scholarly journals Amide-π interactions in active centers of superoxide dismutase

2021 ◽  
pp. 42-42
Author(s):  
Srdjan Stojanovic ◽  
Zoran Petrovic ◽  
Mario Zlatovic
Keyword(s):  
Superoxide Dismutase ◽  
Hydrogen Bonds ◽  
Active Center ◽  
Energy Contribution ◽  
Active Centers ◽  
Lower Range ◽  
Data Set ◽  
Evolutionarily Conserved ◽  
Conservation Patterns ◽  
The Stability

In this work, we have analyzed the influence of amide-? interactions on stability and properties of superoxide dismutase (SOD) active centers. In the data set of 43 proteins, 5017 amide-? interactions were observed, and every active center forms 117 interactions, on the average. Most of the interactions belong to the backbone of proteins. The analysis of the geometry of the amide-? interactions revealed two preferred structures, parallel-displaced and T-shaped structure. The aim of this study was to investigate the energy contribution resulting from amide-? interactions, which were in the lower range of strong hydrogen bonds. The conservation patterns in the present study indicate that more than half of the residues involved in these interactions are evolutionarily conserved. Stabilization centers for these proteins showed that all residues involved in amide-? interactions were important in locating one or more of such centers. The results presented in this work can be very useful for understanding the contribution of amide-? interaction to the stability of SOD active centers.

Fusion based learning approach for predicting concrete pouring productivity based on construction and supply parameters

2016 ◽  
Vol 16 (2) ◽  
pp. 185-202 ◽  
Author(s):  
Mojtaba Maghrebi ◽  
Ali Shamsoddini ◽  
S. Travis Waller
Keyword(s):  
Supply Chain ◽  
Production Rate ◽  
Learning Method ◽  
Data Set ◽  
Content Type ◽  
Field Database ◽  
The Stability ◽  
Stable Learning ◽  
Ready Mixed Concrete ◽  
Practical Implications

Purpose The purpose of this paper is to predict the concrete pouring production rate by considering both construction and supply parameters, and by using a more stable learning method. Design/methodology/approach Unlike similar approaches, this paper considers not only construction site parameters, but also supply chain parameters. Machine learner fusion-regression (MLF-R) is used to predict the production rate of concrete pouring tasks. Findings MLF-R is used on a field database including 2,600 deliveries to 507 different locations. The proposed data set and the results are compared with ANN-Gaussian, ANN-Sigmoid and Adaboost.R2 (ANN-Gaussian). The results show better performance of MLF-R obtaining the least root mean square error (RMSE) compared with other methods. Moreover, the RMSEs derived from the predictions by MLF-R in some trials had the least standard deviation, indicating the stability of this approach among similar used approaches. Practical implications The size of the database used in this study is much larger than the size of databases used in previous studies. It helps authors draw their conclusions more confidently and introduce more generalised models that can be used in the ready-mixed concrete industry. Originality/value Introducing a more stable learning method for predicting the concrete pouring production rate helps not only construction parameters, but also traffic and supply chain parameters.

scholarly journals Effects of electron transfer on the stability of hydrogen bonds

2017 ◽  
Vol 8 (11) ◽  
pp. 7324-7329 ◽  
Author(s):  
Tyler M. Porter ◽  
Gavin P. Heim ◽  
Clifford P. Kubiak
Keyword(s):  
Electron Transfer ◽  
Hydrogen Bonds ◽  
Ruthenium Complexes ◽  
Complementary Pair ◽  
Redox States ◽  
The Stability ◽  
Hydrogen Bonded

The measurement of the dimerization constants of hydrogen-bonded ruthenium complexes (12, 22, 32) linked by a self-complementary pair of 4-pyridylcarboxylic acid ligands in different redox states is reported.

Sparse reflectivity inversion for nonstationary seismic data with surface-related multiples: Numerical and field-data experiments

Geophysics ◽  
2017 ◽  
Vol 82 (3) ◽  
pp. R199-R217 ◽  
Author(s):  
Xintao Chai ◽  
Shangxu Wang ◽  
Genyang Tang
Keyword(s):  
Seismic Data ◽  
Resolution Enhancement ◽  
Synthetic Data ◽  
Data Sets ◽  
Data Set ◽  
Anelastic Attenuation ◽  
Seismic Resolution ◽  
Text Filtering ◽  
The Stability ◽  
Reflectivity Inversion

Seismic data are nonstationary due to subsurface anelastic attenuation and dispersion effects. These effects, also referred to as the earth’s [Formula: see text]-filtering effects, can diminish seismic resolution. We previously developed a method of nonstationary sparse reflectivity inversion (NSRI) for resolution enhancement, which avoids the intrinsic instability associated with inverse [Formula: see text] filtering and generates superior [Formula: see text] compensation results. Applying NSRI to data sets that contain multiples (addressing surface-related multiples only) requires a demultiple preprocessing step because NSRI cannot distinguish primaries from multiples and will treat them as interference convolved with incorrect [Formula: see text] values. However, multiples contain information about subsurface properties. To use information carried by multiples, with the feedback model and NSRI theory, we adapt NSRI to the context of nonstationary seismic data with surface-related multiples. Consequently, not only are the benefits of NSRI (e.g., circumventing the intrinsic instability associated with inverse [Formula: see text] filtering) extended, but also multiples are considered. Our method is limited to be a 1D implementation. Theoretical and numerical analyses verify that given a wavelet, the input [Formula: see text] values primarily affect the inverted reflectivities and exert little effect on the estimated multiples; i.e., multiple estimation need not consider [Formula: see text] filtering effects explicitly. However, there are benefits for NSRI considering multiples. The periodicity and amplitude of the multiples imply the position of the reflectivities and amplitude of the wavelet. Multiples assist in overcoming scaling and shifting ambiguities of conventional problems in which multiples are not considered. Experiments using a 1D algorithm on a synthetic data set, the publicly available Pluto 1.5 data set, and a marine data set support the aforementioned findings and reveal the stability, capabilities, and limitations of the proposed method.

scholarly journals UV Sensitivity of Free and Immobilized on Chitosan Matrix Proteases

2020 ◽  
Vol 2 (1) ◽  
pp. 17
Author(s):  
Svetlana Pankova ◽  
Marina Holyavka ◽  
Valeriy Artyukhov
Keyword(s):  
Uv Irradiation ◽  
Living Systems ◽  
Essential Factor ◽  
Active Centers ◽  
Santa Ana ◽  
Uv Sensitivity ◽  
Chitosan Matrix ◽  
Lowry Method ◽  
The Stability

UV irradiation is an essential factor in natural and artificial climate in modern environmental conditions, which has a constant effect on living systems. Collagenase, bromelain, ficin, papain (Sigma-Aldrich: St. Louis, MO, USA) and trypsin (MP biomedicals: Santa Ana, CA, USA) were the objects of this study. The substrate for hydrolysis was BSA (Sigma-Aldrich: St. Louis, MO, USA), the carriers for immobilization were chitosans (<100, 200 and 350 kDa) and chitosan succinate (Bioprogress: Shchyolkovo, Russia). The protease immobilization was carried out by the adsorption. The determination of the protein amount in samples and their catalytic activity was carried out by the modified Lowry method. UV irradiation of proteases was performed using doses 151–6040 J/m2. By the degree of photosensitivity, hydrolases can be arranged in the next row: collagenase → bromelain → ficin → papain → trypsin. Adsorption on a chitosan and succinate of chitosan leads to an increase in the stability to ultraviolet light of heterogeneous (immobilized) biocatalysts compared to free enzymes. Photoprotective effect of the chitosan may be due to the following reasons: enzyme interact with the chitosan to form photo resistant complexes; сhitosan screens active free-radicals, preventing the photooxidation of a certain number of amino acids, including the active centers of the studied enzymes under the influence of UV irradiation.

scholarly journals Computational Approach to Identify Mutations in Genes of Notch Signaling Pathway and Its Association with OSCC

2020 ◽  
pp. 84-92
Author(s):  
Madhumithaa Sivarajan ◽  
A. S. Smiline Girija ◽  
A. Paramasivam ◽  
J. Vijayashree Priyadharsini
Keyword(s):  
Notch Signaling ◽  
Signaling Pathway ◽  
Tumor Development ◽  
Suppressor Gene ◽  
Notch Signaling Pathway ◽  
Computational Approach ◽  
Notch Signalling ◽  
Cell Renewal ◽  
Data Set ◽  
The Stability

Derailments in signal transduction pathways are associated with the development of tumors. One such vital pathway is the Notch signaling pathway which is associated with various processes of carcinogenesis such as proliferation of cells, cell renewal, angiogenesis and oncogenic microenvironment preservation. Interestingly, Notch also plays a pivotal role in tumor development by acting as an oncogene as well as tumor suppressor gene. In view of this fact, the present study was designed to analyze mutations in Notch signalling pathway which might have a crucial role in the etiology of oral squamous cell carcinoma (OSCC) using computational approach. The Cancer Gene Atlas data set hosted in the cBioportal was used in the present study. These samples were queried for the presence of mutations in Notch signalling genes which included a predefined list of 55 genes. Further, the Oncoprint data obtained was compared to that of gnomAD database which identified novel and reported mutations in the genes analyzed. Additionally, I-Mutant and MutPred analysis was carried out to determine the stability and pathogenicity of the variations recorded. Among 55 genes analysed, SPEN gene was shown to possess the highest frequency of mutation (5%) followed by FBXW7, Notch1, EP300, NUMB, and RBPJL genes. Most of the mutations identified were novel as assessed using the control dataset from the gnomAD database. The stability of the protein was found to decrease upon nucleotide substitution. Finally, the MutPred score revealed that most of the mutant proteins were pathogenic.  Several novel mutations have been identified in the pathway analyzed. Functional analysis of these variants using experimental approaches would aid in dissecting their association with OSCC.

scholarly journals Impact of the volatility of resource revenue on non-resource revenue volatility

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sena Kimm Gnangnon
Keyword(s):  
Empirical Analysis ◽  
Economic Diversification ◽  
Data Set ◽  
Content Type ◽  
Generalized Methods Of Moments ◽  
Public Revenue ◽  
Revenue Volatility ◽  
The Stability ◽  
Methods Of Moments ◽  
The Empirical Analysis

PurposeThis paper investigates the effect of the volatility of resource revenue on the volatility of non-resource revenue.Design/methodology/approachThe empirical analysis has utilized an unbalanced panel data set comprising 54 countries over the period 1980–2015. The two-step system generalized methods of moments (GMM) is the main economic approach used to carry out the empirical analysis.FindingsResults show that resource revenue volatility generates lower non-resource revenue volatility only when the share of resource revenue in total public revenue is lower than 18%. Otherwise, higher resource revenue volatility would result in a rise in non-resource revenue volatility.Research limitations/implicationsIn light of the adverse effect of volatility of non-resource revenue on public spending, and hence on economic growth and development prospects, countries whose total public revenue is highly dependent on resource revenue should adopt appropriate policies to ensure the rise in non-resource revenue, as well as the stability of the latter.Practical implicationsEconomic diversification in resource-rich countries (particularly in developing countries among them) could contribute to reducing the dependence of economies on natural resources, and hence the dependence of public revenue on resource revenue. Therefore, policies in favour of economic diversification would contribute to stabilizing non-resource revenue, which is essential for financing development needs.Originality/valueTo the best of our knowledge, this topic has not been addressed in the literature.

scholarly journals The role of an evolutionarily conserved cis-proline in the thioredoxin-like domain of human class Alpha glutathione transferase A1-1

2003 ◽  
Vol 372 (1) ◽  
pp. 241-246 ◽  
Author(s):  
Chris NATHANIEL ◽  
Louise A. WALLACE ◽  
Jonathan BURKE ◽  
Heini W. DIRR
Keyword(s):  
Glutathione Transferase ◽  
Conformational Stability ◽  
Wild Type ◽  
Catalytic Function ◽  
Evolutionarily Conserved ◽  
Glutathione S Transferases ◽  
Equilibrium Unfolding ◽  
The Stability ◽  
Unfolding Kinetics

The thioredoxin-like fold has a βαβαββα topology, and most proteins/domains with this fold have a topologically conserved cis-proline residue at the N-terminus of β-strand 3. This residue plays an important role in the catalytic function and stability of thioredoxin-like proteins, but is reported not to contribute towards the stability of glutathione S-transferases (GSTs) [Allocati, Casalone, Masulli, Caccarelli, Carletti, Parker and Di Ilio (1999) FEBS Lett. 445, 347–350]. In order to further address the role of the cis-proline in the structure, function and stability of GSTs, cis-Pro-56 in human GST (hGST) A1-1 was replaced with a glycine, and the properties of the P56G mutant were compared with those of the wild-type protein. Not only was the catalytic function of the mutant dramatically reduced, so was its conformational stability, as indicated by equilibrium unfolding and unfolding kinetics experiments with urea as denaturant. These findings are discussed in the context of other thioredoxin-like proteins.

Do C—H...O hydrogen bonds contribute to the stability of nucleic acid base pairs?

1995 ◽  
Vol 51 (2) ◽  
pp. 136-139 ◽  
Author(s):  
G. A. Leonard ◽  
K. McAuley-Hecht ◽  
T. Brown ◽  
W. N. Hunter
Keyword(s):  
Nucleic Acid ◽  
Hydrogen Bonds ◽  
Acid Base ◽  
Base Pairs ◽  
Nucleic Acid Base ◽  
The Stability

Effect of Superoxide Dismutase on the Stability ofS-Nitrosothiols

1999 ◽  
Vol 361 (2) ◽  
pp. 323-330 ◽  
Author(s):  
David Jourd'heuil ◽  
F.Stephen Laroux ◽  
Allen M. Miles ◽  
David A. Wink ◽  
Matthew B. Grisham
Keyword(s):  
Superoxide Dismutase ◽  
The Stability

scholarly journals HSP90 is a chaperone for DLK and is required for axon injury signaling

2018 ◽  
Vol 115 (42) ◽  
pp. E9899-E9908 ◽  
Author(s):  
Scott Karney-Grobe ◽  
Alexandra Russo ◽  
Erin Frey ◽  
Jeffrey Milbrandt ◽  
Aaron DiAntonio
Keyword(s):  
Leucine Zipper ◽  
Axon Regeneration ◽  
Heat Shock Protein 90 ◽  
Hsp90 Inhibitor ◽  
Loss Of Function ◽  
Hsp90 Inhibition ◽  
Axon Injury ◽  
Evolutionarily Conserved ◽  
The Stability

Peripheral nerve injury induces a robust proregenerative program that drives axon regeneration. While many regeneration-associated genes are known, the mechanisms by which injury activates them are less well-understood. To identify such mechanisms, we performed a loss-of-function pharmacological screen in cultured adult mouse sensory neurons for proteins required to activate this program. Well-characterized inhibitors were present as injury signaling was induced but were removed before axon outgrowth to identify molecules that block induction of the program. Of 480 compounds, 35 prevented injury-induced neurite regrowth. The top hits were inhibitors to heat shock protein 90 (HSP90), a chaperone with no known role in axon injury. HSP90 inhibition blocks injury-induced activation of the proregenerative transcription factor cJun and several regeneration-associated genes. These phenotypes mimic loss of the proregenerative kinase, dual leucine zipper kinase (DLK), a critical neuronal stress sensor that drives axon degeneration, axon regeneration, and cell death. HSP90 is an atypical chaperone that promotes the stability of signaling molecules. HSP90 and DLK show two hallmarks of HSP90–client relationships: (i) HSP90 binds DLK, and (ii) HSP90 inhibition leads to rapid degradation of existing DLK protein. Moreover, HSP90 is required for DLK stability in vivo, where HSP90 inhibitor reduces DLK protein in the sciatic nerve. This phenomenon is evolutionarily conserved in Drosophila. Genetic knockdown of Drosophila HSP90, Hsp83, decreases levels of Drosophila DLK, Wallenda, and blocks Wallenda-dependent synaptic terminal overgrowth and injury signaling. Our findings support the hypothesis that HSP90 chaperones DLK and is required for DLK functions, including proregenerative axon injury signaling.

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