Phospholipase A2 (PLA2) Sequences in Rattus norvegicus Genome

Author(s):  
Jyothi Kanagaraj

Phospholipase A2 is enzyme that hydrolyses phospholipids at sn-2 position. This class of enzymes are significant due to their ability to cleave membrane phospholipids and hence causing inflammation. The PLA2 enzymes present in Rattus norvegicus is extensively studied to predict its properties. The Protparam analysis was performed to predict the physical properties like number of amino acids, Theoretical pH, stability index value, aliphatic index value and GRAVY value. The SOPMA analysis predicted its structural properties like the number of alpha-helices and beta-strands. Hence the focus of the present study was to perform a preliminary in silico analysis to identify the PLA2 protein sequences in the genome of Rattus norvegicus.

2021 ◽  
Vol 132 ◽  
pp. S168-S169
Author(s):  
Busra Goksel Tulgar ◽  
Fahrettin Duymus ◽  
Deniz Esin ◽  
Fatma Betul Maden ◽  
Ebru Marzioglu Ozdemir ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Francisco Javier Rodal Canales ◽  
Laura Pérez-Campos Mayoral ◽  
María Teresa Hernández-Huerta ◽  
Luis Manuel Sánchez Navarro ◽  
Carlos Alberto Matias-Cervantes ◽  
...  

AbstractNumerous repositioned drugs have been sought to decrease the severity of SARS-CoV-2 infection. It is known that among its physicochemical properties, Ursodeoxycholic Acid (UDCA) has a reduction in surface tension and cholesterol solubilization, it has also been used to treat cholesterol gallstones and viral hepatitis. In this study, molecular docking was performed with the SARS-CoV-2 Spike protein and UDCA. In order to confirm this interaction, we used Molecular Dynamics (MD) in “SARS-CoV-2 Spike protein-UDCA”. Using another system, we also simulated MD with six UDCA residues around the Spike protein at random, naming this “SARS-CoV-2 Spike protein-6UDCA”. Finally, we evaluated the possible interaction between UDCA and different types of membranes, considering the possible membrane conformation of SARS-CoV-2, this was named “SARS-CoV-2 membrane-UDCA”. In the “SARS-CoV-2 Spike protein-UDCA”, we found that UDCA exhibits affinity towards the central region of the Spike protein structure of − 386.35 kcal/mol, in a region with 3 alpha helices, which comprises residues from K986 to C1032 of each monomer. MD confirmed that UDCA remains attached and occasionally forms hydrogen bonds with residues R995 and T998. In the presence of UDCA, we observed that the distances between residues atoms OG1 and CG2 of T998 in the monomers A, B, and C in the prefusion state do not change and remain at 5.93 ± 0.62 and 7.78 ± 0.51 Å, respectively, compared to the post-fusion state. Next, in “SARS-CoV-2 Spike protein-6UDCA”, the three UDCA showed affinity towards different regions of the Spike protein, but only one of them remained bound to the region between the region's heptad repeat 1 and heptad repeat 2 (HR1 and HR2) for 375 ps of the trajectory. The RMSD of monomer C was the smallest of the three monomers with a value of 2.89 ± 0.32, likewise, the smallest RMSF was also of the monomer C (2.25 ± 056). In addition, in the simulation of “SARS-CoV-2 membrane-UDCA”, UDCA had a higher affinity toward the virion-like membrane; where three of the four residues remained attached once they were close (5 Å, to the centre of mass) to the membrane by 30 ns. However, only one of them remained attached to the plasma-like membrane and this was in a cluster of cholesterol molecules. We have shown that UDCA interacts in two distinct regions of Spike protein sequences. In addition, UDCA tends to stay bound to the membrane, which could potentially reduce the internalization of SARS-CoV-2 in the host cell.


Biologics ◽  
2022 ◽  
Vol 2 (1) ◽  
pp. 45-55
Author(s):  
Muhammad Muzammal ◽  
Muzammil Ahmad Khan ◽  
Mohammed Al Mohaini ◽  
Abdulkhaliq J. Alsalman ◽  
Maitham A. Al Hawaj ◽  
...  

Venom from different organisms was used in ancient times to treat a wide range of diseases, and to combat a variety of enveloped and non-enveloped viruses. The aim of this in silico research was to investigate the impact of honeybee venom proteins and peptides against Ebola virus. In the current in silico study, different online and offline tools were used. RaptorX (protein 3D modeling) and PatchDock (protein–protein docking) were used as online tools, while Chimera and LigPlot + v2.1 were used for visualizing protein–protein interactions. We screened nine venom proteins and peptides against the normal Ebola virus spike protein and found that melittin, MCD and phospholipase A2 showed a strong interaction. We then screened these peptides and proteins against mutated strains of Ebola virus and found that the enzyme phospholipase A2 showed a strong interaction. According to the findings, phospholipase A2 found in honeybee venom may be an effective source of antiviral therapy against the deadly Ebola virus. Although the antiviral potency of phospholipase A2 has been recorded previously, this is the first in silico analysis of honeybee phospholipase A2 against the Ebola viral spike protein and its more lethal mutant strain.


2003 ◽  
Vol 2003 (4) ◽  
pp. 231-236 ◽  
Author(s):  
Manuela Pruess ◽  
Rolf Apweiler

In the growing field of proteomics, tools for the in silico analysis of proteins and even of whole proteomes are of crucial importance to make best use of the accumulating amount of data. To utilise this data for healthcare and drug development, first the characteristics of proteomes of entire species—mainly the human—have to be understood, before secondly differentiation between individuals can be surveyed. Specialised databases about nucleic acid sequences, protein sequences, protein tertiary structure, genome analysis, and proteome analysis represent useful resources for analysis, characterisation, and classification of protein sequences. Different from most proteomics tools focusing on similarity searches, structure analysis and prediction, detection of specific regions, alignments, data mining, 2D PAGE analysis, or protein modelling, respectively, comprehensive databases like the proteome analysis database benefit from the information stored in different databases and make use of different protein analysis tools to provide computational analysis of whole proteomes.


2017 ◽  
Vol 3 (2) ◽  
pp. 26
Author(s):  
Ramchander Merugu ◽  
Sireesha Radarapu ◽  
Sandhya Rani Dasari ◽  
Jyothi Mandala

In silico analysis of Fluoride transporter proteins obtained from database are presented in this study. The composition of alanine and glycine was high while low concentrations of aspartic acid, cysteine and glutamine were seen when compared to other aminoacids. Molecular weight of fungal transporters was the highest while the bacterial showed relatively less molecular weights. The instability index of all the proteins was less than 40 showing that all of them are stable except that of Neurospora and Bifidobacterium. Aliphatic index was found to be within a range of 65 to 100.


2020 ◽  
Vol 47 (6) ◽  
pp. 398-408
Author(s):  
Sonam Tulsyan ◽  
Showket Hussain ◽  
Balraj Mittal ◽  
Sundeep Singh Saluja ◽  
Pranay Tanwar ◽  
...  

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.


2013 ◽  
Vol 9 (4) ◽  
pp. 608-616 ◽  
Author(s):  
Zaheer Ul-Haq ◽  
Saman Usmani ◽  
Uzma Mahmood ◽  
Mariya al-Rashida ◽  
Ghulam Abbas

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