Ken Nishikawa

What's in a name? Why these proteins are intrinsically disordered: Why these proteins are intrinsically disordered.

“What’s in a name? That which we call a rose By any other name would smell as sweet.” From “Romeo and Juliet”, William Shakespeare (1594) This article opens a series of publications on disambiguation of the basic terms used in the field of intrinsically disordered proteins. We start from the beginning, namely from the explanation of what the expression “intrinsically disordered protein” actually means and why this particular term has been chosen as the common denominator for this class of proteins characterized by broad structural, dynamic and functional characteristics.

Binary classification of protein molecules into intrinsically disordered and ordered segments

BackgroundAlthough structural domains in proteins (SDs) are important, half of the regions in the human proteome are currently left with no SD assignments. These unassigned regions consist not only of novel SDs, but also of intrinsically disordered (ID) regions since proteins, especially those in eukaryotes, generally contain a significant fraction of ID regions. As ID regions can be inferred from amino acid sequences, a method that combines SD and ID region assignments can determine the fractions of SDs and ID regions in any proteome.ResultsIn contrast to other available ID prediction programs that merely identify likely ID regions, the DICHOT system we previously developed classifies the entire protein sequence into SDs and ID regions. Application of DICHOT to the human proteome revealed that residue-wise ID regions constitute 35%, SDs with similarity to PDB structures comprise 52%, while SDs with no similarity to PDB structures account for the remaining 13%. The last group consists of novel structural domains, termed cryptic domains, which serve as good targets of structural genomics. The DICHOT method applied to the proteomes of other model organisms indicated that eukaryotes generally have high ID contents, while prokaryotes do not. In human proteins, ID contents differ among subcellular localizations: nuclear proteins had the highest residue-wise ID fraction (47%), while mitochondrial proteins exhibited the lowest (13%). Phosphorylation and O-linked glycosylation sites were found to be located preferentially in ID regions. As O-linked glycans are attached to residues in the extracellular regions of proteins, the modification is likely to protect the ID regions from proteolytic cleavage in the extracellular environment. Alternative splicing events tend to occur more frequently in ID regions. We interpret this as evidence that natural selection is operating at the protein level in alternative splicing.ConclusionsWe classified entire regions of proteins into the two categories, SDs and ID regions and thereby obtained various kinds of complete genome-wide statistics. The results of the present study are important basic information for understanding protein structural architectures and have been made publicly available at http://spock.genes.nig.ac.jp/~genome/DICHOT.

Computational Prediction of O-linked Glycosylation Sites that Preferentially Map on Intrinsically Disordered Regions of Extracellular Proteins

O-glycosylation of mammalian proteins is one of the important posttranslational modifications. We applied a support vector machine (SVM) to predict whether Ser or Thr is glycosylated, in order to elucidate the O-glycosylation mechanism. O-glycosylated sites were often found clustered along the sequence, whereas other sites were located sporadically. Therefore, we developed two types of SVMs for predicting clustered and isolated sites separately. We found that the amino acid composition was effective for predicting the clustered type, whereas the site-specific algorithm was effective for the isolated type. The highest prediction accuracy for the clustered type was 74%, while that for the isolated type was 79%. The existence frequency of amino acids around the O-glycosylation sites was different in the two types: namely, Pro, Val and Ala had high existence probabilities at each specific position relative to a glycosylation site, especially for the isolated type. Independent component analyses for the amino acid sequences around O-glycosylation sites showed the position-specific existences of the identified amino acids as independent components. The O-glycosylation sites were preferentially located within intrinsically disordered regions of extracellular proteins: particularly, more than 90% of the clustered O-GalNAc glycosylation sites were observed in intrinsically disordered regions. This feature could be the key for understanding the non-conservation property of O-glycosylation, and its role in functional diversity and structural stability.

Development of an accurate classification system of proteins into structured and unstructured regions that uncovers novel structural domains: its application to human transcription factors

BackgroundIn addition to structural domains, most eukaryotic proteins possess intrinsically disordered (ID) regions. Although ID regions often play important functional roles, their accurate identification is difficult. As human transcription factors (TFs) constitute a typical group of proteins with long ID regions, we regarded them as a model of all proteins and attempted to accurately classify TFs into structural domains and ID regions. Although an extremely high fraction of ID regions besides DNA binding and/or other domains was detected in human TFs in our previous investigation, 20% of the residues were left unassigned. In this report, we exploit the generally higher sequence divergence in ID regions than in structural regions to completely divide proteins into structural domains and ID regions.ResultsThe new dichotomic system first identifies domains of known structures, followed by assignment of structural domains and ID regions with a combination of pre-existing tools and a newly developed program based on sequence divergence, taking un-aligned regions into consideration. The system was found to be highly accurate: its application to a set of proteins with experimentally verified ID regions had an error rate as low as 2%. Application of this system to human TFs (401 proteins) showed that 38% of the residues were in structural domains, while 62% were in ID regions. The preponderance of ID regions makes a sharp contrast to TFs of Escherichia coli (229 proteins), in which only 5% fell in ID regions. The method also revealed that 4.0% and 11.8% of the total length in human and E. coli TFs, respectively, are comprised of structural domains whose structures have not been determined.ConclusionThe present system verifies that sequence divergence including information of unaligned regions is a good indicator of ID regions. The system for the first time estimates the complete fractioning of structured/un-structured regions in human TFs, also revealing structural domains without homology to known structures. These predicted novel structural domains are good targets of structural genomics. When applied to other proteins, the system is expected to uncover more novel structural domains.

The GTOP database in 2009: updated content and novel features to expand and deepen insights into protein structures and functions

The Genomes TO Protein Structures and Functions (GTOP) database (http://spock.genes.nig.ac.jp/~genome/gtop.html) freely provides an extensive collection of information on protein structures and functions obtained by application of various computational tools to the amino acid sequences of entirely sequenced genomes. GTOP contains annotations of 3D structures, protein families, functions, and other useful data of a protein of interest in user-friendly ways to give a deep insight into the protein structure. From the initial 1999 version, GTOP has been continually updated to reap the fruits of genome projects and augmented to supply novel information, in particular intrinsically disordered regions. As intrinsically disordered regions constitute a considerable fraction of proteins and often play crucial roles especially in eukaryotes, their assignments give important additional clues to the functionality of proteins. Additionally, we have incorporated the following features into GTOP: a platform independent structural viewer, results of HMM searches against SCOP and Pfam, secondary structure predictions, color display of exon boundaries in eukaryotic proteins, assignments of gene ontology terms, search tools, and master files.

Natively unfolded proteins: An overview

Proteins with wholly or partly denatured structures in vivo are called intrinsically disordered or natively unfolded proteins (NUPs). Functional importance of NUPs was revealed by NMR studies as first reviewed by P. Wright in 1999. Since then, computational analyses on NUPs have also been intensively carried out to predict that approximately one third of eukaryotic proteins are NUPs. I will start this overview with the question why it took so long to identify NUPs as an important subject of protein science, and then move on to several issues such as, whether or not NUPs are specific to eukaryotes, what a particularly higher fraction of NUPs existing in the nucleus means, and what evolutionary implications NUPs have.

Structure of the F-spondin reeler domain reveals a unique β-sandwich fold with a deformable disulfide-bonded loop

F-spondin is a secreted and extracellular matrix-attached protein that has been implicated in axonal pathfinding during neural development as well as in vascular remodelling in adult tissues. F-spondin is composed of a reeler, a spondin and six thrombospondin type 1 repeat domains. The reeler domain shares homology with the amino-terminal domain of reelin, a large secreted glycoprotein that guides migrating neurons during cortical development. Crystal structures of the F-spondin reeler domain were determined at 1.45 and 2.70 A resolution. The structure revealed a nine-stranded antiparallel beta-sandwich fold similar to the immunoglobulin or fibronectin type III domains, but with a unique extra beta-hairpin. Moreover, an amino-terminal extension which is anchored at its beginning via a conserved disulfide bond loosely packs against one face of the beta-sandwich, making a major contribution to the surface features of the domain. Structural comparison among the different molecules contained in two different crystals reveals an unusual conformational plasticity of the amino-terminal loop, suggesting its role in molecular interactions.

Cooperation between phenotypic plasticity and genetic mutations can account for the cumulative selection in evolution

We propose the cooperative model of phenotype-driven evolution, in which natural selection operates on a phenotype caused by both genetic and epigenetic factors. The conventional theory of evolutionary synthesis assumes that a phenotypic value (P) is the sum of genotypic value (G) and environmental deviation (E), P=G+E, where E is the fluctuations of the phenotype among individuals in the absence of environmental changes. In contrast, the cooperative model assumes that an evolution is triggered by an environmental change and individuals respond to the change by phenotypic plasticity (epigenetic changes). The phenotypic plasticity, while essentially qualitative, is denoted by a quantitative value F which is modeled as a normal random variable like E, but with a much larger variance. Thus, the fundamental equation of the cooperative model is given as P=G+F where F includes the effect of E. Computer simulations using a genetic algorithm demonstrated that the cooperative model realized much faster evolution than the evolutionary synthesis. This accelerated evolution was found to be due to the cumulative evolution made possible by a ratchet mechanism due to the epigenetic contribution to the phenotypic value. The cooperative model can well account for the phenomenon of genetic assimilation, which, in turn, suggests the mechanism of cumulative selection. The cooperative model may also serve as a theoretical basis to understand various ideas and phenomena of the phenotype-driven evolution such as genetic assimilation, the theory of facilitated phenotypic variation, and epigenetic inheritance over generations.

Intrinsically disordered proteins in human mitochondria.

Intrinsically disordered (ID) proteins (IDPs) are abundant in eukaryotes but are scarce in prokaryotes. Mitochondria, cellular organelles that descended from Rickettsia‐like α‐proteobacteria, are at the intersection between prokaryotes and eukaryotes. Although IDPs are reportedly as rare in mitochondria as in bacteria, these details remained to be clarified. Human mitochondrial proteins (n = 706) were obtained from the UniProt database, and information on ID regions of all human proteins was extracted from the DICHOT database. A BLAST search carried out against all α‐proteobacterial proteins identified two types of mitochondrial proteins: those with (B) and without (E) bacterial homologues. The B‐type proteins (n = 387) descended from a bacterial ancestor, whereas the E‐type proteins (n = 319) were more recently added to the mitochondria via the host cell during the early evolution of eukaryotes. The average ID ratios of B‐type/E‐type proteins are 10.3% and 21.4%, respectively. The 706 proteins were further classified into four groups based on the mitochondrial subcompartment, namely, the matrix, intermembrane space, inner membrane, or outer membrane. The ID ratios in these different locations suggest that the frequency of IDPs in mitochondria might be due to the evolutionary origin (B‐type/E‐type) of the protein, rather than differences in its functional environment.

Two dimensional position detection method using bi-directional leaky coaxial cable based on TDOA

Position detection of wireless terminal tends to be important technology in wireless communication system. Demand for position detection is increasing. This paper proposes position detection method using bi-directional LCX (Leaky CoaXial cable). Due to bi-directional and the reflection at end of LCX on purpose, proposed method makes four propagation pathes. Proposed system can detect two dimensional position using the differences of four propagation times. This paper describes the equations for position detection and optimal arrangement about slots.