scholarly journals Statistical Analysis of the Internal Distances of Helical Pairs in Protein Molecules

2016 ◽  
Vol 11 (2) ◽  
pp. 170-190 ◽  
Author(s):  
Д.А. Тихонов ◽  
D.A. Tikhonov
Keyword(s):  
Regression Analysis ◽  
Statistical Analysis ◽  
Protein Data Bank ◽  
Long Range ◽  
Data Bank ◽  
Interplanar Distance ◽  
Minimal Distance ◽  
Gamma Distributions ◽  
Protein Molecules ◽  
Plane Passing

The statistical analysis of interhelical distances in pairs of connected α-helices found in known proteins has been performed. In accordance with the certain rules, a database of the pairs found in the Protein Data Bank has been compiled. This set was subdivided into three subsets according to criterion of crossing helix projections on the parallel plane passing through the axis of the helix. It was shown that the distribution of distances between the pairs of helices whose projections are not crossed has a more long-range nature than those whose projections are overlapped. Using the regression analysis the nature of distributions is investigated. In particular, it is shown that the distributions of interhelical distances in the subset of pairs of helices without intersections belong to the gamma distributions. It is also shown that the subset of the pairs with crossing projections have a smaller ratio of the minimal distance between the helical axes to the interplanar distance that is contrast to the set without crossing projections. It was concluded that the helical pairs with crossing projections are additionally stabilized by internal interactions.

scholarly journals Disordered Residues and Patterns in the Protein Data Bank

Molecules ◽  
2020 ◽  
Vol 25 (7) ◽  
pp. 1522 ◽  
Author(s):  
Mikhail Yu. Lobanov ◽  
Ilya V. Likhachev ◽  
Oxana V. Galzitskaya
Keyword(s):  
Amino Acids ◽  
Statistical Analysis ◽  
Protein Data Bank ◽  
Protein Structures ◽  
3D Structure ◽  
Data Bank ◽  
Disordered Regions

We created a new library of disordered patterns and disordered residues in the Protein Data Bank (PDB). To obtain such datasets, we clustered the PDB and obtained the groups of chains with different identities and marked disordered residues. We elaborated a new procedure for finding disordered patterns and created a new version of the library. This library includes three sets of patterns: unique patterns, patterns consisting of two kinds of amino acids, and homo-repeats. Using this database, the user can: (1) find homologues in the entire Protein Data Bank; (2) perform a statistical analysis of disordered residues in protein structures; (3) search for disordered patterns and homo-repeats; (4) search for disordered regions in different chains of the same protein; (5) download clusters of protein chains with different identity from our database and library of disordered patterns; and (6) observe 3D structure interactively using MView. A new library of disordered patterns will help improve the accuracy of predictions for residues that will be structured or unstructured in a given region.

scholarly journals Analysis of the Torsion Angles between Helical Axes in Pairs of Helices in Protein Molecules

2017 ◽  
Vol 12 (2) ◽  
pp. 398-410 ◽  
Author(s):  
Д.А. Тихонов ◽  
D.A. Tikhonov
Keyword(s):  
Protein Data Bank ◽  
Data Bank ◽  
Structural Features ◽  
Torsion Angles ◽  
Protein Molecules ◽  
Helix Packing

In this study, an analysis of distribution of the torsion angles Ω between helical axes in pairs of connected helices found in known proteins has been performed. The database for helical pairs was compiled using the Protein Data Bank taking into account the definite rules suggested earlier. The database was analyzed in order to elaborate its classification and find out novel structural features in helix packing. The database was subdivided into three subsets according to criterion of crossing helix projections on the parallel planes passing through the axes of the helices. It was shown that helical pairs not having crossing projections are distributed along whole range of angles Ω, although there are two maxima at Ω = 0° and Ω = 180°. Most of helical pairs of this subset are pairs formed by α-helices and 310- helices. It is shown that the distribution of all the helical pairs having the crossing helix projections has a maximum at 20° < Ω < 25°. In this subset, most helical pairs are formed by α-helices. The distribution of only α-helical pairs having crossing axes projections has three maxima, at –50° < Ω < –25°, 20° < Ω < 25°, and 70° < Ω < 110°.

Packing bridges in protein crystal structures

2013 ◽  
Vol 47 (1) ◽  
pp. 458-461 ◽  
Author(s):  
Oliviero Carugo ◽  
Kristina Djinović-Carugo
Keyword(s):  
Statistical Analysis ◽  
Data Bank ◽  
Protein Crystal ◽  
Minor Amount ◽  
Nucleation Process ◽  
Related Protein ◽  
Crystallization Experiment ◽  
Protein Molecules ◽  
Crystallization Solution ◽  
A Minor

On the basis of a statistical analysis of the data deposited in the Protein Data Bank [Bermanet al.(2000).Nucleic Acids Res.28, 235–242; Bernsteinet al.(1977).J. Mol. Biol.112, 535–542], it is shown that two symmetry-related protein molecules are frequently bridged by a small molecule/monoatomic ion, which was used in the crystallization medium despite the fact that it is not a physiological ligand of the macromolecule. It is therefore sensible to suppose that some of the solutes used in crystallizations can favour the nucleation process by bridging and opportunely orienting adjacent protein molecules. This would explain why small changes in the composition of the crystallization solution, for example, the presence of a minor amount of a specific additive, can have a dramatic impact on the outcome of a crystallization experiment.

scholarly journals The study of interhelical angles in the structural motifs formed by two helices

2017 ◽  
Vol 12 (1) ◽  
pp. 83-101 ◽  
Author(s):  
Д.А. Тихонов ◽  
D.A. Tikhonov
Keyword(s):  
Statistical Analysis ◽  
Protein Data Bank ◽  
Entire Range ◽  
Structural Organization ◽  
Protein Structures ◽  
Data Bank ◽  
Acute Angle ◽  
Spatial Structures ◽  
Pass Through ◽  
Selection Of

In this paper a statistical analysis of distributions of inter-helical angles in pairs of consecutive and connected α-helices in spatial structures of proteins is presented. A number of rules for selection of the helical pairs from a set of protein structures obtained from the Protein Data Bank (PDB) were developed. The set of helical pairs has been analyzed for the purpose of classification and finding out the features of protein structural organization. All pairs of connected helices were divided into three subsets according to the criterion of crossing of projections of the helices on parallel planes, which pass through the axes of the helices. It is shown that the distribution of all types of helical pairs, whose projections do not cross each others, covers almost the entire range of inter-helical angles. The distribution have a single maximum which is close to right angle. Most pairs in this set constitute helical pairs consisting of α- and 310-helices, and most pairs with the crossing projections of helices are helical pairs formed by two α-helices. It is also shown that a great amount of the pairs of connected α-helices has acute angle 20° ≤ φ ≤ 60° between the axes of the helices. The distribution of all types of helical pairs depending on the length of the inter-helical connections was also analyzed. It is shown that the structures with short connections occur most often in all the subsets.

The Effects of Exercise Commitment Facilitated by Service Quality of Smartphone Exercise Applications on Continued Exercise Intention

2019 ◽  
Vol 118 (1) ◽  
pp. 14-19
Author(s):  
Boo-Gil Seok ◽  
Hyun-Suk Park
Keyword(s):  
College Students ◽  
Factor Analysis ◽  
Regression Analysis ◽  
Statistical Analysis ◽  
Correlation Analysis ◽  
Service Quality ◽  
Frequency Analysis ◽  
Primary Data ◽  
Exercise Intention

Background/Objectives: The purpose of this study is to examine the effects of exercise commitment facilitated by service quality of smartphone exercise Apps on continued exercise intention and provide primary data for developing and/or improving smartphone exercise Apps. Methods/Statistical analysis: A questionnaire survey was conducted amongst college students who have experiences in using exercise App(s) and regularly exercise. The questionnaire is composed of four parts asking about service quality, exercise commitment, continued exercise intention, which were measured with a 5-point Likert Scale, and demographics. Frequency analysis, factor analysis, correlation analysis, and regression analysis were carried out to analyze the obtained data with PASW 18.0.

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