Amino acid sequence determination, in silico tertiary structure prediction and anticancer activity assessment of l-glutaminase from Bacillus cereus

2016 ◽  
Vol 5 (1) ◽  
Author(s):  
Priyanka Singh ◽  
Rathindra Mohan Banik ◽  
Priyanka Shah
Keyword(s):  
Amino Acid ◽  
Amino Acid Sequence ◽  
Bacillus Cereus ◽  
Anticancer Activity ◽  
In Silico ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Sequence Determination ◽  
Tertiary Structure Prediction ◽  
Activity Assessment

Protein tertiary structure prediction using hidden Markov model based on lattice

2019 ◽  
Vol 17 (02) ◽  
pp. 1950007
Author(s):  
Farzad Peyravi ◽  
Alimohammad Latif ◽  
Seyed Mohammad Moshtaghioun
Keyword(s):  
Amino Acid ◽  
Amino Acid Sequence ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Hidden Markov ◽  
Face Centered Cubic ◽  
Tertiary Structure Prediction ◽  
Cubic Lattices ◽  
Face Centered ◽  
Protein Tertiary Structure Prediction

The prediction of protein structure from its amino acid sequence is one of the most prominent problems in computational biology. The biological function of a protein depends on its tertiary structure which is determined by its amino acid sequence via the process of protein folding. We propose a novel fold recognition method for protein tertiary structure prediction based on a hidden Markov model and 3D coordinates of amino acid residues. The method introduces states based on the basis vectors in Bravais cubic lattices to learn the path of amino acids of the proteins of each fold. Three hidden Markov models are considered based on simple cubic, body-centered cubic (BCC) and face-centered cubic (FCC) lattices. A 10-fold cross validation was performed on a set of 42 fold SCOP dataset. The proposed composite methodology is compared to fold recognition methods which have HMM as base of their algorithms having approaches on only amino acid sequence or secondary structure. The accuracy of proposed model based on face-centered cubic lattices is quite better in comparison with SAM, 3-HMM optimized and Markov chain optimized in overall experiment. The huge data of 3D space help the model to have greater performance in comparison to methods which use only primary structures or only secondary structures.

PROTEIN TERTIARY STRUCTURE PREDICTION BASED ON MAIN CHAIN ANGLE USING A HYBRID BEES COLONY OPTIMIZATION ALGORITHM

2012 ◽  
Vol 09 ◽  
pp. 143-156 ◽  
Author(s):  
ZAKARIA N. MAHMOOD ◽  
MASSUDI MAHMUDDIN ◽  
MOHAMMED NOORALDEEN MAHMOOD
Keyword(s):  
Amino Acid ◽  
Amino Acid Sequence ◽  
Optimization Algorithm ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Promising Result ◽  
3D Structure ◽  
Research Area ◽  
Prototype System ◽  
Protein Tertiary Structure

Encoding proteins of amino acid sequence to predict classified into their respective families and subfamilies is important research area. However for a given protein, knowing the exact action whether hormonal, enzymatic, transmembranal or nuclear receptors does not depend solely on amino acid sequence but on the way the amino acid thread folds as well. This study provides a prototype system that able to predict a protein tertiary structure. Several methods are used to develop and evaluate the system to produce better accuracy in protein 3D structure prediction. The Bees Optimization algorithm which inspired from the honey bees food foraging method, is used in the searching phase. In this study, the experiment is conducted on short sequence proteins that have been used by the previous researches using well-known tools. The proposed approach shows a promising result.

Structural characterization of extracellular ribonuclease of Bacillus polymyxa : amino acid sequence determination and spatial structure prediction

FEBS Letters ◽  
1996 ◽  
Vol 392 (2) ◽  
pp. 105-109 ◽  
Author(s):  
A.A. Lebedev ◽  
S.V. Shlyapnikov ◽  
V.N. Pustobaev ◽  
M.P. Kirpichnikov ◽  
A.A. Dementiev
Keyword(s):  
Amino Acid ◽  
Amino Acid Sequence ◽  
Spatial Structure ◽  
Structural Characterization ◽  
Structure Prediction ◽  
Bacillus Polymyxa ◽  
Sequence Determination

scholarly journals In-silico prediction and modeling of the Entamoeba histolytica proteins: Serine-rich Entamoeba histolytica protein and peroxiredoxin

2016 ◽  
Author(s):  
Kumar Manochitra ◽  
Subhash Chandra Parija
Keyword(s):  
Amino Acid ◽  
Entamoeba Histolytica ◽  
In Silico ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Amino Acid Sequences ◽  
Treatment Modalities ◽  
Bioinformatic Tools ◽  
Quaternary Structures

Background: Amoebiasis is the third most common parasitic cause of morbidity and mortality particularly in countries with poor hygienic settings. There exists an ambiguity in the diagnosis of amoebiasis, and hence arises a necessity for a better diagnostic approach. Serine-rich Entamoeba histolytica protein (SREHP), peroxiredoxin and Gal/GalNAc lectin are pivotal in E. histolytica virulence and are extensively studied as diagnostic and vaccine targets. For elucidating the cellular function of these proteins, details regarding their respective quaternary structures are essential which are not available till date. Hence, this study was carried out to predict the structure of these target proteins and characterize them structurally as well as functionally using relevant in-silico methods. Methods:The amino acid sequences of the proteins were retrieved from National Centre for Biotechnology Information database and aligned using ClustalW. Bioinformatic tools were employed in the secondary structure and tertiary structure prediction. The predicted structure was validated, and final refinement was carried out. Results: The protein structures predicted by i-TASSER were found to be more accurate than Phyre2 based on the validation using SAVES server. The prediction suggests SREHP to be a extracellular protein, peroxiredoxin was a peripheral membrane protein, while Gal/GalAc was found to be a cell-wall protein. Signal peptides were found in the amino-acid sequences of SREHP and Gal/GalNAc, whereas they were not present in the peroxiredoxin sequence. Gal/GalNAc lectin showed better antigenicity than the other two proteins studied. All three proteins exhibited similarity in their structures and were mostly composed of loops. Discussion:The structures of SREHP and peroxiredoxin were predicted successfully, while the structure of Gal/GalNAc lectin could not be predicted as it was a complex protein composed of three sub-units. Also, this protein showed less similarity with the available structural homologs. The quaternary structures predicted from this study would provide better structural and functional insights into these proteins and may aid in development of newer diagnostic assays or enhancement of the available treatment modalities.

scholarly journals In-silico prediction and modeling of the Entamoeba histolytica proteins: Serine-rich Entamoeba histolytica protein and peroxiredoxin

2016 ◽  
Author(s):  
Kumar Manochitra ◽  
Subhash Chandra Parija
Keyword(s):  
Amino Acid ◽  
Entamoeba Histolytica ◽  
In Silico ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Amino Acid Sequences ◽  
Treatment Modalities ◽  
Bioinformatic Tools ◽  
Quaternary Structures

Background: Amoebiasis is the third most common parasitic cause of morbidity and mortality particularly in countries with poor hygienic settings. There exists an ambiguity in the diagnosis of amoebiasis, and hence arises a necessity for a better diagnostic approach. Serine-rich Entamoeba histolytica protein (SREHP), peroxiredoxin and Gal/GalNAc lectin are pivotal in E. histolytica virulence and are extensively studied as diagnostic and vaccine targets. For elucidating the cellular function of these proteins, details regarding their respective quaternary structures are essential which are not available till date. Hence, this study was carried out to predict the structure of these target proteins and characterize them structurally as well as functionally using relevant in-silico methods. Methods:The amino acid sequences of the proteins were retrieved from National Centre for Biotechnology Information database and aligned using ClustalW. Bioinformatic tools were employed in the secondary structure and tertiary structure prediction. The predicted structure was validated, and final refinement was carried out. Results: The protein structures predicted by i-TASSER were found to be more accurate than Phyre2 based on the validation using SAVES server. The prediction suggests SREHP to be a extracellular protein, peroxiredoxin was a peripheral membrane protein, while Gal/GalAc was found to be a cell-wall protein. Signal peptides were found in the amino-acid sequences of SREHP and Gal/GalNAc, whereas they were not present in the peroxiredoxin sequence. Gal/GalNAc lectin showed better antigenicity than the other two proteins studied. All three proteins exhibited similarity in their structures and were mostly composed of loops. Discussion:The structures of SREHP and peroxiredoxin were predicted successfully, while the structure of Gal/GalNAc lectin could not be predicted as it was a complex protein composed of three sub-units. Also, this protein showed less similarity with the available structural homologs. The quaternary structures predicted from this study would provide better structural and functional insights into these proteins and may aid in development of newer diagnostic assays or enhancement of the available treatment modalities.

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.

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