scholarly journals Predicted transmembrane proteins with homology to Mef(A) are not responsible for complementing mef(A) deletion in the mef(A)–msr(D) macrolide efflux system in Streptococcus pneumoniae

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Valeria Fox ◽  
Francesco Santoro ◽  
Gianni Pozzi ◽  
Francesco Iannelli
Keyword(s):  
Streptococcus Pneumoniae ◽  
Transmembrane Proteins ◽  
In Silico Analysis ◽  
Deletion Mutants ◽  
Atp Binding ◽  
Efflux System ◽  
Efflux Transport ◽  
Transmembrane Channel ◽  
Binding Domains ◽  
Silico Analysis

Abstract Objectives In streptococci, the type M resistance to macrolides is due to the mef(A)–msr(D) efflux transport system of the ATP-Binding cassette (ABC) superfamily, where it is proposed that mef(A) codes for the transmembrane channel and msr(D) for the two ATP-binding domains. Phage ϕ1207.3 of Streptococcus pyogenes, carrying the mef(A)–msr(D) gene pair, is able to transfer the macrolide efflux phenotype to Streptococcus pneumoniae. Deletion of mef(A) in pneumococcal ϕ1207.3-carrying strains did not affect erythromycin efflux. In order to identify candidate genes likely involved in complementation of mef(A) deletion, the Mef(A) amino acid sequence was used as probe for database searching. Results In silico analysis identified 3 putative candidates in the S. pneumoniae R6 genome, namely spr0971, spr1023 and spr1932. Isogenic deletion mutants of each candidate gene were constructed and used in erythromycin sensitivity assays to investigate their contribution to mef(A) complementation. Since no change in erythromycin sensitivity was observed compared to the parental strain, we produced double and triple mutants to assess the potential synergic activity of the selected genes. Also these mutants did not complement the mef(A) function.

scholarly journals In silico Analysis of Phytochemicals from Cocoa against Ribitol-5-Phosphate 2-Dehydrogenase of Streptococcus pneumoniae Causing Pneumonia

2020 ◽  
pp. 1-5
Author(s):  
Sunanya Das ◽  
Suchismita Khatei ◽  
Saismita Sahoo ◽  
Sitaram Swain ◽  
Dipankar Bhattacharyay
Keyword(s):  
Molecular Docking ◽  
Streptococcus Pneumoniae ◽  
Vanillic Acid ◽  
In Silico ◽  
Metabolic Pathways ◽  
In Silico Analysis ◽  
Discovery Studio ◽  
Dehydrogenase Enzyme ◽  
High Possibility ◽  
Silico Analysis

This analysis aims at evaluating the effects of Cocoa extract on Pneumonia. Pneumonia is caused by Streptococcus pneumoniae. Caffeine, Chorogenic acid, Ferulic acid, Iso- Orientin, luteolin, Naringenin and Vanillic acid of Cocoa were interacted with ribitol-5-phosphate 2-dehydrogenase which is involved in pentose and glucorunate interconversion pathways of Streptococcus pneumoniae. The enzyme was taken as receptor and phytochemicals were considered as ligands. All the interactions were done in Biovia discovery Studio 2020 and the process is known as molecular Docking. Molecular Docking provides us an opportunity to identify the potential phytochemical or component which can act as powerful tool against the pathogen. Out of all the phytochemicals, Luteolin of Cocoa inhibits or blocks the mechanism or action of ribitol-5-phosphate 2-dehydrogenase enzyme of Streptococcus pneumoniae. There is high possibility that these phytochemicals can potentially inhibit others enzymes involved in various metabolic pathways of Streptococcus pneumoniae.

scholarly journals IN SILICO ANALYSIS RELATED TO TIGR4 STRAIN IN STREPTOCOCCUS PNEUMONIAE

2018 ◽  
Vol 11 (4) ◽  
pp. 96
Author(s):  
Balasankar Karavadi ◽  
Pooja Suresh
Keyword(s):  
Streptococcus Pneumoniae ◽  
Binding Energy ◽  
In Silico Analysis ◽  
Melissa Officinalis ◽  
Docking Analysis ◽  
Pubchem Compound ◽  
Drug Score ◽  
Compound Database ◽  
Natural Components ◽  
Silico Analysis

 Objective: Numerous current investigations are done on the efficiency of natural components to combat the invasion by Streptococcus pneumoniae – strain TIGR4; the main objective is to propose the most favorable ligand compound that could be effective to target the protein.Methods: The normal segments from the Melissa officinalis are docked against serine/threonine protein kinase (STPK) receptor. The tools and programming utilized are modeler v 9.10 for displaying the protein structure, PubChem compound database to recover the synthetic structure of the ligands. ADMET was used to know the toxicity of the ligands and data warrior and the docking analysis was done by PyRx.Result: The results show that 5-cedranone compounds satisfy the ADMET properties and are more favorable to bind with STPK receptor. The drug score of 5-cedranone is 0.4572 and the m binding energy is −7.9.Conclusions: The amino acid residue for the least binding energy for STPK is Ser 175 and Thr 167. Based on the ADMET analysis, 5-cedranone shows moderate cLogP and cLogS values and we predict 5-cedranone may not produce any side effects.

A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

2020 ◽  
Vol 47 (6) ◽  
pp. 398-408
Author(s):  
Sonam Tulsyan ◽  
Showket Hussain ◽  
Balraj Mittal ◽  
Sundeep Singh Saluja ◽  
Pranay Tanwar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Gallbladder Carcinoma ◽  
In Silico ◽  
In Silico Analysis ◽  
Transcriptomic Profile ◽  
Silico Analysis

Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki
Keyword(s):  
Data Analysis ◽  
Virtual Screening ◽  
In Silico ◽  
Model Development ◽  
In Silico Analysis ◽  
Material Design ◽  
Efficient Solutions ◽  
Biological Data ◽  
Cost Efficient ◽  
Silico Analysis

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.

In-Silico Analysis of Chromone Containing Sulfonamide Derivatives as Human Carbonic Anhydrase Inhibitors

2013 ◽  
Vol 9 (4) ◽  
pp. 608-616 ◽  
Author(s):  
Zaheer Ul-Haq ◽  
Saman Usmani ◽  
Uzma Mahmood ◽  
Mariya al-Rashida ◽  
Ghulam Abbas
Keyword(s):  
Carbonic Anhydrase ◽  
In Silico ◽  
In Silico Analysis ◽  
Carbonic Anhydrase Inhibitors ◽  
Human Carbonic Anhydrase ◽  
Silico Analysis

In-Vitro and In-Silico Characterization of Xylose Reductase from Emericella nidulans

2019 ◽  
Vol 13 (2) ◽  
pp. 159-170 ◽  
Author(s):  
Vishal Ahuja ◽  
Aashima Sharma ◽  
Ranju Kumari Rathour ◽  
Vaishali Sharma ◽  
Nidhi Rana ◽  
...  
Keyword(s):  
Production Process ◽  
In Silico ◽  
Xylose Reductase ◽  
In Silico Analysis ◽  
Emericella Nidulans ◽  
Higher Temperature ◽  
In Silico Characterization ◽  
Silico Analysis

Background: Lignocellulosic residues generated by various anthropogenic activities can be a potential raw material for many commercial products such as biofuels, organic acids and nutraceuticals including xylitol. Xylitol is a low-calorie nutritive sweetener for diabetic patients. Microbial production of xylitol can be helpful in overcoming the drawbacks of traditional chemical production process and lowring cost of production. Objective: Designing efficient production process needs the characterization of required enzyme/s. Hence current work was focused on in-vitro and in-silico characterization of xylose reductase from Emericella nidulans. Methods: Xylose reductase from one of the hyper-producer isolates, Emericella nidulans Xlt-11 was used for in-vitro characterization. For in-silico characterization, XR sequence (Accession No: Q5BGA7) was used. Results: Xylose reductase from various microorganisms has been studied but the quest for better enzymes, their stability at higher temperature and pH still continues. Xylose reductase from Emericella nidulans Xlt-11 was found NADH dependent and utilizes xylose as its sole substrate for xylitol production. In comparison to whole cells, enzyme exhibited higher enzyme activity at lower cofactor concentration and could tolerate higher substrate concentration. Thermal deactivation profile showed that whole cell catalysts were more stable than enzyme at higher temperature. In-silico analysis of XR sequence from Emericella nidulans (Accession No: Q5BGA7) suggested that the structure was dominated by random coiling. Enzyme sequences have conserved active site with net negative charge and PI value in acidic pH range. Conclusion: Current investigation supported the enzyme’s specific application i.e. bioconversion of xylose to xylitol due to its higher selectivity. In-silico analysis may provide significant structural and physiological information for modifications and improved stability.

Sign in / Sign up

Export Citation Format

Share Document