Biomedical subjects

A Keith Dunker

Publications and source records attributed to A Keith Dunker.

At least 37 records · Page 2Linked to original sources

PubMed2005

Flexible nets. The roles of intrinsic disorder in protein interaction networks.

Proteins participate in complex sets of interactions that represent the mechanistic foundation for much of the physiology and function of the cell. These protein-protein interactions are organized into exquisitely complex networks. The architecture of protein-protein interaction networks was recently proposed to be scale-free, with most of the proteins having only one or two connections but with relatively fewer 'hubs' possessing tens, hundreds or more links. The high level of hub connectivity must somehow be reflected in protein structure. What structural quality of hub proteins enables them to interact with large numbers of diverse targets? One possibility would be to employ binding regions that have the ability to bind multiple, structurally diverse partners. This trait can be imparted by the incorporation of intrinsic disorder in one or both partners. To illustrate the value of such contributions, this review examines the roles of intrinsic disorder in protein network architecture. We show that there are three general ways that intrinsic disorder can contribute: First, intrinsic disorder can serve as the structural basis for hub protein promiscuity; secondly, intrinsically disordered proteins can bind to structured hub proteins; and thirdly, intrinsic disorder can provide flexible linkers between functional domains with the linkers enabling mechanisms that facilitate binding diversity. An important research direction will be to determine what fraction of protein-protein interaction in regulatory networks relies on intrinsic disorder.

Animals↗

PubMed2005

Optimizing long intrinsic disorder predictors with protein evolutionary information.

Protein existing as an ensemble of structures, called intrinsically disordered, has been shown to be responsible for a wide variety of biological functions and to be common in nature. Here we focus on improving sequence-based predictions of long (>30 amino acid residues) regions lacking specific 3-D structure by means of four new neural-network-based Predictors Of Natural Disordered Regions (PONDRs): VL3, VL3H, VL3P, and VL3E. PONDR VL3 used several features from a previously introduced PONDR VL2, but benefitted from optimized predictor models and a slightly larger (152 vs. 145) set of disordered proteins that were cleaned of mislabeling errors found in the smaller set. PONDR VL3H utilized homologues of the disordered proteins in the training stage, while PONDR VL3P used attributes derived from sequence profiles obtained by PSI-BLAST searches. The measure of accuracy was the average between accuracies on disordered and ordered protein regions. By this measure, the 30-fold cross-validation accuracies of VL3, VL3H, and VL3P were, respectively, 83.6 +/- 1.4%, 85.3 +/- 1.4%, and 85.2 +/- 1.5%. By combining VL3H and VL3P, the resulting PONDR VL3E achieved an accuracy of 86.7 +/- 1.4%. This is a significant improvement over our previous PONDRs VLXT (71.6 +/- 1.3%) and VL2 (80.9 +/- 1.4%). The new disorder predictors with the corresponding datasets are freely accessible through the web server at http://www.ist.temple.edu/disprot.

Algorithms↗

PubMed2004

Interaction between cardiac calsequestrin and drugs with known cardiotoxicity.

Ca(2+) regulation is coupled to critical signals in eucaryotic cells, and calsequestrin is one of the crucial components for this calcium regulation. Our previous observations of calsequestrins revealed the existence of three thioredoxin-like folds, a basic motif that often provides the platform for small molecule binding. Therefore, we have examined the previously reported trifluoperazine and other pharmaceuticals that have similar heart-related side effects (such as tachycardia; bradycardia; palpitation; changing PR, QRS, QTc intervals in electrocardiogram; heart failure) for their binding affinity to cardiac calsequestrin (cCSQ) using isothermal titration calorimetry. Our results showed that several antipsychotic phenothiazine derivatives, tricyclic antidepressants, and anthracycline derivatives bind cCSQ with K(d) in the micromolar range. For these compounds that have a significantly low K(d), their effect on Ca(2+) binding capacity of cCSQ was checked using equilibrium dialysis and atomic absorption spectroscopy, which clearly showed a significant reduction in Ca(2+) binding capacity of cCSQ as a result of this interaction. Furthermore, 8-anilino-1-naphthalene sulfonate (ANS) binding to cCSQ closely resembles ANS binding to flavine or nucleotide binding sites. The combination of this information with the high abundance of CSQ in SR and the high membrane permeability of those drugs led us to the specific hypothesis that there are undesirable and damaging interactions between cCSQ and tricyclic antidepressants, phenothiazine derivatives, anthracyclines, and many other pharmaceutical compounds and to the corollary hypothesis that better understanding of the molecular details of cCSQ-drug interactions could lead to modified drug molecules with reduced heart-related side effects.

Animals↗

PubMed2004

DisProt: a database of protein disorder.

UNLABELLED: The Database of Protein Disorder (DisProt) is a curated database that provides structure and function information about proteins that lack a fixed three-dimensional (3D) structure under putatively native conditions, either in their entirety or in part. Starting from the central premise that intrinsic disorder is an important structural class of protein and in order to meet the increasing interest thereof, DisProt is aimed at becoming a central repository of disorder-related information. For each disordered protein, the database includes the name of the protein, various aliases, accession codes, amino acid sequence, location of the disordered region(s), and methods used for structural (disorder) characterization. If applicable, most entries also list the biological function(s) of each disordered region, how each region of disorder is used for function, as well as provide links to PubMed abstracts and major protein databases. AVAILABILITY: www.disprot.org

Amino Acid Sequence↗

PubMed2004

The importance of intrinsic disorder for protein phosphorylation.

Reversible protein phosphorylation provides a major regulatory mechanism in eukaryotic cells. Due to the high variability of amino acid residues flanking a relatively limited number of experimentally identified phosphorylation sites, reliable prediction of such sites still remains an important issue. Here we report the development of a new web-based tool for the prediction of protein phosphorylation sites, DISPHOS (DISorder-enhanced PHOSphorylation predictor, http://www.ist.temple. edu/DISPHOS). We observed that amino acid compositions, sequence complexity, hydrophobicity, charge and other sequence attributes of regions adjacent to phosphorylation sites are very similar to those of intrinsically disordered protein regions. Thus, DISPHOS uses position-specific amino acid frequencies and disorder information to improve the discrimination between phosphorylation and non-phosphorylation sites. Based on the estimates of phosphorylation rates in various protein categories, the outputs of DISPHOS are adjusted in order to reduce the total number of misclassified residues. When tested on an equal number of phosphorylated and non-phosphorylated residues, the accuracy of DISPHOS reaches 76% for serine, 81% for threonine and 83% for tyrosine. The significant enrichment in disorder-promoting residues surrounding phosphorylation sites together with the results obtained by applying DISPHOS to various protein functional classes and proteomes, provide strong support for the hypothesis that protein phosphorylation predominantly occurs within intrinsically disordered protein regions.

Amino Acids↗

PubMed2004

Comparing skeletal and cardiac calsequestrin structures and their calcium binding: a proposed mechanism for coupled calcium binding and protein polymerization.

Calsequestrin, the major calcium storage protein of both cardiac and skeletal muscle, binds and releases large numbers of Ca(2+) ions for each contraction and relaxation cycle. Here we show that two crystal structures for skeletal and cardiac calsequestrin are nearly superimposable not only for their subunits but also their front-to-front-type dimers. Ca(2+) binding curves were measured using atomic absorption spectroscopy. This method enables highly accurate measurements even for Ca(2+) bound to polymerized protein. The binding curves for both skeletal and cardiac calsequestrin were complex, with binding increases that correlated with protein dimerization, tetramerization, and oligomerization. The Ca(2+) binding capacities of skeletal and cardiac calsequestrin are directly compared for the first time, with approximately 80 Ca(2+) ions bound per skeletal calsequestrin and approximately 60 Ca(2+) ions per cardiac calsequestrin, as compared with net charges for these molecules of -80 and -69, respectively. Deleting the negatively charged and disordered C-terminal 27 amino acids of cardiac calsequestrin results in a 50% reduction of its calcium binding capacity and a loss of Ca(2+)-dependent tetramer formation. Based on the crystal structures of rabbit skeletal muscle calsequestrin and canine cardiac calsequestrin, Ca(2+) binding capacity data, and previous light-scattering data, a mechanism of Ca(2+) binding coupled with polymerization is proposed.

Amino Acid Sequence↗

PubMed2004

Classification and knowledge discovery in protein databases.

We consider the problem of classification in noisy, high-dimensional, and class-imbalanced protein datasets. In order to design a complete classification system, we use a three-stage machine learning framework consisting of a feature selection stage, a method addressing noise and class-imbalance, and a method for combining biologically related tasks through a prior-knowledge based clustering. In the first stage, we employ Fisher's permutation test as a feature selection filter. Comparisons with the alternative criteria show that it may be favorable for typical protein datasets. In the second stage, noise and class imbalance are addressed by using minority class over-sampling, majority class under-sampling, and ensemble learning. The performance of logistic regression models, decision trees, and neural networks is systematically evaluated. The experimental results show that in many cases ensembles of logistic regression classifiers may outperform more expressive models due to their robustness to noise and low sample density in a high-dimensional feature space. However, ensembles of neural networks may be the best solution for large datasets. In the third stage, we use prior knowledge to partition unlabeled data such that the class distributions among non-overlapping clusters significantly differ. In our experiments, training classifiers specialized to the class distributions of each cluster resulted in a further decrease in classification error.

Algorithms↗

PubMed2004

Combining prediction, computation and experiment for the characterization of protein disorder.

Several computational and experimental methods exist for identifying disordered residues within proteins. Computational algorithms can now identify these disordered sequences and predict their occurrence within genomes with relatively high accuracy. Recent advances in NMR and mass spectroscopy permit faster and more detailed studies of disordered states at atomic resolutions. Combining prediction, computation and experimentation is proposed to accelerate and enhance the characterization of intrinsically disordered protein.

Hydrolysis↗

PubMed2004

Protein flexibility and intrinsic disorder.

Comparisons were made among four categories of protein flexibility: (1) low-B-factor ordered regions, (2) high-B-factor ordered regions, (3) short disordered regions, and (4) long disordered regions. Amino acid compositions of the four categories were found to be significantly different from each other, with high-B-factor ordered and short disordered regions being the most similar pair. The high-B-factor (flexible) ordered regions are characterized by a higher average flexibility index, higher average hydrophilicity, higher average absolute net charge, and higher total charge than disordered regions. The low-B-factor regions are significantly enriched in hydrophobic residues and depleted in the total number of charged residues compared to the other three categories. We examined the predictability of the high-B-factor regions and developed a predictor that discriminates between regions of low and high B-factors. This predictor achieved an accuracy of 70% and a correlation of 0.43 with experimental data, outperforming the 64% accuracy and 0.32 correlation of predictors based solely on flexibility indices. To further clarify the differences between short disordered regions and ordered regions, a predictor of short disordered regions was developed. Its relatively high accuracy of 81% indicates considerable differences between ordered and disordered regions. The distinctive amino acid biases of high-B-factor ordered regions, short disordered regions, and long disordered regions indicate that the sequence determinants for these flexibility categories differ from one another, whereas the significantly-greater-than-chance predictability of these categories from sequence suggest that flexible ordered regions, short disorder, and long disorder are, to a significant degree, encoded at the primary structure level.

Amino Acid Sequence↗

PubMed2004

Natively disordered proteins: functions and predictions.

Proteins can exist in at least three forms: the ordered form (solid-like), the partially folded form (collapsed, molten globule-like or liquid-like) and the extended form (extended, random coil-like or gas-like). The protein trinity hypothesis has two components: (i) a given native protein can be in any one of the three forms, depending on the sequence and the environment; and (ii) function can arise from any one of the three forms or from transitions between them. In this study, bioinformatics and data mining were used to investigate intrinsic disorder in proteins and develop neural network-based predictors of natural disordered regions (PONDR) that can discriminate between ordered and disordered residues with up to 84% accuracy. Predictions of intrinsic disorder indicate that the three kingdoms follow the disorder ranking eubacteria < archaebacteria << eukaryotes, with approximately half of eukaryotic proteins predicted to contain substantial regions of intrinsic disorder. Many of the known disordered regions are involved in signalling, regulation or control. Involvement of highly flexible or disordered regions in signalling is logical: a flexible sensor more readily undergoes conformational change in response to environmental perturbations than does a rigid one. Thus, the increased disorder in the eukaryotes is likely the direct result of an increased need for signalling and regulation in nucleated organisms. PONDR can also be used to detect molecular recognition elements that are disordered in the unbound state and become structured when bound to a biologically meaningful partner. Application of disorder predictions to cell-signalling, cancer-associated and control protein databases supports the widespread occurrence of protein disorder in these processes.

Amino Acid Sequence↗

PubMed2003

Flavors of protein disorder.

Intrinsically disordered proteins are characterized by long regions lacking 3-D structure in their native states, yet they have been so far associated with 28 distinguishable functions. Previous studies showed that protein predictors trained on disorder from one type of protein often achieve poor accuracy on disorder of proteins of a different type, thus indicating significant differences in sequence properties among disordered proteins. Important biological problems are identifying different types, or flavors, of disorder and examining their relationships with protein function. Innovative use of computational methods is needed in addressing these problems due to relative scarcity of experimental data and background knowledge related to protein disorder. We developed an algorithm that partitions protein disorder into flavors based on competition among increasing numbers of predictors, with prediction accuracy determining both the number of distinct predictors and the partitioning of the individual proteins. Using 145 variously characterized proteins with long (>30 amino acids) disordered regions, 3 flavors, called V, C, and S, were identified by this approach, with the V subset containing 52 segments and 7743 residues, C containing 39 segments and 3402 residues, and S containing 54 segments and 5752 residues. The V, C, and S flavors were distinguishable by amino acid compositions, sequence locations, and biological function. For the sequences in SwissProt and 28 genomes, their protein functions exhibit correlations with the commonness and usage of different disorder flavors, suggesting different flavor-function sets across these protein groups. Overall, the results herein support the flavor-function approach as a useful complement to structural genomics as a means for automatically assigning possible functions to sequences.

Algorithms↗

PubMed2003

Polymerization of calsequestrin. Implications for Ca2+ regulation.

Two distinct dimerization contacts in calsequestrin crystals suggested a mechanism for Ca(2+) regulation resulting from the occurrence of coupled Ca(2+) binding and protein polymerization. Ca(2+)-induced formation of one contact was proposed to lead to dimerization followed by Ca(2+)-induced formation of the second contact to bring about polymerization (). To test this mechanism, we compared canine cardiac calsequestrin and four truncation mutants with regard to their folding properties, structures, and Ca(2+)-induced polymerization. The wild-type calsequestrin and truncation mutants exhibited similar K(+)-induced folding and end-point structures as indicated by intrinsic fluorescence and circular dichroism, respectively, whereas the polymerization tendencies of the wild-type calsequestrin differed markedly from the polymerization tendencies of the truncation mutants. Static laser light scattering and 3,3'-dithiobis sulfosuccinimidyl-propionate cross-linking indicated that wild-type protein exhibited an initial Ca(2+)-induced dimerization, followed by additional oligomerization as the Ca(2+) concentration was raised or as the K(+) concentration was lowered. None of the truncation mutants exhibited clear stepwise oligomerization that depended on increasing Ca(2+) concentration. Comparison of the three-dimensional structure of rabbit skeletal calsequestrin with a homology model of canine cardiac calsequestrin from the point of view of our coupled Ca(2+) binding and polymerization mechanism leads to a possible explanation for the 2-fold reduced Ca(2+) binding capacity of cardiac calsequestrin despite very similar overall net negative charge for the two proteins.

Amino Acid Sequence↗

PubMed2003

Predicting intrinsic disorder from amino acid sequence.

Blind predictions of intrinsic order and disorder were made on 42 proteins subsequently revealed to contain 9,044 ordered residues, 284 disordered residues in 26 segments of length 30 residues or less, and 281 disordered residues in 2 disordered segments of length greater than 30 residues. The accuracies of the six predictors used in this experiment ranged from 77% to 91% for the ordered regions and from 56% to 78% for the disordered segments. The average of the order and disorder predictions ranged from 73% to 77%. The prediction of disorder in the shorter segments was poor, from 25% to 66% correct, while the prediction of disorder in the longer segments was better, from 75% to 95% correct. Four of the predictors were composed of ensembles of neural networks. This enabled them to deal more efficiently with the large asymmetry in the training data through diversified sampling from the significantly larger ordered set and achieve better accuracy on ordered and long disordered regions. The exclusive use of long disordered regions for predictor training likely contributed to the disparity of the predictions on long versus short disordered regions, while averaging the output values over 61-residue windows to eliminate short predictions of order or disorder probably contributed to the even greater disparity for three of the predictors. This experiment supports the predictability of intrinsic disorder from amino acid sequence.

Amino Acids↗

PubMed2003

Order, disorder, and flexibility: prediction from protein sequence.

The new predictor of disordered protein regions (disEMBL) introduced in this issue of Structure represents a computational tool developed to aid structural biologists in the design of protein constructs that avoid disordered protein regions in order to increase the success rate of structure determination.

Algorithms↗

PubMed2003

Improved amino acid flexibility parameters.

Protein molecules exhibit varying degrees of flexibility throughout their three-dimensional structures, with some segments showing little mobility while others may be so disordered as to be unresolvable by techniques such as X-ray crystallography. Atomic displacement parameters, or B-factors, from X-ray crystallographic studies give an experimentally determined indication of the degree of mobility in a protein structure. To provide better estimators of amino acid flexibility, we have examined B-factors from a large set of high-resolution crystal structures. Because of the differences among structures, it is necessary to normalize the B-factors. However, many proteins have segments of unusually high mobility, which must be accounted for before normalization can be performed. Accordingly, a median-based method from quality control studies was used to identify outliers. After removal of outliers from, and normalization of, each protein chain, the B-factors were collected for each amino acid in the set. It was found that the distribution of normalized B-factors followed a Gumbel, or extreme value distribution, and the location parameter, or mode, of this distribution was used as an estimator of flexibility for the amino acid. These new parameters have a higher correlation with experimentally determined B-factors than parameters from earlier methods.

Amino Acids↗

PubMed2003

Prediction of boundaries between intrinsically ordered and disordered protein regions.

Using proteins with both disordered and ordered regions collected through literature searches and database scanning, we assembled a set of 24-residue long segments centered on their order/disorder boundaries as well as a larger set of non-boundary segments consisting of either order or disorder. We analyzed position-specific amino acid compositions around the order/disorder boundaries and found more than thirty significant (p < 0.05) compositional differences between boundary and non-boundary data. From this analysis, we constructed several logistic regression predictors of order/disorder boundaries using slightly different data modeling approaches. Exact boundary prediction accuracies were estimated to be in the range from 74% to 80% for the different predictors.

Amino Acids↗

PubMed2002

Intrinsic disorder in cell-signaling and cancer-associated proteins.

The number of intrinsically disordered proteins known to be involved in cell-signaling and regulation is growing rapidly. To test for a generalized involvement of intrinsic disorder in signaling and cancer, we applied a neural network predictor of natural disordered regions (PONDR VL-XT) to four protein datasets: human cancer-associated proteins (HCAP), signaling proteins (AfCS), eukaryotic proteins from SWISS-PROT (EU_SW) and non-homologous protein segments with well-defined (ordered) 3D structure (O_PDB_S25). PONDR VL-XT predicts >or=30 consecutive disordered residues for 79(+/-5)%, 66(+/-6)%, 47(+/-4)% and 13(+/-4)% of the proteins from HCAP, AfCS, EU_SW, and O_PDB_S25, respectively, indicating significantly more intrinsic disorder in cancer-associated and signaling proteins as compared to the two control sets. The disorder analysis was extended to 11 additional functionally diverse categories of human proteins from SWISS-PROT. The proteins involved in metabolism, biosynthesis, and degradation together with kinases, inhibitors, transport, G-protein coupled receptors, and membrane proteins are predicted to have at least twofold less disorder than regulatory, cancer-associated and cytoskeletal proteins. In contrast to 44.5% of the proteins from representative non-membrane categories, just 17.3% of the cancer-associated proteins had sequence alignments with structures in the Protein Data Bank covering at least 75% of their lengths. This relative lack of structural information correlated with the greater amount of predicted disorder in the HCAP dataset. A comparison of disorder predictions with the experimental structural data for a subset of the HCAP proteins indicated good agreement between prediction and observation. Our data suggest that intrinsically unstructured proteins play key roles in cell-signaling, regulation and cancer, where coupled folding and binding is a common mechanism.

Amino Acid Sequence↗

PubMed2002

Hydrophobic probe binding of beta-lactoglobulin in the native and molten globule state induced by high pressure as affected by pH, KIO(3) and N-ethylmaleimide.

High hydrostatic pressure (HHP) at 500 MPa and 50 degrees C induces beta-LG into the molten globule state. Retinol, cis-parinaric acid (CPA), and 1-anilino-naphthalene-8-sulfonate (ANS) fluorescence from pH 2.5 to 10.5 in the presence of the native and molten globule states of beta-LG indicate that retinol binds to beta-LG in the calyx, CPA at the surface hydrophobic site, and ANS in multiple hydrophobic sites. HHP treatment results in a decrease of beta-LG affinity for retinol and CPA, suggesting conformational changes in the calyx and surface hydrophobic site of beta-LG during HHP treatment. beta-LG treated by HHP in the presence of N-ethylmaleimide (NEM) retains retinol affinity, suggesting that NEM protects the calyx conformation of beta-LG during HHP treatment. HHP treatment of beta-LG in the presence of KIO(3) exhibits a great decrease of CPA affinity compared to HHP-treated beta-LG in the absence of KIO(3), suggesting the formation of non-native disulfide bonding at the CPA binding site.

Anilino Naphthalenesulfonates↗