scholarly journals In silico analysis to elect superior bacterial alkaline protease for detergent and leather industries

2015 ◽  
Vol 5 (3) ◽  
pp. 685-698 ◽  
Author(s):  
Kamonashis Das ◽  
Sourav Chakraborty ◽  
Mahmudul Hasan ◽  
Abdullah Maruf Rahman Shovo
Keyword(s):  
High Temperature ◽  
Bacillus Megaterium ◽  
In Silico ◽  
Alkaline Protease ◽  
Protein Sequences ◽  
In Silico Analysis ◽  
Alkaline Proteases ◽  
Leather Industry ◽  
Catalytic Function ◽  
Common Motif

Alkaline protease contributes 40% of the total worldwide enzyme sales. Alkaline protease that is stable at very high temperature and pH is massively desirable for detergent industry and leather industry specially in tanning process. So the present study aims to elect superior bacterial alkaline protease (high temperature and pH stable) as compared to the alkaline proteases of currently industrially used bacteria (Bacillus subtilis and Bacillus cereus). A total of 50 protein sequences of alkaline proteases of different bacteria were analyzed through in silico characterization. ProtParam result revealed that isoelectric point and aliphatic index of alkaline protease of Bacillus megaterium were 8.83 and 93.35 respectively. In case of alkaline protease of B. megaterium, these two properties were significant in comparison to alkaline proteases of industrially used bacteria and other considered bacteria. A common motif of 28 amino acid residues i.e., IQSTYPGEDYEYMSGTSMATPHVAGVAA was found using MEME software in 46 protein sequences. It can be concluded that alkaline protease of Bacillus megaterium may be superior to alkaline proteases of industrially used bacteria and other considered bacteria. In addition, obtained common motif indicates its probable role in catalytic function and structure of alkaline proteases. 

scholarly journals In silico analysis of similar protein sequences between Sars-Cov-2 and BCG vaccine

2021 ◽  
Vol 132 ◽  
pp. S168-S169
Author(s):  
Busra Goksel Tulgar ◽  
Fahrettin Duymus ◽  
Deniz Esin ◽  
Fatma Betul Maden ◽  
Ebru Marzioglu Ozdemir ◽  
...  
Keyword(s):  
In Silico ◽  
Protein Sequences ◽  
In Silico Analysis ◽  
Bcg Vaccine ◽  
Similar Protein ◽  
Silico Analysis

Cloning and In Silico Analysis of a High-Temperature Inducible Lipase from Brevibacillus

2015 ◽  
Vol 41 (6) ◽  
pp. 2159-2170 ◽  
Author(s):  
A. K. Panda ◽  
S. P. S. Bisht ◽  
A. K. Panigrahi ◽  
S. De Mandal ◽  
N. Senthil Kumar
Keyword(s):  
High Temperature ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis

scholarly journals In silico screening and experimental analysis of family GH11 xylanases for applications under conditions of alkaline pH and high temperature

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
David Talens-Perales ◽  
Paloma Sánchez-Torres ◽  
Julia Marín-Navarro ◽  
Julio Polaina
Keyword(s):  
High Temperature ◽  
Experimental Analysis ◽  
In Silico ◽  
High Efficiency ◽  
In Silico Analysis ◽  
Poor Performance ◽  
Carbohydrate Binding ◽  
Alkaline Ph ◽  
Xylanolytic Activity ◽  
Cazy Database

Abstract Background Xylanases are one of the most extensively used enzymes for biomass digestion. However, in many instances, their use is limited by poor performance under the conditions of pH and temperature required by the industry. Therefore, the search for xylanases able to function efficiently at alkaline pH and high temperature is an important objective for different processes that use lignocellulosic substrates, such as the production of paper pulp and biofuels. Results A comprehensive in silico analysis of family GH11 sequences from the CAZY database allowed their phylogenetic classification in a radial cladogram in which sequences of known or presumptive thermophilic and alkalophilic xylanases appeared in three clusters. Eight sequences from these clusters were selected for experimental analysis. The coding DNA was synthesized, cloned and the enzymes were produced in E. coli. Some of these showed high xylanolytic activity at pH values > 8.0 and temperature > 80 °C. The best enzymes corresponding to sequences from Dictyoglomus thermophilum (Xyn5) and Thermobifida fusca (Xyn8). The addition of a carbohydrate-binding module (CBM9) to Xyn5 increased 4 times its activity at 90 °C and pH > 9.0. The combination of Xyn5 and Xyn8 was proved to be efficient for the saccharification of alkali pretreated rice straw, yielding xylose and xylooligosaccharides. Conclusions This study provides a fruitful approach for the selection of enzymes with suitable properties from the information contained in extensive databases. We have characterized two xylanases able to hydrolyze xylan with high efficiency at pH > 8.0 and temperature > 80 °C.

scholarly journals Bioinformatics Resources for In Silico Proteome Analysis

2003 ◽  
Vol 2003 (4) ◽  
pp. 231-236 ◽  
Author(s):  
Manuela Pruess ◽  
Rolf Apweiler
Keyword(s):  
In Silico ◽  
Computational Analysis ◽  
Tertiary Structure ◽  
Protein Sequences ◽  
In Silico Analysis ◽  
Proteome Analysis ◽  
Protein Modelling ◽  
Similarity Searches ◽  
Silico Analysis

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.

scholarly journals Metabolism of Daidzein and Genistein by Gut Bacteria of the Class Coriobacteriia

Foods ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 2741
Author(s):  
Sebastian Tobias Soukup ◽  
Dominic Alexander Stoll ◽  
Nicolas Danylec ◽  
Alena Schoepf ◽  
Sabine Emma Kulling ◽  
...  
Keyword(s):  
Gene Cluster ◽  
In Silico ◽  
Pcr Amplification ◽  
Protein Sequences ◽  
In Silico Analysis ◽  
Gut Bacteria ◽  
Strictly Anaerobic ◽  
Bacterial Strains ◽  
Related Family ◽  
Pure Bacterial Cultures

The intake of isoflavones is presumed to be associated with health benefits in humans, but also potential adverse effects of isoflavones are controversially discussed. Isoflavones can be metabolized by gut bacteria leading to modulation of the bioactivity, such as estrogenic effects. Especially bacterial strains of the Eggerthellaceae, a well-known bacterial family of the human gut microbiota, are able to convert the isoflavone daidzein into equol. In addition, metabolization of genistein is also described for strains of the Eggerthellaceae. The aim of this study was to identify and investigate gut bacterial strains of the family Eggerthellaceae as well as the narrowly related family Coriobacteriaceae which are able to metabolize daidzein and genistein. This study provides a comprehensive, polyphasic approach comprising in silico analysis of the equol gene cluster, detection of genes associated with the daidzein, and genistein metabolism via PCR and fermentation of these isoflavones. The in silico search for protein sequences that are associated with daidzein metabolism identified sequences with high similarity values in already well-known equol-producing strains. Furthermore, protein sequences that are presumed to be associated with daidzein and genistein metabolism were detected in the two type strains ‘Hugonella massiliensis’ and Senegalimassilia faecalis which were not yet described to metabolize these isoflavones. An alignment of these protein sequences showed that the equol gene cluster is highly conserved. In addition, PCR amplification supported the presence of genes associated with daidzein and genistein metabolism. Furthermore, the metabolism of daidzein and genistein was investigated in fermentations of pure bacterial cultures under strictly anaerobic conditions and proofed the metabolism of daidzein and genistein by the strains ‘Hugonella massiliensis’ DSM 101782T and Senegalimassilia faecalis KGMB04484T.

scholarly journals Production and Preliminary Characterization of Alkaline Protease fromAspergillus flavusandAspergillus terreus

2010 ◽  
Vol 7 (2) ◽  
pp. 479-482 ◽  
Author(s):  
P. Chellapandi
Keyword(s):  
Aspergillus Flavus ◽  
Alkaline Protease ◽  
Aspergillus Terreus ◽  
Detergent Industry ◽  
Alkaline Condition ◽  
Good Activity ◽  
Alkaline Proteases ◽  
Leather Industry ◽  
Significant Application

Proteases are being an industrial candidate, which are widely used in food, bakery, and beverage and detergent industry. In leather industry, alkaline proteases are exhibiting a prominent role in unhairing and bating processes. An extensive use of filamentous fungi, especiallyAspergillus specieshas been studied elaborately. Although, the significant application of alkaline protease produced from these strains in leather industry is being limited.Aspergillus flavusandAspergillus terreusfound as the potential strains for production of tannery protease in submerged fermentation. To improve the productivity of this enzyme in liquid broth, various media ingredients have been optimized. The crude and partially purified proteases preliminarily characterized and used for unhairing processes at lab scale in tannery. The protease obtained from these strains showed the good activity in wide alkaline condition at 50 °C suggesting the possibility of using in leather and detergent industry.

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 Study of 1, 4 Alpha Glucan Branching Enzyme and Substrate Docking Studies

2020 ◽  
Vol 17 (1) ◽  
pp. 40-50
Author(s):  
Farzane Kargar ◽  
Amir Savardashtaki ◽  
Mojtaba Mortazavi ◽  
Masoud Torkzadeh Mahani ◽  
Ali Mohammad Amani ◽  
...  
Keyword(s):  
Phylogenetic Tree ◽  
In Silico ◽  
Alpha Helix ◽  
In Silico Analysis ◽  
Glycogen Storage ◽  
Docking Studies ◽  
Random Coil ◽  
Special Topic ◽  
Industrial Biotechnology ◽  
In Silico Study

Background: The 1,4-alpha-glucan branching protein (GlgB) plays an important role in the glycogen biosynthesis and the deficiency in this enzyme has resulted in Glycogen storage disease and accumulation of an amylopectin-like polysaccharide. Consequently, this enzyme was considered a special topic in clinical and biotechnological research. One of the newly introduced GlgB belongs to the Neisseria sp. HMSC071A01 (Ref.Seq. WP_049335546). For in silico analysis, the 3D molecular modeling of this enzyme was conducted in the I-TASSER web server. Methods: For a better evaluation, the important characteristics of this enzyme such as functional properties, metabolic pathway and activity were investigated in the TargetP software. Additionally, the phylogenetic tree and secondary structure of this enzyme were studied by Mafft and Prabi software, respectively. Finally, the binding site properties (the maltoheptaose as substrate) were studied using the AutoDock Vina. Results: By drawing the phylogenetic tree, the closest species were the taxonomic group of Betaproteobacteria. The results showed that the structure of this enzyme had 34.45% of the alpha helix and 45.45% of the random coil. Our analysis predicted that this enzyme has a potential signal peptide in the protein sequence. Conclusion: By these analyses, a new understanding was developed related to the sequence and structure of this enzyme. Our findings can further be used in some fields of clinical and industrial biotechnology.

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