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      Unfoldomics of human diseases: linking protein intrinsic disorder with diseases

      research-article
      1 , 2 , 3 , , 1 , 4 , 4 , 1 , 2 , 4 , 5 , 4 , 1
      BMC Genomics
      BioMed Central
      The 2008 International Conference on Bioinformatics & Computational Biology (BIOCOMP'08)
      14–17 July 2008

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          Abstract

          Background

          Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) lack stable tertiary and/or secondary structure yet fulfills key biological functions. The recent recognition of IDPs and IDRs is leading to an entire field aimed at their systematic structural characterization and at determination of their mechanisms of action. Bioinformatics studies showed that IDPs and IDRs are highly abundant in different proteomes and carry out mostly regulatory functions related to molecular recognition and signal transduction. These activities complement the functions of structured proteins. IDPs and IDRs were shown to participate in both one-to-many and many-to-one signaling. Alternative splicing and posttranslational modifications are frequently used to tune the IDP functionality. Several individual IDPs were shown to be associated with human diseases, such as cancer, cardiovascular disease, amyloidoses, diabetes, neurodegenerative diseases, and others. This raises questions regarding the involvement of IDPs and IDRs in various diseases.

          Results

          IDPs and IDRs were shown to be highly abundant in proteins associated with various human maladies. As the number of IDPs related to various diseases was found to be very large, the concepts of the disease-related unfoldome and unfoldomics were introduced. Novel bioinformatics tools were proposed to populate and characterize the disease-associated unfoldome. Structural characterization of the members of the disease-related unfoldome requires specialized experimental approaches. IDPs possess a number of unique structural and functional features that determine their broad involvement into the pathogenesis of various diseases.

          Conclusion

          Proteins associated with various human diseases are enriched in intrinsic disorder. These disease-associated IDPs and IDRs are real, abundant, diversified, vital, and dynamic. These proteins and regions comprise the disease-related unfoldome, which covers a significant part of the human proteome. Profound association between intrinsic disorder and various human diseases is determined by a set of unique structural and functional characteristics of IDPs and IDRs. Unfoldomics of human diseases utilizes unrivaled bioinformatics and experimental techniques, paves the road for better understanding of human diseases, their pathogenesis and molecular mechanisms, and helps develop new strategies for the analysis of disease-related proteins.

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          Most cited references89

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          Intrinsically unstructured proteins: re-assessing the protein structure-function paradigm.

          A major challenge in the post-genome era will be determination of the functions of the encoded protein sequences. Since it is generally assumed that the function of a protein is closely linked to its three-dimensional structure, prediction or experimental determination of the library of protein structures is a matter of high priority. However, a large proportion of gene sequences appear to code not for folded, globular proteins, but for long stretches of amino acids that are likely to be either unfolded in solution or adopt non-globular structures of unknown conformation. Characterization of the conformational propensities and function of the non-globular protein sequences represents a major challenge. The high proportion of these sequences in the genomes of all organisms studied to date argues for important, as yet unknown functions, since there could be no other reason for their persistence throughout evolution. Clearly the assumption that a folded three-dimensional structure is necessary for function needs to be re-examined. Although the functions of many proteins are directly related to their three-dimensional structures, numerous proteins that lack intrinsic globular structure under physiological conditions have now been recognized. Such proteins are frequently involved in some of the most important regulatory functions in the cell, and the lack of intrinsic structure in many cases is relieved when the protein binds to its target molecule. The intrinsic lack of structure can confer functional advantages on a protein, including the ability to bind to several different targets. It also allows precise control over the thermodynamics of the binding process and provides a simple mechanism for inducibility by phosphorylation or through interaction with other components of the cellular machinery. Numerous examples of domains that are unstructured in solution but which become structured upon binding to the target have been noted in the areas of cell cycle control and both transcriptional and translational regulation, and unstructured domains are present in proteins that are targeted for rapid destruction. Since such proteins participate in critical cellular control mechanisms, it appears likely that their rapid turnover, aided by their unstructured nature in the unbound state, provides a level of control that allows rapid and accurate responses of the cell to changing environmental conditions. Copyright 1999 Academic Press.
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            p53 mutations in human cancers.

            Mutations in the evolutionarily conserved codons of the p53 tumor suppressor gene are common in diverse types of human cancer. The p53 mutational spectrum differs among cancers of the colon, lung, esophagus, breast, liver, brain, reticuloendothelial tissues, and hemopoietic tissues. Analysis of these mutations can provide clues to the etiology of these diverse tumors and to the function of specific regions of p53. Transitions predominate in colon, brain, and lymphoid malignancies, whereas G:C to T:A transversions are the most frequent substitutions observed in cancers of the lung and liver. Mutations at A:T base pairs are seen more frequently in esophageal carcinomas than in other solid tumors. Most transitions in colorectal carcinomas, brain tumors, leukemias, and lymphomas are at CpG dinucleotide mutational hot spots. G to T transversions in lung, breast, and esophageal carcinomas are dispersed among numerous codons. In liver tumors in persons from geographic areas in which both aflatoxin B1 and hepatitis B virus are cancer risk factors, most mutations are at one nucleotide pair of codon 249. These differences may reflect the etiological contributions of both exogenous and endogenous factors to human carcinogenesis.
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              The PSIPRED protein structure prediction server.

              The PSIPRED protein structure prediction server allows users to submit a protein sequence, perform a prediction of their choice and receive the results of the prediction both textually via e-mail and graphically via the web. The user may select one of three prediction methods to apply to their sequence: PSIPRED, a highly accurate secondary structure prediction method; MEMSAT 2, a new version of a widely used transmembrane topology prediction method; or GenTHREADER, a sequence profile based fold recognition method. Freely available to non-commercial users at http://globin.bio.warwick.ac.uk/psipred/
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                Author and article information

                Conference
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2009
                7 July 2009
                : 10
                : Suppl 1
                : S7
                Affiliations
                [1 ]Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
                [2 ]Institute for Intrinsically Disordered Protein Research, Indiana University School of Medicine, Indianapolis, IN 46202, USA
                [3 ]Institute for Biological Instrumentation, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia
                [4 ]Center for Information Science and Technology, Temple University, Philadelphia, PA 19122, USA
                [5 ]Laboratory of Statistical Genetics, The Rockefeller University, New York, NY 10065 USA
                Article
                1471-2164-10-S1-S7
                10.1186/1471-2164-10-S1-S7
                2709268
                19594884
                987f8839-a584-4efc-94d4-e705c8c99824
                Copyright © 2009 Uversky et al; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                The 2008 International Conference on Bioinformatics & Computational Biology (BIOCOMP'08)
                Las Vegas, NV, USA
                14–17 July 2008
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                Genetics
                Genetics

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