Modelling profile of onchocerca volvulus glutamatecysteine ligase (ONCVO-GCL)

2021 ◽  
Vol 10 (3) ◽  
pp. 118-122
Author(s):  
Akinseye Olanrewaju Roland ◽  
Ale E Morayo ◽  
Ojomo Joan ◽  
Gbadamosi Folawiyo I ◽  
Ebenezer Kayode ◽  
...  
Keyword(s):  
Active Sites ◽  
Homology Modelling ◽  
Protein A ◽  
3D Structure ◽  
Chemotherapeutic Agents ◽  
Onchocerca Volvulus ◽  
Glutamate Cysteine Ligase ◽  
3 Dimensional ◽  
High Level ◽  
Favoured Region

Onchocerca volvulus Glutamate cysteine ligase (ONCVO-GCL) catalyzes the first step in the production of the cellular antioxidant glutathione (GSH), which involve the condensation of cysteine and glutamate to form the dipeptide gamma-glutamylcysteine (γ-GC). ONCVO-GCL is critical to cell survival. Its dysregulation could lead to decreased GSH biosynthesis, reduced cellular antioxidant capacity, and the induction of oxidative stress. ONCVO-GCL expression support the high level of cell proliferation and confer resistance to many chemotherapeutic agents, hence could serve as a molecular target for inhibitors. This study aims to model the 3-dimensional (3D) structure of ONCVO-GCL, validate and predict the active sites of the modelled protein. ONCVO-GCL (Uniprot ID: A0A044QR48) 3D structure was modelled and validated using SWISS-MODEL. The Computed Atlas of Surface Topography of proteins (CASTp) 3.0 was used to predict the active sites of the modelled protein. A percentage identity matrix of 41.81% was obtained, which confirms the similarity identity of 40.86% obtained from the homology modelling. Model with 88% in the most favoured region of Ramachandra plot was obtained and the more favourable active sites for docking analyses due to the similarities observed from the alignment of the modelled structure to the template structure were: GLY 2A, LEU3A, LEU 4A, ARG 40A, TRP 47A, GLY 48A, ASP 49A, GLU 50A, GLU 52A, and PRO 109A.

In Silico Prediction and Validation of Oxygen-Regulated Protein N-myc Downstream Regulated Gene 3 and Virtual Screening of Competitive Inhibitors of L-Lactate as Therapeutics

2019 ◽  
Vol 16 (6) ◽  
pp. 637-644
Author(s):  
Hongyu Cao ◽  
Yanhua Wu ◽  
Xingzhi Zhou ◽  
Xuefang Zheng ◽  
Ge Jiang
Keyword(s):  
Active Sites ◽  
Competitive Inhibition ◽  
Hydrophobic Effect ◽  
3D Structure ◽  
Amino Acid Residues ◽  
In Silico Prediction ◽  
Hypoxic Response ◽  
Drug Candidates ◽  
Competitive Inhibitors ◽  
Extracellular Regulated Protein Kinases

Background: N-myc downstream regulated gene 3 (NDRG3) is a newly discovered oxygen-regulated protein which will bind with L-Lactate in hypoxia and further activate Raf (rapidly accelerated fibrosarcoma)-ERK (extracellular regulated protein kinases) pathway, promoting cell growth and angiogenesis. Methods: Competitive inhibition on the binding of NDRG3 and L-Lactate may be potentially a useful strategy for the repression of hypoxic response mediated by NDRG3. The threedimensional (3D) structure of NDRG3 was built by using homology modeling for its crystal structure was not available. Then, L-Lactate was docked into NDRG3, from which we knew it bound with amino acid residues Gln69, His183, Asn189, Ala72 and Pro66 of NDRG3 in the most possible active sites. Approximately 3000 compounds have been virtually screened and the 6 topranked compounds were selected as reference molecules to analyze their interaction relationships, which illustrated that some of them might form electrostatic interaction with Glu70 and Asp187, π-&π stack with Phe75 and Tyr180, hydrogen bonds with Gly71 and Asn189, hydrophobic effect with Ala72 and Ile184. Results: Novel molecules were designed through structural optimization of the 6 top-ranked compounds and subsequently their ADMET properties were predicted. Conclusion: These molecules may be potential drug candidates for the suppression of hypoxic response mediated by NDRG3 and targeted therapy for hypoxia-induced diseases.

scholarly journals Malonyl-proteome profiles of Staphylococcus aureus reveal lysine malonylation modification in enzymes involved in energy metabolism

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yanan Shi ◽  
Jingjing Zhu ◽  
Yan Xu ◽  
Xiaozhao Tang ◽  
Zushun Yang ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Energy Metabolism ◽  
Active Sites ◽  
Current Knowledge ◽  
Tricarboxylic Acid Cycle ◽  
Protein A ◽  
Pentose Phosphate ◽  
Post Translational Modification ◽  
Bacterial Physiology ◽  
Dihydrolipoyl Dehydrogenase

Abstract Background Protein lysine malonylation, a novel post-translational modification (PTM), has been recently linked with energy metabolism in bacteria. Staphylococcus aureus is the third most important foodborne pathogen worldwide. Nonetheless, substrates and biological roles of malonylation are still poorly understood in this pathogen. Results Using anti-malonyl-lysine antibody enrichment and high-resolution LC-MS/MS analysis, 440 lysine-malonylated sites were identified in 281 proteins of S. aureus strain. The frequency of valine in position − 1 and alanine at + 2 and + 4 positions was high. KEGG pathway analysis showed that six categories were highly enriched, including ribosome, glycolysis/gluconeogenesis, pentose phosphate pathway (PPP), tricarboxylic acid cycle (TCA), valine, leucine, isoleucine degradation, and aminoacyl-tRNA biosynthesis. In total, 31 malonylated sites in S. aureus shared homology with lysine-malonylated sites previously identified in E. coli, indicating malonylated proteins are highly conserved among bacteria. Key rate-limiting enzymes in central carbon metabolic pathways were also found to be malonylated in S. aureus, namely pyruvate kinase (PYK), 6-phosphofructokinase, phosphoglycerate kinase, dihydrolipoyl dehydrogenase, and F1F0-ATP synthase. Notably, malonylation sites were found at or near protein active sites, including KH domain protein, thioredoxin, alanine dehydrogenase (ALD), dihydrolipoyl dehydrogenase (LpdA), pyruvate oxidase CidC, and catabolite control protein A (CcpA), thus suggesting that lysine malonylation may affect the activity of such enzymes. Conclusions Data presented herein expand the current knowledge on lysine malonylation in prokaryotes and indicate the potential roles of protein malonylation in bacterial physiology and metabolism.

scholarly journals 3-Dimensional Structure-Imitation Model of Evolution of Microstructure of Powder Body During Sintering

1999 ◽  
Vol 32 (1-4) ◽  
pp. 221-233
Author(s):  
I. G. Kamenin ◽  
R. M. Kadushnikov ◽  
V. M. Alievsky ◽  
D. M. Alievsky ◽  
S. V. Somina
Keyword(s):  
Powder Compact ◽  
3D Structure ◽  
Particle Interaction ◽  
Spherical Particles ◽  
Dimensional Structure ◽  
3 Dimensional ◽  
Powder Body ◽  
Time Dependencies ◽  
Growth Laws ◽  
Evolution Of Microstructure

This paper describes a 3D structure-imitation computer model of evolution of the powder compact during sinteringand recrystallization without nucleation. At the initial stages of the evolution processes (sintering until a mosaic structure of boundaries is formed) the model particles are spheres, and two-particle interaction laws control their evolution. During sintering the degree of mutual penetration of the particles increases, regions where spherical particles are wholly facetted by contacts with neighboring particles are formed and grow. These particles are described using the formalism of Voronoi radical polyhedra, and grain growth laws govern their evolution. The model predicts the time dependencies of the following structure parameters of the polyhedra: average polyhedron size and dispersion, total surface of the facets of the polyhedra and total lenght of the edges of the polyhedra.

scholarly journals Structure of SPH (self-incompatibility protein homologue) proteins: a widespread family of small, highly stable, secreted proteins

2019 ◽  
Vol 476 (5) ◽  
pp. 809-826
Author(s):  
Karthik V. Rajasekar ◽  
Shuangxi Ji ◽  
Rachel J. Coulthard ◽  
Jon P. Ride ◽  
Gillian L. Reynolds ◽  
...  
Keyword(s):  
Fusion Protein ◽  
Analytical Ultracentrifugation ◽  
De Novo ◽  
Learning Algorithm ◽  
Sequence Similarity ◽  
Homology Modelling ◽  
3D Structure ◽  
Large Family ◽  
Secreted Proteins ◽  
Self Incompatibility

Abstract SPH (self-incompatibility protein homologue) proteins are a large family of small, disulfide-bonded, secreted proteins, initially found in the self-incompatibility response in the field poppy (Papaver rhoeas), but now known to be widely distributed in plants, many containing multiple members of this protein family. Using the Origami strain of Escherichia coli, we expressed one member of this family, SPH15 from Arabidopsis thaliana, as a folded thioredoxin fusion protein and purified it from the cytosol. The fusion protein was cleaved and characterised by analytical ultracentrifugation, circular dichroism and nuclear magnetic resonance (NMR) spectroscopy. This showed that SPH15 is monomeric and temperature stable, with a β-sandwich structure. The four strands in each sheet have the same topology as the unrelated proteins: human transthyretin, bacterial TssJ and pneumolysin, with no discernible sequence similarity. The NMR-derived structure was compared with a de novo model, made using a new deep learning algorithm based on co-evolution/correlated mutations, DeepCDPred, validating the method. The DeepCDPred de novo method and homology modelling to SPH15 were then both used to derive models of the 3D structure of the three known PrsS proteins from P. rhoeas, which have only 15–18% sequence homology to SPH15. The DeepCDPred method gave models with lower discreet optimised protein energy scores than the homology models. Three loops at one end of the poppy structures are postulated to interact with their respective pollen receptors to instigate programmed cell death in pollen tubes.

scholarly journals On cross-correlations, averages and noise in electron microscopy

2019 ◽  
Vol 75 (1) ◽  
pp. 12-18 ◽  
Author(s):  
Michael Radermacher ◽  
Teresa Ruiz
Keyword(s):  
High Resolution ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
3D Structure ◽  
Signal To Noise ◽  
High Resolution Structure ◽  
Multiple Copies ◽  
High Level ◽  
2D Images ◽  
Resolution Structure

Biological samples are radiation-sensitive and require imaging under low-dose conditions to minimize damage. As a result, images contain a high level of noise and exhibit signal-to-noise ratios that are typically significantly smaller than 1. Averaging techniques, either implicit or explicit, are used to overcome the limitations imposed by the high level of noise. Averaging of 2D images showing the same molecule in the same orientation results in highly significant projections. A high-resolution structure can be obtained by combining the information from many single-particle images to determine a 3D structure. Similarly, averaging of multiple copies of macromolecular assembly subvolumes extracted from tomographic reconstructions can lead to a virtually noise-free high-resolution structure. Cross-correlation methods are often used in the alignment and classification steps of averaging processes for both 2D images and 3D volumes. However, the high noise level can bias alignment and certain classification results. While other approaches may be implicitly affected, sensitivity to noise is most apparent in multireference alignments, 3D reference-based projection alignments and projection-based volume alignments. Here, the influence of the image signal-to-noise ratio on the value of the cross-correlation coefficient is analyzed and a method for compensating for this effect is provided.

scholarly journals An Assessment of the Reliability of the NIGNET Data

2019 ◽  
Vol 3 (1) ◽  
pp. 18-29
Author(s):  
E. G. Ayodele ◽  
C. J. Okolie ◽  
O. A. Mayaki
Keyword(s):  
National Development ◽  
Accurate Information ◽  
Positional Accuracy ◽  
Data Archiving ◽  
Practical Applications ◽  
3 Dimensional ◽  
Gnss Network ◽  
High Level ◽  
Gnss Data ◽  
Geodetic Reference Frame

The Nigerian Geodetic Reference Frame is defined by a number of Continuously Operating Reference Stations (CORS) that constitute the Nigerian GNSS Network (NIGNET). NIGNET is essential for planning and national development with the main goal of ensuring consistency in the geodetic framework both nationally and internationally. Currently, the strength of the network in terms of data reliability has not been adequately studied due to the fact that research into CORS in Nigeria is just evolving, which constitutes a limitation in its applications. Therefore, the aim of this research is to explore the reliability of the 3-dimensional coordinates of NIGNET to inform usability and adequacy for both scientific and practical applications. In particular, this study examines if the 3-dimensional coordinates of NIGNET are equally reliable in terms of positional accuracy. Accordingly, this study utilised GNSS data collected over a period of six years (2011 – 2016) from the network to compute the daily geocentric coordinates of the stations. Exploratory and statistical data analysis techniques were used to understand the magnitude of the errors and the accuracy level in the 3-dimensional coordinates. For this purpose, accuracy metrics such as standard deviation (𝜎), standard error (𝑆𝐸) and root mean square error (RMSE) were computed. While One-way ANOVA was conducted to explore the coordinate differences. The results obtained showed that SE and RMSE ranged from 13.00 − 56.50𝑚𝑚 and 14.38 − 73.16𝑚𝑚 respectively, which signifies high accuracy. Overall, while 88% of the network showed a high level of positional accuracy, the reliability has been compromised due to excessive gaps in the data archiving. Therefore, due attention must be given to NIGNET to achieve its purpose in the provision of accurate information for various geospatial applications. Also, any efforts directed at understanding the practical implications of NIGNET must be well-embraced for the realization of its set objectives.

scholarly journals High Level 3D Structure Extraction from a Single Image Using a CNN-Based Approach

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 563 ◽  
Author(s):  
J. Osuna-Coutiño ◽  
Jose Martinez-Carranza
Keyword(s):  
Level Structure ◽  
3D Structure ◽  
Depth Estimation ◽  
Point Clouds ◽  
Graph Analysis ◽  
Single Image ◽  
3D Data ◽  
3D Elements ◽  
High Level ◽  
Structure Extraction

High-Level Structure (HLS) extraction in a set of images consists of recognizing 3D elements with useful information to the user or application. There are several approaches to HLS extraction. However, most of these approaches are based on processing two or more images captured from different camera views or on processing 3D data in the form of point clouds extracted from the camera images. In contrast and motivated by the extensive work developed for the problem of depth estimation in a single image, where parallax constraints are not required, in this work, we propose a novel methodology towards HLS extraction from a single image with promising results. For that, our method has four steps. First, we use a CNN to predict the depth for a single image. Second, we propose a region-wise analysis to refine depth estimates. Third, we introduce a graph analysis to segment the depth in semantic orientations aiming at identifying potential HLS. Finally, the depth sections are provided to a new CNN architecture that predicts HLS in the shape of cubes and rectangular parallelepipeds.

Selecting DFT methods for use in optimizations of enzyme active sites: applications to ONIOM treatments of DNA glycosylases

2013 ◽  
Vol 91 (7) ◽  
pp. 559-572 ◽  
Author(s):  
Jennifer L. Kellie ◽  
Stacey D. Wetmore
Keyword(s):  
Active Sites ◽  
Noncovalent Interactions ◽  
Single Point ◽  
Enzymatic Reaction ◽  
Basis Set ◽  
Basis Sets ◽  
Dna Glycosylases ◽  
Dft Methods ◽  
Primary Focus ◽  
High Level

When using a hybrid methodology to treat an enzymatic reaction, many factors contribute to selecting the method for the high-level region, which can be complicated by the presence of dispersion-driven interactions such as π–π stacking. In addition, the proper treatment of the reaction center often requires a large number of heavy atoms to be included in the high-level region, precluding the use of ab initio methods such as MP2 as well as large basis sets, in the optimization step. In the present work, popular DFT methods were tested to identify an appropriate functional for treating the high-level region in ONIOM optimizations of reactions catalyzed by nonmetalloenzymes. Eight different DFT methods (B3LYP, B97-2, MPW1K, MPWB1K, BB1K, B1B95, M06-2X, and ωB97X-D) in combination with four double-ζ quality Pople basis sets were tested for their ability to optimize noncovalent interactions (hydrogen bonding and π–π) and characterize reactions (proton transfer, SN2 hydrolysis, and unimolecular cleavage). Although the primary focus of this study is accurate structure determination, energetics were also examined at both the optimization level of theory, and with triple-ζ quality basis set and select (M06-2X or ωB97X-D) methods. If dispersion-driven interactions exist within the active site, then MPWB1K/6-31G(d,p) or M06-2X/6-31+G(d,p) are recommended for the optimization step with subsequent triple-ζ quality single-point energies. However, since dispersion-corrected functionals (M06-2X and ωB97X-D) generally require diffuse functions to yield appropriate geometries, the possible size of the high-level region is greatly limited with these methods. In contrast, if the model is large enough to recover steric constraints on π–π interactions, then B3LYP with a small basis set performs comparatively well for the optimization step and is significantly less computationally expensive. Interestingly, the functionals that afford the best geometries often do not yield the best energetics, which emphasizes the importance of structural benchmark studies.

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