) and proteins with long disordered regions are highly abundant in various proteomes. Despite their lack of well-defined ordered structure, these proteins and regions are frequently involved in crucial biological processes. Although in recent years these proteins have attracted the attention of many researchers, IDPs represent a significant challenge for structural characterization since these proteins can impact many of the processes in the structure determination pipeline. Here we investigate the effects of IDPs on the structure determination process and the utility of disorder prediction in selecting and improving proteins for structural characterization. Examination of the extent of intrinsic disorder in existing crystal structures found that relatively few protein crystal structures contain extensive regions of intrinsic disorder. Although intrinsic disorder is not the only cause of crystallization failures and many structured proteins cannot be crystallized, filtering out highly disordered proteins from structure-determination target lists is still likely to be cost effective. Therefore it is desirable to avoid highly disordered proteins from structure-determination target lists and we show that disorder prediction can be applied effectively to enrich structure determination pipelines with proteins more likely to yield crystal structures. For structural investigation of specific proteins, disorder prediction can be used to improve targets for structure determination. Finally, a framework for considering intrinsic disorder in the structure determination pipeline is proposed. |
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Keywords: | Proteomics Structural genomics Structural proteomics Intrinsically disordered protein |
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