In silico analysis, expression profiling and correlation of miRNAs targeting genes of steviol glycosides biosynthesis with steviol glycosides contents in different tissues of Stevia rebaudiana

Due to its low-calorie property, Stevia rebaudiana is being promoted as an alternative sweetener for diabetic and obese patients. The steady demand in the market for high-quality stevia extracts presents a challenge for the enhanced production of steviol glycosides that are safe for human consumption. This study characterized the structure and content of the gene involved in the production of UGT74G1 protein for Stevia rebaudiana accession MS007 through in silico analysis using a transcriptome dataset of stevia MS007. Homologous search using BLASTp shows high similarity to Q6VAA6 RecName: Full=UDP-glycosyltransferase 74G1 (S. rebaudiana) as the top hit sequence. InterPro family and domain protein motif search revealed UDP-glucuronosyl/UDP-glucosyltransferase (IPR002213) and UDP-glycosyltransferase family, conserved site (IPR035595). The phylogenetic tree construction was done by selecting 14 out of 102 protein sequences from BLASTp search. The phylogenetic analysis revealed a high value of bootstrapping, which was 100, indicating the high similarity between UGT74G1 (Q6VAA6.1 and Cluster-31069.45201) in S. rebaudiana. ProtParam ExPASy, PSIPRED, and Phyre2 computed the primary, secondary, and tertiary structures for UGT74G1 protein. The UGT74G1 predicted tertiary structure scored 100.0% confidence by the single highest scoring template and coverage of 96%. The model has dimensions (Å) of X: 57.609, Y: 70.386, and Z: 58.351. Outcomes of this research will help enhance understanding UDP-glycosyltransferase 74G1 (S. rebaudiana MS007) characteristics and enhance target identification processes to improve understanding of protein-protein interaction in S. rebaudiana MS007.

Download Full-text

Comparison of mammalian cell entry operons of mycobacteria: in silico analysis and expression profiling

FEMS Immunology & Medical Microbiology ◽

10.1016/j.femsim.2004.08.013 ◽

2005 ◽

Vol 43 (2) ◽

pp. 185-195 ◽

Cited By ~ 34

Author(s):

Ashwani Kumar ◽

Amita Chandolia ◽

Uma Chaudhry ◽

Vani Brahmachari ◽

Mridula Bose

Keyword(s):

Mammalian Cell ◽

Expression Profiling ◽

In Silico ◽

In Silico Analysis ◽

Cell Entry ◽

Silico Analysis

Download Full-text

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

Seminars in Oncology ◽

10.1053/j.seminoncol.2020.02.012 ◽

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

Download Full-text

In Silico Analysis of Single Nucleotide Polymorphism in Human Prothrombin Gene

10.1055/s-0039-1680245 ◽

2019 ◽

Author(s):

I. Farah ◽

A. El-Mubark ◽

M. Osman ◽

A. Soliman ◽

F. Ali ◽

...

Keyword(s):

Single Nucleotide Polymorphism ◽

In Silico ◽

In Silico Analysis ◽

Nucleotide Polymorphism ◽

Single Nucleotide ◽

Prothrombin Gene ◽

Silico Analysis

Download Full-text

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

Current Medicinal Chemistry ◽

10.2174/0929867327666200727114410 ◽

2020 ◽

Vol 27 (38) ◽

pp. 6523-6535 ◽

Cited By ~ 3

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.

Download Full-text