scholarly journals In silico Characterization of UGT74G1 Protein in Stevia rebaudiana Bertoni Accession MS007

2021 ◽  
Vol 11 (3) ◽  
pp. 323-330
Author(s):  
Afiqah Khan ◽  
◽  
Nor Mokthar ◽  
Zarina Zainuddin ◽  
Nurul Samsulrizal ◽  
...  
Keyword(s):  
In Silico ◽  
Tertiary Structure ◽  
Target Identification ◽  
Stevia Rebaudiana ◽  
In Silico Analysis ◽  
Human Consumption ◽  
Steviol Glycosides ◽  
High Similarity ◽  
Protein Motif ◽  
Enhanced Production

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.

In Silico Study of Potential Cross-Kingdom Plant MicroRNA Based Regulation in Chronic Myeloid Leukemia

2020 ◽  
Vol 17 (2) ◽  
pp. 125-132
Author(s):  
Marjanu Hikmah Elias ◽  
Noraziah Nordin ◽  
Nazefah Abdul Hamid
Keyword(s):  
Targeted Therapy ◽  
In Silico ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Target Prediction ◽  
In Silico Analysis ◽  
Microrna Target ◽  
Good Target

Background: Chronic Myeloid Leukaemia (CML) is associated with the BCRABL1 gene, which plays a central role in the pathogenesis of CML. Thus, it is crucial to suppress the expression of BCR-ABL1 in the treatment of CML. MicroRNA is known to be a gene expression regulator and is thus a good candidate for molecularly targeted therapy for CML. Objective: This study aims to identify the microRNAs from edible plants targeting the 3’ Untranslated Region (3’UTR) of BCR-ABL1. Methods: In this in silico analysis, the sequence of 3’UTR of BCR-ABL1 was obtained from Ensembl Genome Browser. PsRNATarget Analysis Server and MicroRNA Target Prediction (miRTar) Server were used to identify miRNAs that have binding conformity with 3’UTR of BCR-ABL1. The MiRBase database was used to validate the species of plants expressing the miRNAs. The RNAfold web server and RNA COMPOSER were used for secondary and tertiary structure prediction, respectively. Results: In silico analyses revealed that cpa-miR8154, csi-miR3952, gma-miR4414-5p, mdm-miR482c, osa-miR1858a and osa-miR1858b show binding conformity with strong molecular interaction towards 3’UTR region of BCR-ABL1. However, only cpa-miR- 8154, osa-miR-1858a and osa-miR-1858b showed good target site accessibility. Conclusion: It is predicted that these microRNAs post-transcriptionally inhibit the BCRABL1 gene and thus could be a potential molecular targeted therapy for CML. However, further studies involving in vitro, in vivo and functional analyses need to be carried out to determine the ability of these miRNAs to form the basis for targeted therapy for CML.

scholarly journals Reduction of the Oxidative Stress Status Using Steviol Glycosides in a Fish Model (Cyprinus carpio)

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Livier Mireya Sánchez-Aceves ◽  
Octavio Dublán-García ◽  
Leticia-Xochitl López-Martínez ◽  
Karen Adriana Novoa-Luna ◽  
Hariz Islas-Flores ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Antioxidant Activity ◽  
Cyprinus Carpio ◽  
Stevia Rebaudiana ◽  
Protein Carbonyl ◽  
Human Consumption ◽  
Steviol Glycosides ◽  
Protein Carbonyl Content ◽  
Fish Model ◽  
Oxidative Stress Status

Steviol glycosides are sweetening compounds from the Stevia rebaudiana Bertoni plant. This product is considered safe for human consumption and was approved as a food additive by the Food and Drugs Administration (FDA) and European Food Safety Authority (EFSA). Its effects on the ecosystem have not been studied in depth; therefore, it is necessary to carry out ecotoxicological studies in organisms such as Cyprinus carpio. The present study aimed to evaluate the antioxidant activity by SGs on diverse tissues in C. carpio using oxidative stress (OS) biomarkers. To test the antioxidant activity, carps were exposed to four systems: (1) SGs free control, (2) CCl4 0.5 mL/kg, (3) SGs 1 g/L, and (4) CCl4 0.5 mL/kg + SGs 1 g/L at 96 h. The following biomarkers were analyzed: lipoperoxidation (LPX), hydroperoxide content (HPC), and protein carbonyl content (PCC), as well as antioxidant activity of superoxide dismutase (SOD) and catalase (CAT). It was found that both (3 and 4) systems’ exposure decreases LPX, CHP, PCC, SOD, and CAT with respect to the CCl4 system. The results of this study demonstrate that the concentrations of SGs used are not capable of generating oxidative stress and, on the contrary, would appear to induce an antioxidant effect.

scholarly journals Extensive In Silico Analysis of the Functional and Structural Consequences of SNPs in Human ARX Gene

2020 ◽  
Author(s):  
Mujahed I. Mustafa ◽  
Naseem S. Murshed ◽  
Abdelrahman H. Abdelmoneim ◽  
Abdelrafie M. Makhawi
Keyword(s):  
In Silico ◽  
Tertiary Structure ◽  
Motor Impairment ◽  
Gene Mutations ◽  
In Silico Analysis ◽  
Epileptic Encephalopathy ◽  
Nucleotide Polymorphisms ◽  
Severe Intellectual Disability ◽  
Structural Impacts ◽  
Silico Analysis

AbstractEarly infantile epileptic encephalopathy 1 (EIEE1) is a rare but devastating neurologic disorder that displays concomitant cognitive and motor impairment, and is often presented in the first months of life with severe intellectual disability. The objective of this study is to classify the most deleterious nsSNPs in ARX gene that may cause EIEE1 disease. Despite the reported association of ARX gene mutations with vulnerability to several neurologic condition, there is lack of in silico analysis on the functional and structural impacts of single nucleotide polymorphisms (SNPs) of the ARX at protein level. Therefore, the pathogenic nsSNPs in the human ARX obtained from NCBI were analyzed for their functional and structural impact using bioinformatics tools like SIFT, Polyphen, PROVEAN, I-Mutant, and MUPro. The effects of the mutations on tertiary structure of the human ARX protein were predicted using RaptorX and visualized by UCSF Chimera while STRING was used to investigate its protein–protein interaction. Our extensive in silico analysis revealed 11 mutations that will significantly alter the structure of human ARX protein; that may disturb the domain which will affect the function of the protein. Extensive in silico analysis of the functional and structural consequences of SNPs in human ARX gene revealed 11 mutations (L535Q, R528S, R380L, V374D, L343Q, T333N, T333S, R332H, R330H, G34R and L33P) that may cause EIEE1.Therefore, can be used as diagnostic markers for EIEE1.

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 Design an efficient multi-epitope peptide vaccine candidate against SARS-CoV-2: An in silico analysis

2020 ◽  
Author(s):  
Zahra Yazdani ◽  
Alireza Rafiei ◽  
Mohammadreza Yazdani ◽  
Reza Valadan
Keyword(s):  
Escherichia Coli ◽  
In Silico ◽  
Tertiary Structure ◽  
Peptide Vaccine ◽  
High Mobility ◽  
In Silico Analysis ◽  
Epitope Peptide ◽  
Cellular And Humoral Immunity ◽  
Cellular Immune ◽  
Immunodominant Epitopes

AbstractBackgroundTo date, no specific vaccine or drug has been proven to be effective for SARS-CoV-2 infection. Therefore, we implemented immunoinformatics approach to design an efficient multi-epitopes vaccine against SARS-CoV-2.ResultsThe designed vaccine construct has several immunodominant epitopes from structural proteins of Spike, Nucleocapsid, Membrane and Envelope. These peptides promote cellular and humoral immunity and Interferon gamma responses. In addition, these epitopes have antigenicity ability and no allergenicity probability. To enhance the vaccine immunogenicity, we used three potent adjuvants; Flagellin, a driven peptide from high mobility group box 1 as HP-91 and human beta defensin 3 protein. The physicochemical and immunological properties of the vaccine structure were evaluated. Tertiary structure of the vaccine protein was predicted and refined by I-Tasser and galaxi refine and validated using Rampage and ERRAT. Results of Ellipro showed 242 residues from vaccine might be conformational B cell epitopes. Docking of vaccine with Toll-Like Receptors 3, 5 and 8 proved an appropriate interaction between the vaccine and receptor proteins. In silico cloning demonstrated that the vaccine can be efficiently expressed in Escherichia coli.ConclusionsThe designed multi epitope vaccine is potentially antigenic in nature and has the ability to induce humoral and cellular immune responses against SARS-CoV-2. This vaccine can interact appropriately with the TLR3, 5, and 8. Also, this vaccine has high quality structure and suitable characteristics such as high stability and potential for expression in Escherichia coli.

scholarly journals A Bioinformatics Approach for the Prediction of Immunogenic Properties and Structure of the SARS-COV-2 B.1.617.1 Variant Spike Protein

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Vijay Kumar Srivastava ◽  
Sanket Kaushik ◽  
Gazal Bhargava ◽  
Ajay Jain ◽  
Juhi Saxena ◽  
...  
Keyword(s):  
Amino Acid ◽  
T Cell ◽  
B Cell ◽  
In Silico ◽  
Tertiary Structure ◽  
In Silico Analysis ◽  
Respiratory Illness ◽  
T Cell Epitopes ◽  
S Protein ◽  
Immunogenic Properties

Background. B.1.617.1, a variant of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causing respiratory illness is responsible for the second wave of COVID-19 and associated with a high incidence of infectivity and mortality. To mitigate the B.1.617.1 variant of SARS-CoV-2, deciphering the protein structure and immunological responses by employing bioinformatics tools for data mining and analysis is pivotal. Objectives. Here, an in silico approach was employed for deciphering the structure and immune function of the subunit of spike (S) protein of SARS-CoV-2 B.1.617.1 variant. Methods. The partial amino acid sequence of SARS-CoV-2 B.1.617.1 variant S protein was analyzed, and its putative secondary and tertiary structure was predicted. Immunogenic analyses including B- and T-cell epitopes, interferon-gamma (IFN-γ) response, chemokine, and protective antigens for SARS-CoV 2 S proteins were predicted using appropriate tools. Results. B.1.617.1 variant S protein sequence was found to be highly stable and amphipathic. ABCpred and CTLpred analyses led to the identification of two potential antigenic B cell and T cell epitopes with starting amino acid positions at 60 and 82 (for B cell epitopes) and 54 and 98 (for T cell epitopes) having prediction scores > 0.8 . Further, RAMPAGE tool was used for determining the allowed and disallowed regions of the three-dimensional predicted structure of SARS-CoV-2 B.1.617.1 variant S protein. Conclusion. Together, the in silico analysis revealed the predicted structure of partial S protein, immunogenic properties, and possible regions for S protein of SARS-CoV-2 and provides a valuable prelude for engineering the targeted vaccine or drug against B.1.617.1 variant of SARS-CoV-2.

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