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Joseph P Zbilut

Publications and source records attributed to Joseph P Zbilut.

15 recordsLinked to original sources

A topologically related singularity suggests a maximum preferred size for protein domains.

A variety of protein physicochemical as well as topological properties, demonstrate a scaling behavior relative to chain length. Many of the scalings can be modeled as a power law which is qualitatively similar across the examples. In this article, we suggest a rational explanation to these observations on the basis of both protein connectivity and hydrophobic constraints of residues compactness relative to surface volume. Unexpectedly, in an examination of these relationships, a singularity was shown to exist near 255-270 residues length, and may be associated with an upper limit for domain size. Evaluation of related G-factor data points to a wide range of conformational plasticity near this point. In addition to its theoretical importance, we show by an application of CASP experimental and predicted structures, that the scaling is a practical filter for protein structure prediction.

Binding Sites↗

Entropic criteria for protein folding derived from recurrences: six residues patch as the basic protein word.

Some research has suggested that patches of six constitute an important amino acid window length in proteins for conveying information. We present database evidence that supports this conjecture, as well as additional recurrence-based data that characterization and quantification of these words affect the folding/aggregation features of proteins. Other indirect evidence is presented and discussed.

Amino Acid Sequence↗

Men in nursing.

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Attitude to Health↗

Detection of cardiac variability in the isolated rat heart.

Cardiac variability can be assessed from two perspectives: beat-to-beat performance and continuous performance during the cardiac cycle. Linear analysis techniques assess cardiac variability by measuring the physical attributes of a signal, whereas nonlinear techniques evaluate signal dynamics. This study sought to determine if recurrence quantification analysis (RQA), a nonlinear technique, could detect pharmacologically induced autonomic changes in the continuous left ventricular pressure (LVP) and electrographic (EC) signals from an isolated rat heart-a model that theoretically contains no inherent variability. LVP and EC signal data were acquired simultaneously during Langendorff perfusion of isolated rat hearts before and after the addition of acetylcholine (n = 11), norepinephrine (n = 12), or no drug (n = 12). Two-minute segments of the continuous LVP and EC signal data were analyzed by RQA. Findings showed that%recurrence,%determinism, entropy, maxline, and trend from the continuous LVP signal significantly increased in the presence of both acetylcholine and norepinephrine, although systolic LVP significantly increased only with norepinephrine. In the continuous EC signal, the RQA trend variable significantly increased in the presence of norepinephrine. These results suggest that when either the sympathetic or parasympathetic division of the autonomic nervous system overwhelms the other, the dynamics underlying cardiac variability become stationary. This study also shows that information concerning inherent variability in the isolated rat heart can be gained via RQA of the continuous cardiac signal. Although speculative, RQA may be a tool for detecting alterations in cardiac variability and evaluating signal dynamics as a nonlinear indicator of cardiac pathology.

Acetylcholine↗

Early events in protein aggregation: molecular flexibility and hydrophobicity/charge interaction in amyloid peptides as studied by molecular dynamics simulations.

In a previous article (Zbilut et al., Biophys J 2003;85:3544-3557), we demonstrated how an aggregation versus folding choice could be approached considering hydrophobicity distribution and charge. In this work, our aim is highlighting the mutual interaction of charge and hydrophobicity distribution in the aggregation process. Use was made of two different peptides, both derived from a transmembrane protein (amyloid precursor protein; APP), namely, Abeta(1-28) and Abeta(1-40). Abeta(1-28) has a much lower aggregation propensity than Abeta(1-40). The results obtained by means of molecular dynamics simulations show that, when submitted to the most "aggregation-prone" environment, corresponding to the isoelectric point and consequently to zero net charge, both peptides acquire their maximum flexibility, but Abeta(1-40) has a definitely higher conformational mobility than Abeta(1-28). The absence of a hydrophobic "tail," which is the most mobile part of the molecule in Abeta(1-40), is the element lacking in Abeta(1-28) for obtaining a "fully aggregating" phenotype. Our results suggest that conformational flexibility, determined by both hydrophobicity and charge effect, is the main mechanistic determinant of aggregation propensity.

Amyloid↗

Discrimination of single amino acid mutations of the p53 protein by means of deterministic singularities of recurrence quantification analysis.

p53 is mutated in roughly 50% of all human tumors, predominantly in the DNA-binding domain codons. Structural, biochemical, and functional studies have reported that the different p53 mutants possess a broad range of behaviors that include the elimination of the tumor-suppression function of wild-type protein, the acquisition of dominant-negative function over the wild-type form, and the establishment of gain-of-function activities. The contribution of each of these types of mutations to tumor progression, grade of malignancy, and response to anticancer treatments has been so far analyzed only for a few "hot-spots." In an attempt to identify new approaches to systematically characterize the complete spectrum of p53 mutations, we applied recurrence quantification analysis (RQA), a non-linear signal analysis technique, to p53 primary structure. Moving from the study of the p53 hydrophobicity pattern, which revealed important similarities with the singular deterministic structuring of prions, we could statistically discriminate, on a pure amino acid sequence basis, between experimentally characterized DNA-contact defective and conformational p53 mutants with a very high percentage of success. This result indicates that RQA is a mathematical tool particularly advantageous for the development of a database of p53 mutations that integrates epidemiological data with structural and functional categorizations.

Amino Acid Sequence↗

EMG recurrence quantifications in dynamic exercise.

This study was designed to evaluate the suitability of nonlinear recurrence quantification analysis (RQA) in assessing electromyograph (EMG) signals during dynamic exercise. RQA has been proven to be effective in analyzing nonstationary signals. The subject group consisted of 19 male patients diagnosed with low back pain. EMG signals were recorded from left and right paraspinal muscles during isoinertial exercise both before and after 12 weeks of regimented physical therapy. Autorecurrence analysis was performed between the left and right EMG signals individually, and cross-recurrence analysis was performed on the left-right EMG pairs. Spectral analysis of the EMG signals was employed as an independent, objective measure of fatigue. Increase in the RQA variable % determinism during the 90-s dynamic tests was found to be a good marker for fatigue. Before physical therapy, this nonlinear marker revealed simultaneous increases in motor unit recruitment within each pool and between left and right pools. After physical therapy, the motor unit recruitment was less within and between pools, indicative of increased fatigue resistance. Finally, fatigue resistance (less increase in % determinism) correlated well with subjective scores of pain relief. Taken together, these latter results indicate that recurrence analysis may be useful in charting the efficacy of a specific exercise therapy program in reducing low back pain by elevating the fatigue threshold.

Electromyography↗

Application of trilinear SLICING to analyse a single relaxation curve.

Determining the time constants and amplitudes of exponential decays from relaxation data is a common task in LF-NMR. In this communication, we present an application of the SLICING algorithm to evaluate its possibilities for solving this problem. The method, originally introduced to compare different samples, is applied here to analyse a single relaxation curve, using the embedding technique. To test this procedure, we acquired data sets from samples of liquids properly separated, and characterized by different relaxation times. The results show a good estimation of parameters, comparable with those obtained applying Marquardt's algorithm, when the components have sufficiently different relaxation times.

Journal Article↗

Protein aggregation/folding: the role of deterministic singularities of sequence hydrophobicity as determined by nonlinear signal analysis of acylphosphatase and Abeta(1-40).

The problem of protein folding vs. aggregation was investigated in acylphosphatase and the amyloid protein Abeta(1-40) by means of nonlinear signal analysis of their chain hydrophobicity. Numerical descriptors of recurrence patterns provided the basis for statistical evaluation of folding/aggregation distinctive features. Static and dynamic approaches were used to elucidate conditions coincident with folding vs. aggregation using comparisons with known protein secondary structure classifications, site-directed mutagenesis studies of acylphosphatase, and molecular dynamics simulations of amyloid protein, Abeta(1-40). The results suggest that a feature derived from principal component space characterized by the smoothness of singular, deterministic hydrophobicity patches plays a significant role in the conditions governing protein aggregation.

Acid Anhydride Hydrolases↗

Recurrence quantification analysis as a tool for nonlinear exploration of nonstationary cardiac signals.

The complexity, nonlinearity and nonstationarity of the cardiovascular system typically defy comprehensive and deterministic mathematical modeling, except from a statistical perspective. Living systems are governed by numerous, continuously changing, interacting variables in the presence of noise. Cardiovascular signals can be shown to be discontinuous alternations between deterministic trajectories and stochastic pauses (terminal dynamics). One promising approach for assessing such nondeterministic complexity is recurrence quantification analysis (RQA). As reviewed in this paper, strategies implementing quantification of recurrences have been successful in diagnosing changes in nonstationary cardiac signals not easily detected by traditional methods. It is concluded that recurrence quantification analysis is a powerful discriminatory tool which, when properly applied to cardiac signals, can provide objectivity regarding the degree of determinism characterizing the system, state changes, as well as degrees of complexity and/or randomness.

Algorithms↗

Review of nonlinear analysis of proteins through recurrence quantification.

This review considers the use of a nonlinear signal analysis tool, recurrence quantification analysis, as a method to study sequence/structure relationships of proteins. Four broad categories are discussed: (1) a point of view involving information contained in deterministic aspects of hydrophobicity; (2) the analysis of protein hydrophobicity "singularities"; (3) time-series analysis of protein dynamics simulations; and (4) prediction of protein secondary structure.

Algorithms↗

Structure-related statistical singularities along protein sequences: a correlation study.

A data set composed of 1141 proteins representative of all eukaryotic protein sequences in the Swiss-Prot Protein Knowledge base was coded by seven physicochemical properties of amino acid residues. The resulting numerical profiles were submitted to correlation analysis after the application of a linear (simple mean) and a nonlinear (Recurrence Quantification Analysis, RQA) filter. The main RQA variables, Recurrence and Determinism, were subsequently analyzed by Principal Component Analysis. The RQA descriptors showed that (i) within protein sequences is embedded specific information neither present in the codes nor in the amino acid composition and (ii) the most sensitive code for detecting ordered recurrent (deterministic) patterns of residues in protein sequences is the Miyazawa-Jernigan hydrophobicity scale. The most deterministic proteins in terms of autocorrelation properties of primary structures were found (i) to be involved in protein-protein and protein-DNA interactions and (ii) to display a significantly higher proportion of structural disorder with respect to the average data set. A study of the scaling behavior of the average determinism with the setting parameters of RQA (embedding dimension and radius) allows for the identification of patterns of minimal length (six residues) as possible markers of zones specifically prone to inter- and intramolecular interactions.

Amino Acid Sequence↗

Charge and hydrophobicity patterning along the sequence predicts the folding mechanism and aggregation of proteins: a computational approach.

The presence of partially folded intermediates along the folding funnel of proteins has been suggested to be a signature of potentially aggregating systems. Many studies have concluded that metastable, highly flexible intermediates are the basic elements of the aggregation process. In a previous paper, we demonstrated how the choice between aggregation and folding behavior was influenced by hydrophobicity distribution patterning along the sequence, as quantified by recurrence quantification analysis (RQA) of the Myiazawa-Jernigan coded primary structures. In the present paper, we tried to unify the "partially folded intermediate" and "hydrophobicity/charge" models of protein aggregation verifying the ability of an empirical relation, developed for rationalizing the effect of different mutations on aggregation propensity of acyl-phosphatase and based on the combination of hydrophobicity RQA and charge descriptors, to discriminate in a statistically significant way two different protein populations: (a) proteins that fold by a process passing by partially folded intermediates and (b) proteins that do not present partially folded intermediates.

Acid Anhydride Hydrolases↗