A Keith Dunker

Indiana University-Purdue University School of Medicine, Indianapolis, Indiana, United States

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Publications (285)922.6 Total impact

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    ABSTRACT: Intrinsically disordered regions (IDRs) are highly populated in eukaryotic proteomes and serve pivotal, mostly regulatory functions. Many IDRs appear to be functionally conserved and analysis of protein domains indicates high pro-pensity of conserved regions predicted to be disordered. Nevertheless, it is difficult to assess conservation of IDRs in gen-eral due to their fast evolution and low sequence similarity. We propose three measures to evaluate conservation of IDRs: i) similarities of the disorder profiles using different prediction conditions; ii) the conservation of amino acids with pro-pensities for promoting either disorder or order; and iii) the overlap between disordered/ordered regions. These measures are computed on multiple sequence alignments that also include low-complexity regions of proteins. Using three subunits of the Mediator complex of transcription regulation from Homo sapiens and Drosophila melanogaster as an example we show that despite of their sequence dissimilarity IDRs can be conserved and likely carry out the same function in different organisms.
    Full-text · Article · Jun 2008 · The Open Proteomics Journal
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    ABSTRACT: Parasitic protozoal infections have long been known to cause profound degrees of sickness and death in humans as well as animal populations. Despite the increase in the number of annotated genomes available for a large variety of protozoa, a great deal more has yet to be learned about them, from their fundamental physiology to mechanisms invoked during host-pathogen interactions. Most of these genomes share a common feature, namely a high prevalence of low complexity regions in their predicted proteins, which is believed to contribute to the uniqueness of the individual species within this diverse group of early-branching eukaryotes. In the case of Plasmodium species, which cause malaria, such regions have also been reported to hamper the identification of homologues, thus making functional genomics exceptionally challenging. One of the better accepted theories accounting for the high number of low complexity regions is the presence of intrinsic disorder in these microbes. In this study we compare the degree of disordered proteins that are predicted to be expressed in many such ancient eukaryotic cells. Our findings indicate an unusual bias in the amino acids comprising protozoal proteomes, and show that intrinsic disorder is remarkably abundant among their predicted proteins. Additionally, the intrinsically disordered regions tend to be considerably longer in the early-branching eukaryotes. An analysis of a Plasmodium falciparum interactome indicates that protein-protein interactions may be at least one function of the intrinsic disorder. This study provides a bioinfomatics basis for the discovery and analysis of unfoldomes (the complement of intrinsically disordered proteins in a given proteome) of early-branching eukaryotes. It also provides new insights into the evolution of intrinsic disorder in the context of adapting to a parasitic lifestyle and lays the foundation for further work on the subject.
    Full-text · Article · May 2008 · Molecular BioSystems
  • A Keith Dunker · Vladimir N Uversky
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    ABSTRACT: Signaling via phosphorylation-regulated protein-protein interactions often involves flexible or unstructured proteins. Detailed biophysical and computational studies on one such interaction reveal a marvelously intricate, temporally regulated, multistep conduit for signal transduction in the cell cycle.
    No preview · Article · May 2008 · Nature Chemical Biology
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    Wei Zhang · A Keith Dunker · Yaoqi Zhou
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    ABSTRACT: How to make an objective assignment of secondary structures based on a protein structure is an unsolved problem. Defining the boundaries between helix, sheet, and coil structures is arbitrary, and commonly accepted standard assignments do not exist. Here, we propose a criterion that assesses secondary structure assignment based on the similarity of the secondary structures assigned to pairwise sequence-alignment benchmarks, where these benchmarks are determined by prior structural alignments of the protein pairs. This criterion is used to rank six secondary structure assignment methods: STRIDE, DSSP, SECSTR, KAKSI, P-SEA, and SEGNO with three established sequence-alignment benchmarks (PREFAB, SABmark, and SALIGN). STRIDE and KAKSI achieve comparable success rates in assigning the same secondary structure elements to structurally aligned residues in the three benchmarks. Their success rates are between 1-4% higher than those of the other four methods. The consensus of STRIDE, KAKSI, SECSTR, and P-SEA, called SKSP, improves assignments over the best single method in each benchmark by an additional 1%. These results support the usefulness of the sequence-alignment benchmarks as a means to evaluate secondary structure assignment. The SKSP server and the benchmarks can be accessed at http://sparks.informatics.iupui.edu
    Full-text · Article · Apr 2008 · Proteins Structure Function and Bioinformatics
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    ABSTRACT: Intrinsically disordered proteins (IDPs) lack stable tertiary and/or secondary structures under physiological conditions in vitro. They are highly abundant in nature and their functional repertoire complements the functions of ordered proteins. IDPs are involved in regulation, signaling, and control, where binding to multiple partners and high-specificity/low-affinity interactions play a crucial role. Functions of IDPs are tuned via alternative splicing and posttranslational modifications. Intrinsic disorder is a unique structural feature that enables IDPs to participate in both one-to-many and many-to-one signaling. Numerous IDPs are associated with human diseases, including cancer, cardiovascular disease, amyloidoses, neurodegenerative diseases, and diabetes. Overall, intriguing interconnections among intrinsic disorder, cell signaling, and human diseases suggest that protein conformational diseases may result not only from protein misfolding, but also from misidentification, missignaling, and unnatural or nonnative folding. IDPs, such as alpha-synuclein, tau protein, p53, and BRCA1, are attractive targets for drugs modulating protein-protein interactions. From these and other examples, novel strategies for drug discovery based on IDPs have been developed. To summarize work in this area, we are introducing the D2 (disorder in disorders) concept.
    Full-text · Article · Feb 2008 · Annual Review of Biophysics
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    ABSTRACT: Proteins are involved in many interactions with other proteins leading to networks that regulate and control a wide variety of physiological processes. Some of these proteins, called hub proteins or hubs, bind to many different protein partners. Protein intrinsic disorder, via diversity arising from structural plasticity or flexibility, provide a means for hubs to associate with many partners (Dunker AK, Cortese MS, Romero P, Iakoucheva LM, Uversky VN: Flexible Nets: The roles of intrinsic disorder in protein interaction networks. FEBS J 2005, 272:5129-5148). Here we present a detailed examination of two divergent examples: 1) p53, which uses different disordered regions to bind to different partners and which also has several individual disordered regions that each bind to multiple partners, and 2) 14-3-3, which is a structured protein that associates with many different intrinsically disordered partners. For both examples, three-dimensional structures of multiple complexes reveal that the flexibility and plasticity of intrinsically disordered protein regions as well as induced-fit changes in the structured regions are both important for binding diversity. These data support the conjecture that hub proteins often utilize intrinsic disorder to bind to multiple partners and provide detailed information about induced fit in structured regions.
    Full-text · Article · Feb 2008 · BMC Genomics
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    ABSTRACT: To examine the usefulness of protein disorder predictions as a tool for the comparative analysis of viral proteins, a relational database has been constructed. The database includes proteins from influenza A and HIV-related viruses. Annotations include viral protein sequence, disorder prediction, structure, and function. Location of each protein within a virion, if known, is also denoted. Our analysis reveals a clear relationship between proximity to the RNA core and the percentage of predicted disordered residues for a set of influenza A virus proteins. Neuraminidases (NA) and hemagglutinin (HA) of major influenza A pandemics tend to pair in such a way that both proteins tend to be either ordered-ordered or disordered-disordered by prediction. This may be the result of these proteins evolving from being lipid-associated. High abundance of intrinsic disorder in envelope and matrix proteins from HIV-related viruses likely represents a mechanism where HIV virions can escape immune response despite the availability of antibodies for the HIV-related proteins. This exercise provides an example showing how the combined use of intrinsic disorder predictions and relational databases provides an improved understanding of the functional and structural behaviour of viral proteins.
    Full-text · Article · Feb 2008 · BMC Genomics
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    ABSTRACT: Intrinsically disordered proteins carry out various biological functions while lacking ordered secondary and/or tertiary structure. In order to find general intrinsic properties of amino acid residues that are responsible for the absence of ordered structure in intrinsically disordered proteins we surveyed 517 amino acid scales. Each of these scales was taken as an independent attribute for the subsequent analysis. For a given attribute value X, which is averaged over a consecutive string of amino acids, and for a given data set having both ordered and disordered segments, the conditional probabilities P(s(o) | x) and P(s(d) | x) for order and disorder, respectively, can be determined for all possible values of X. Plots of the conditional probabilities P(s(o) | x) and P(s(o) | x) versus X give a pair of curves. The area between these two curves divided by the total area of the graph gives the area ratio value (ARV), which is proportional to the degree of separation of the two probability curves and, therefore, provides a measure of the given attribute's power to discriminate between order and disorder. As ARV falls between zero and one, larger ARV corresponds to the better discrimination between order and disorder. Starting from the scale with the highest ARV, we applied a simulated annealing procedure to search for alternative scale values and have managed to increase the ARV by more than 10%. The ranking of the amino acids in this new TOP-IDP scale is as follows (from order promoting to disorder promoting): W, F, Y, I, M, L, V, N, C, T, A, G, R, D, H, Q, K, S, E, P. A web-based server has been created to apply the TOP-IDP scale to predict intrinsically disordered proteins (http://www.disprot.org/dev/disindex.php).
    Full-text · Article · Feb 2008 · Protein and Peptide Letters
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    Jack Y Yang · Mary Qu Yang · A Keith Dunker · Youping Deng · Xudong Huang
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    ABSTRACT: An important subfamily of membrane proteins are the transmembrane alpha-helical proteins, in which the membrane-spanning regions are made up of alpha-helices. Given the obvious biological and medical significance of these proteins, it is of tremendous practical importance to identify the location of transmembrane segments. The difficulty of inferring the secondary or tertiary structure of transmembrane proteins using experimental techniques has led to a surge of interest in applying techniques from machine learning and bioinformatics to infer secondary structure from primary structure in these proteins. We are therefore interested in determining which physicochemical properties are most useful for discriminating transmembrane segments from non-transmembrane segments in transmembrane proteins, and for discriminating intrinsically unstructured segments from intrinsically structured segments in transmembrane proteins, and in using the results of these investigations to develop classifiers to identify transmembrane segments in transmembrane proteins. We determined that the most useful properties for discriminating transmembrane segments from non-transmembrane segments and for discriminating intrinsically unstructured segments from intrinsically structured segments in transmembrane proteins were hydropathy, polarity, and flexibility, and used the results of this analysis to construct classifiers to discriminate transmembrane segments from non-transmembrane segments using four classification techniques: two variants of the Self-Organizing Global Ranking algorithm, a decision tree algorithm, and a support vector machine algorithm. All four techniques exhibited good performance, with out-of-sample accuracies of approximately 75%. Several interesting observations emerged from our study: intrinsically unstructured segments and transmembrane segments tend to have opposite properties; transmembrane proteins appear to be much richer in intrinsically unstructured segments than other proteins; and, in approximately 70% of transmembrane proteins that contain intrinsically unstructured segments, the intrinsically unstructured segments are close to transmembrane segments.
    Full-text · Article · Feb 2008 · BMC Genomics
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    ABSTRACT: Protein interactions are essential for most cellular functions. Interactions mediated by domains that appear in a large number of proteins are of particular interest since they are expected to have an impact on diversities of cellular processes such as signal transduction and immune response. Many well represented domains recognize and bind to primary sequences less than 10 amino acids in length called Short Linear Motifs (SLiMs). In this study, we systematically studied the evolutionary conservation of SLiMs recognized by SH2, SH3 and Ser/Thr Kinase domains in both ordered and disordered protein regions. Disordered protein regions are protein sequences that lack a fixed three-dimensional structure under putatively native conditions. We find that, in all these domains examined, SLiMs are more conserved in disordered regions. This trend is more evident in those protein functional groups that are frequently reported to interact with specific domains. The correlation between SLiM conservation with disorder prediction demonstrates that functional SLiMs recognized by each domain occur more often in disordered as compared to structured regions of proteins.
    Full-text · Article · Feb 2008 · BMC Genomics
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    ABSTRACT: Our first predictor of protein disorder was published just over a decade ago in the Proceedings of the IEEE International Conference on Neural Networks (Romero P, Obradovic Z, Kissinger C, Villafranca JE, Dunker AK (1997) Identifying disordered regions in proteins from amino acid sequence. Proceedings of the IEEE International Conference on Neural Networks, 1: 90-95). By now more than twenty other laboratory groups have joined the efforts to improve the prediction of protein disorder. While the various prediction methodologies used for protein intrinsic disorder resemble those methodologies used for secondary structure prediction, the two types of structures are entirely different. For example, the two structural classes have very different dynamic properties, with the irregular secondary structure class being much less mobile than the disorder class. The prediction of secondary structure has been useful. On the other hand, the prediction of intrinsic disorder has been revolutionary, leading to major modifications of the more than 100 year-old views relating protein structure and function. Experimentalists have been providing evidence over many decades that some proteins lack fixed structure or are disordered (or unfolded) under physiological conditions. In addition, experimentalists are also showing that, for many proteins, their functions depend on the unstructured rather than structured state; such results are in marked contrast to the greater than hundred year old views such as the lock and key hypothesis. Despite extensive data on many important examples, including disease-associated proteins, the importance of disorder for protein function has been largely ignored. Indeed, to our knowledge, current biochemistry books don't present even one acknowledged example of a disorder-dependent function, even though some reports of disorder-dependent functions are more than 50 years old. The results from genome-wide predictions of intrinsic disorder and the results from other bioinformatics studies of intrinsic disorder are demanding attention for these proteins. Disorder prediction has been important for showing that the relatively few experimentally characterized examples are members of a very large collection of related disordered proteins that are wide-spread over all three domains of life. Many significant biological functions are now known to depend directly on, or are importantly associated with, the unfolded or partially folded state. Here our goal is to review the key discoveries and to weave these discoveries together to support novel approaches for understanding sequence-function relationships. Intrinsically disordered protein is common across the three domains of life, but especially common among the eukaryotic proteomes. Signaling sequences and sites of posttranslational modifications are frequently, or very likely most often, located within regions of intrinsic disorder. Disorder-to-order transitions are coupled with the adoption of different structures with different partners. Also, the flexibility of intrinsic disorder helps different disordered regions to bind to a common binding site on a common partner. Such capacity for binding diversity plays important roles in both protein-protein interaction networks and likely also in gene regulation networks. Such disorder-based signaling is further modulated in multicellular eukaryotes by alternative splicing, for which such splicing events map to regions of disorder much more often than to regions of structure. Associating alternative splicing with disorder rather than structure alleviates theoretical and experimentally observed problems associated with the folding of different length, isomeric amino acid sequences. The combination of disorder and alternative splicing is proposed to provide a mechanism for easily "trying out" different signaling pathways, thereby providing the mechanism for generating signaling diversity and enabling the evolution of cell differentiation and multicellularity. Finally, several recent small molecules of interest as potential drugs have been shown to act by blocking protein-protein interactions based on intrinsic disorder of one of the partners. Study of these examples has led to a new approach for drug discovery, and bioinformatics analysis of the human proteome suggests that various disease-associated proteins are very rich in such disorder-based drug discovery targets.
    Full-text · Article · Feb 2008 · BMC Genomics
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    ABSTRACT: IntroductionMethods Used to Characterize Natively Disordered ProteinsDo Natively Disordered Proteins Exist Inside Cells?Functional RepertoireImportance of Disorder for Protein FoldingExperimental Protocols
    No preview · Chapter · Jan 2008
  • Liwei Li · Vladimir N Uversky · A. Keith Dunker,†,‡ and · Samy O Meroueh
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    ABSTRACT: The catabolite activator protein is a dimer that consists of two cAMP-binding subunits, each containing a C-terminus DNA-binding module and a N-terminus ligand binding domain. The system is well-known to exhibit negative cooperativity, whereby the binding of one cAMP molecule reduces the binding affinity of the other cAMP molecule by 2 orders of magnitude, despite the large separation between the cAMP binding pockets. Here we use extensive explicit-solvent molecular dynamics simulations (135 ns) to investigate the allosteric mechanism of CAP. Six trajectories were carried out for apo, singly liganded, and doubly liganded CAP, both in the presence and absence of DNA. Thorough analyses of the dynamics through the construction of dynamical cross-correlated maps, as well as essential dynamics analyses, indicated that the system experienced a switch in motion as a result of cAMP binding, in accordance with recent NMR experiments carried out on a truncated form of the protein. Analyses of conformer structures collected from the simulations revealed a remarkable event: the DNA-binding module was found to dissociate from the N-terminus ligand binding domain. An interesting aspect of this structural change is that it only occurred in unoccupied subunits, suggesting that the binding of cAMP provides additional stability to the system, consistent with the increase in entropy that was observed in our calculations and from isothermal titration calorimetry. Analysis of the distribution of intrinsic disorder propensities in CAP amino acid sequence using PONDR VLXT and VSL1 predictors revealed that the region connecting ligand-binding and DNA-binding domains of CAP have the potential to exhibit increased flexibility. We complemented these trajectories with free energy calculations following the MM-PBSA approach on more than 2000 snapshots that included 880 normal mode analysis. The resulting free energy differences between the singly liganded and doubly liganded states were in excellent agreement with isothermal titration calorimetry data. When the free energy calculations were carried out in the presence of DNA, we discovered that a switch in cooperativity occurred, so that the binding of the first cAMP promoted the binding of the other cAMP. The components of the free energy reveal that this effect is mainly entropic in nature, whereby the DNA reduces the degree of tightening that is observed in its absence, thereby promoting binding of the second cAMP. This finding prompted us to propose a new mechanism by which CAP triggers the transcription activation that is based on an order to disorder transition mediated by cAMP binding as well as DNA.
    No preview · Article · Jan 2008 · Journal of the American Chemical Society
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    ABSTRACT: Previously described algorithms for mining alpha-helix-forming molecular recognition elements (MoREs), described by Oldfield et al. (Oldfield, C. J., Cheng, Y., Cortese, M. S., Brown, C. J., Uversky, V. N., and Dunker, A. K. (2005) Comparing and combining predictors of mostly disordered proteins, Biochemistry 44, 1989-2000), also known as molecular recognition features (MoRFs) (Mohan, A., Oldfield, C. J., Radivojac, P., Vacic, V., Cortese, M. S., Dunker, A. K., and Uversky, V. N. (2006) Analysis of Molecular Recognition Features (MoRFs), J. Mol. Biol. 362, 1043-1059), revealed that regions undergoing disorder-to-order transition are involved in many molecular recognition events and are crucial for protein-protein interactions. However, these algorithms were developed using a training data set of a limited size. Here we propose to improve the prediction algorithms by (1) including additional alpha-MoRF examples and their cross species homologues in the positive training set, (2) carefully extracting monomer structure chains from the Protein Data Bank (PDB) as the negative training set, (3) including attributes from recently developed disorder predictors, secondary structure predictions, and amino acid indices, and (4) constructing neural network based predictors and performing validation. Over 50 regions which undergo disorder-to-order transition that were identified in the PDB together with a set of corresponding cross species homologues of each structure-based example were included in a new positive training set. Over 1500 attributes, including disorder predictions, secondary structure predictions, and amino acid indices, were evaluated by the conditional probability method. The top attributes, including VSL2 and VL3 disorder predictions and several physicochemical propensities of amino acid residues, were used to develop the feed forward neural networks. The sensitivity, specificity, and accuracy of the resulting predictor, alpha-MoRF-PredII, were 0.87 +/- 0.10, 0.87 +/- 0.11, and 0.87 +/- 0.08 over 10 cross validations, respectively. We present the results of these analyses and validation examples to discuss the potential improvement of the alpha-MoRF-PredII prediction accuracy.
    Full-text · Article · Dec 2007 · Biochemistry
  • V.N. Uversky · C.J. Oldfield · A K Dunker
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    ABSTRACT: Intrinsically disordered proteins lack stable tertiary and/or secondary structure under physiological conditions in vitro. They are highly abundant in nature, with ~25-30% of eukaryotic proteins being mostly disordered, and with >50% of eukaryotic proteins and > 70% of signaling proteins having long disordered regions. Functional repertoire of intrinsically disordered proteins is very broad and complements functions of ordered proteins. Often, intrinsically disordered proteins are involved in regulation, signaling and control pathways, where binding to multiple partners and high-speciflcity/low-afflnity interactions play a crucial role. We have found that out of the 711 Swiss-Prot functional keywords associated with at least 20 proteins, 262 were strongly positively correlated with long intrinsically disordered regions, and 302 were strongly negatively correlated. It is suggested that functions of intrinsically disordered proteins may arise from the specific disorder form, from inter-conversion of disordered forms, or from transitions between disordered and ordered conformations. The choice between these conformations is determined by the peculiarities of the protein environment, and many intrinsically disordered proteins possess an exceptional ability to fold in a template-dependent manner. Intrinsically disordered proteins are key players in protein-protein interaction networks being highly abundant among hubs. Furthermore, regions of mRNA which undergo alternative splicing code for disordered proteins much more often than they code for structured proteins. This association of alternative splicing and intrinsic disorder helps proteins to avoid folding difficulties and provides a novel mechanism for developing tissue-specific protein interaction networks. Numerous intrinsically disordered proteins are associated with such human diseases as cancer, cardiovascular disease, amyloidoses, neurodegenerative diseases, diabetes and others. Our bioinformatics analys- is revealed that many human diseases are strongly correlated with proteins predicted to be disordered. Contrary to this, we did not find disease associated proteins to be strongly correlated with absence of disorder. Overall, there is an intriguing interconnection between intrinsic disorder, cell signaling and human diseases, which suggests that protein conformational diseases may result not only from protein misfolding, but also from misidentification and missignaling. Intrinsically disordered proteins, such as alpha-synuclein, tau protein, p53, BRCA1 and many other disease-associated hub proteins represent attractive targets for drugs modulating protein-protein interactions. Therefore, novel strategies for drug discovery are based on intrinsically disordered proteins.
    No preview · Conference Paper · Nov 2007
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    A Keith Dunker
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    ABSTRACT: Current biochemistry textbooks discuss the typical functions of globular proteins in terms of “lock and key” and “induced fit” models. The lock and key model depends on a structured protein with a rigid binding site, while the original induced fit model was described in terms of a structured protein with a flexible binding site that undergoes conformational change upon interaction with its ligand. Induced fit was later extended to include binding site changes resulting from domain shifts. For both the lock and key and the induced fit models, the formation of protein 3D structure is a prerequisite to function and can be described as the sequence → structure → function paradigm.
    Preview · Article · Oct 2007 · Structure
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    ABSTRACT: The functional specificity of type 1 protein phosphatases (PP1) depends on the associated regulatory/targeting and inhibitory subunits. To gain insights into the mechanism of PP1 regulation by inhibitor-2, an ancient and intrinsically disordered regulator, we solved the crystal structure of the complex to 2.5Å resolution. Our studies show that, when complexed with PP1c, I-2 acquires three regions of order: site 1, residues 12-17, binds adjacent to a region recognized by many PP1 regulators; site 2, amino acids 44-56, interacts along the RVXF binding groove through an unsuspected sequence, KSQKW; and site 3, residues 130-169, forms α-helical regions that lie across the substrate-binding cleft. Specifically, residues 148-151 interact at the catalytic center, displacing essential metal ions, accounting for both rapid inhibition and slower inactivation of PP1c. Thus, our structure provides novel insights into the mechanism of PP1 inhibition and subsequent reactivation, has broad implications for the physiological regulation of PP1, and highlights common inhibitory interactions among phosphoprotein phosphatase family members.
    Preview · Article · Oct 2007 · Journal of Biological Chemistry
  • A Keith Dunker

    No preview · Chapter · Sep 2007
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    ABSTRACT: Molecular Recognition Features (MoRFs) are short, interaction-prone segments of protein disorder that undergo disorder-to-order transitions upon specific binding, representing a specific class of intrinsically disordered regions that exhibit molecular recognition and binding functions. MoRFs are common in various proteomes and occupy a unique structural and functional niche in which function is a direct consequence of intrinsic disorder. Example MoRFs collected from the Protein Data Bank (PDB) have been divided into three subtypes according to their structures in the bound state: alpha-MoRFs form alpha-helices, beta-MoRFs form beta-strands, and iota-MoRFs form structures without a regular pattern of backbone hydrogen bonds. These example MoRFs were indicated to be intrinsically disordered in the absence of their binding partners by several criteria. In this study, we used several geometric and physiochemical criteria to examine the properties of 62 alpha-, 20 beta-, and 176 iota-MoRF complex structures. Interface residues were examined by calculating differences in accessible surface area between the complex and isolated monomers. The compositions and physiochemical properties of MoRF and MoRF partner interface residues were compared to the interface residues of homodimers, heterodimers, and antigen-antibody complexes. Our analysis indicates that there are significant differences in residue composition and several geometric and physicochemical properties that can be used to discriminate, with a high degree of accuracy, between various interfaces in protein interaction data sets. Implications of these findings for the development of MoRF-partner interaction predictors are discussed. In addition, structural changes upon MoRF-to-partner complex formation were examined for several illustrative examples.
    Full-text · Article · Jul 2007 · Journal of Proteome Research
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    A Keith Dunker · Ariel Fernández
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    ABSTRACT: Natural enzymes were selected to function inside the cell, not in the test tube; therefore, their performance is optimized for the crowded conditions encountered in vivo. Most man-made matrices for enzyme confinement lead to suboptimal catalytic activity. Ackerman and colleagues showed that an entrapping environment consisting of functionalized mesoporous silica actually enhances enzyme activity beyond the test-tube levels of free enzymes in solution. These findings provide an approach for dissecting the effect of various contributors to enzyme activity and thereby provide a means for fine-tuning the entrapping matrices to optimize enzyme performance in a rational way.
    Full-text · Article · Jun 2007 · Trends in Biotechnology

Publication Stats

23k Citations
922.60 Total Impact Points

Institutions

  • 2005-2015
    • Indiana University-Purdue University School of Medicine
      • Department of Biochemistry and Molecular Biology
      Indianapolis, Indiana, United States
    • Indiana University Bloomington
      • Department of Informatics
      Bloomington, IN, United States
  • 2003-2015
    • Indiana University-Purdue University Indianapolis
      • • Center for Computational Biology and Bioinformatics
      • • Department of Medicine
      • • Department of Biochemistry and Molecular Biology
      Indianapolis, Indiana, United States
    • Temple University
      • Department of Computer and Information Science
      Philadelphia, Pennsylvania, United States
  • 2012
    • University of South Florida
      Tampa, Florida, United States
  • 1978-2012
    • Washington State University
      • • School of Mechanical and Materials Engineering
      • • Department of Biological Systems Engineering
      • • School of Molecular Biosciences
      • • School of Electrical Engineering and Computer Science
      • • Department of Chemistry
      Pullman, Washington, United States
  • 2009
    • Hungarian Academy of Sciences
      • Institute of Enzymology
      Budapest, Budapest fovaros, Hungary
    • University of Missouri
      • Department of Computer Science and IT
      Columbia, MO, United States
  • 2008
    • Universität Basel
      • Department of Biophysical Chemistry
      Bâle, Basel-City, Switzerland
  • 1980
    • University of Oregon
      • Department of Chemistry
      Eugene, Oregon, United States