scholarly journals Proteins sequence analysis of Contagious Caprine Pleuropneumonia

2017 ◽  
Vol 33 (3) ◽  
pp. 309-319
Author(s):  
Ayuba Dauda ◽  
Abdulmojeed Yakubu ◽  
Ihe Dim ◽  
Deeve Gwaza
Keyword(s):  
Amino Acid ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Three Dimensional ◽  
Chemical Properties ◽  
Alpha Helix ◽  
Amino Acid Sequences ◽  
Contagious Bovine Pleuropneumonia ◽  
Isoleucine Leucine ◽  
Grand Average

A total of twenty (20) contagious bovine pleuropneumonia (CCPP) proteins were retrieved from the GenBank (www.ncbi.nlm.nih.gov). The proteins sequences were used to investigate the molecular identity of various CCPP proteins. The physico-chemical properties of CCPP proteins were performed using protparam tool. Isoelectric point (pI), molecular weight (MW), extinction coefficient (EC); instability index (II), aliphatic index (AI) and grand average of hydropathicity (GRAVY) were computed. The study revealed that the pI of CCPP proteins were acidic and basic in nature. The EC and II of CCPP proteins indicate better stability which is an indication of resistant to mutation and thermally stable. The GRAVY of CCPP proteins revealed some are positive while some are negative. The positive value indicates solubility (hydrophilic) in water while negative is not soluble (hydrophobic) in water. The amino acid composition of CCPP proteins indicates that they are rich in isoleucine, leucine and lysine. The three dimensional structures (3D) of the CCPP proteins were determine using Phyre2 server. The amino acid sequences of CCPP proteins were subjected to secondary structure prediction using ExPASy?s SOPMA tool. The proteins are more of alpha helix structure. The genetic information eminating from this study may bring insight into mutagenesis and pharmacogenetic. <br><br><font color="red"><b> This article has been retracted. Link to the retraction <u><a href="http://dx.doi.org/10.2298/BAH1803369E">10.2298/BAH1803369E</a><u></b></font>

In Silico Study of Secondary Structure of Hemoglobin Protein

2021 ◽  
pp. 6245-6249
Author(s):  
Roma Chandra
Keyword(s):  
Secondary Structure ◽  
Protein Sequence ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Secondary Structure Prediction ◽  
Three Dimensional ◽  
Protein Secondary Structure ◽  
Alpha Helix ◽  
Prediction Methods ◽  
Protein Secondary Structures

Protein structure prediction is one of the important goals in the area of bioinformatics and biotechnology. Prediction methods include structure prediction of both secondary and tertiary structures of protein. Protein secondary structure prediction infers knowledge related to presence of helixes, sheets and coils in a polypeptide chain whereas protein tertiary structure prediction infers knowledge related to three dimensional structures of proteins. Protein secondary structures represent the possible motifs or regular expressions represented as patterns that are predicted from primary protein sequence in the form of alpha helix, betastr and and coils. The secondary structure prediction is useful as it infers information related to the structure and function of unknown protein sequence. There are various secondary structure prediction methods used to predict about helixes, sheets and coils. Based on these methods there are various prediction tools under study. This study includes prediction of hemoglobin using various tools. The results produced inferred knowledge with reference to percentage of amino acids participating to produce helices, sheets and coils. PHD and DSC produced the best of the results out of all the tools used.

In silicoAnalysis of L-Glutaminase from Extremophiles

2019 ◽  
Vol 16 (3) ◽  
pp. 210-221
Author(s):  
Sarita Devi ◽  
Savitri ◽  
Tilak Raj ◽  
Nikhil Sharma ◽  
Wamik Azmi
Keyword(s):  
Amino Acid ◽  
Evolutionary Relationship ◽  
Chemical Properties ◽  
In Silico Analysis ◽  
Amino Acid Sequences ◽  
Multiple Sequence ◽  
Mesophilic Bacteria ◽  
Grand Average ◽  
Aliphatic Index ◽  
Nitrogen Bonds

Background:L-glutaminase enzyme belongs to the family of hydrolases, those acting on carbon-nitrogen bonds other than peptide bonds, specifically in linear amides. Protein L-glutaminase, which converts amino acid glutamine to a glutamate residue, is useful as antileukemic agent, antiretroviral agent and a new food-processing enzyme.Objective:The sequences representing L-glutaminase from extremophiles were analyzed for different physico-chemical properties and to relate these observed differences to their extremophilic properties, phylogenetic tree construction and the evolutionary relationship among them.Methods:In this work, in silico analysis of amino acid sequences of extremophilic (thermophile, halophile and psychrophiles) proteins has been done. The physiochemical properties of these four groups of proteins for L-glutaminase also differ in number of amino acids, aliphatic index and grand average of hydropathicity (GRAVY).Result:The GRAVY was found to be significantly high in thermophilic (2.29 fold) and psychrophilic bacteria (3.3 fold) as compare to mesophilic bacteria. The amino acid Cys (C) was found to be statistically significant in mesophilic bacteria (approximately or more than 3 fold) as compared to the abundance of this amino acid in extremophilic bacteria.Conclusion:Multiple sequence alignment revealed the domain/motif for glutaminase that consists of Ser-74, Lys-77, Asn-126, Lys-268, and Ser-269, which is highly conserved in all microorganisms.

scholarly journals Localnet: A Simple Recurrent Neural Network Model for Protein Secondary Structure Prediction Using Local Amino Acid Sequences Only

2021 ◽  
Author(s):  
Shutong Yang ◽  
Yuhong Wang ◽  
Kennie Cruz-Gutierrez ◽  
Fangling Wu ◽  
Chuan-Fan Ding
Keyword(s):  
Protein Structure ◽  
Amino Acid ◽  
Secondary Structure ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Protein Secondary Structure ◽  
Amino Acid Sequences ◽  
Evolutionary Information ◽  
Structure Modeling ◽  
Protein Structure Modeling

Abstract BackgroundProtein secondary structure prediction (PSSP) is important for protein structure modeling and design. Over the past a few years, deep learning models have shown promising results for PSSP. However, the current good performers for PSSP often require evolutionary information such as multiple sequence alignments and even real protein structures (templates), entire protein sequences, and amino acid property profiles. ResultsIn this study, we used a fixed-size window of adjacent residues and only amino acid sequences, without any evolutionary information, as inputs, and developed a very simple, yet accurate RNN model: LocalNet. The accuracy for three states of secondary structures is as high as 85.15%, indicating that the local amino acid sequence itself contains enough information for PSSP, a well-known classical view. By comparing to other predictors, we also achieve an state-of-art accuracy on dataset of CASP11, CASP12 and CASP13.ConclusionThe well-trained models are expected to have good applications in protein structure modeling and protein design. This model can be downloaded from https://github.com/lake-chao/protein-secondary-structure-prediction.

scholarly journals Analysis of structural similarities between brain Thy-1 antigen and immunoglobulin domains. Evidence for an evolutionary relationship and a hypothesis for its functional significance

1981 ◽  
Vol 195 (1) ◽  
pp. 31-40 ◽  
Author(s):  
F E Cohen ◽  
J Novotný ◽  
M J E Sternberg ◽  
D G Campbell ◽  
A F Williams
Keyword(s):  
Functional Significance ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Three Dimensional ◽  
Evolutionary Relationship ◽  
Dimensional Structure ◽  
Sequence Homologies ◽  
Beta Structure ◽  
Beta 2 Microglobulin

The Thy-1 membrane glycoprotein from rat brain is shown to have structural and sequence homologies with immunoglobulin (Ig) domains on the basis of the following evidence. 1. The two disulphide bonds of Thy-1 are both consistent with the Ig-fold. 2. The molecule contains extensive beta-structure as shown by the c.d. spectrum. 3. Secondary structure prediction locates beta-strands along the sequence in a manner consistent with the Ig-fold. 4. On the basis of rules derived from known beta-sheet structures, a three-dimensional structure with the Ig-fold is predicted as favourable for Thy-1. 5. Sequences in the proposed beta-strands of Thy-1 and known beta-strands of Ig domains show significant sequence homology. This homology is statistically more significant than for the comparison of proposed beta-strand sequences of beta 2-microglobulin with Ig domains. An hypothesis is presented for the possible functional significance of an evolutionary relationship between Thy-1 and Ig. It is suggested that both Thy-1 and Ig evolved from primitive molecules, with an Ig fold, which mediated cell--cell interactions. The present-day role of Thy-1 may be similar to that of the primitive domain.

scholarly journals In-silicoprediction and modeling of theEntamoeba histolyticaproteins: Serine-richEntamoeba histolyticaprotein and 29 kDa Cysteine-rich protease

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3160 ◽  
Author(s):  
Kumar Manochitra ◽  
Subhash Chandra Parija
Keyword(s):  
Amino Acid ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Amino Acid Sequences ◽  
Treatment Modalities ◽  
Bioinformatic Tools ◽  
Complex Protein ◽  
A Cell ◽  
Quaternary Structures

BackgroundAmoebiasis 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 there arises a necessity for a better diagnostic approach. Serine-richEntamoeba histolyticaprotein (SREHP), peroxiredoxin and Gal/GalNAc lectin are pivotal inE. histolyticavirulence 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. However, studies in this aspect are scant. Hence, this study was carried out to predict the structure of these target proteins and characterize them structurally as well as functionally using appropriatein-silicomethods.MethodsThe 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.ResultsThe 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 an extracellular protein, peroxiredoxin a peripheral membrane protein while Gal/GalNAc lectin was found to be a cell-wall protein. Signal peptides were found in the amino-acid sequences of SREHP and Gal/GalNAc lectin, whereas they were not present in the peroxiredoxin sequence. Gal/GalNAc lectin showed better antigenicity than the other two proteins studied. All the three proteins exhibited similarity in their structures and were mostly composed of loops.DiscussionThe 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 sub-units. Also, this protein showed less similarity with the available structural homologs. The quaternary structures of SREHP and peroxiredoxin 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 Selection of sequence motifs and generative Hopfield-Potts models for protein families

2019 ◽  
Author(s):  
Kai Shimagaki ◽  
Martin Weigt
Keyword(s):  
Amino Acid ◽  
Ad Hoc ◽  
Three Dimensional ◽  
Generative Models ◽  
Amino Acid Sequences ◽  
Dimensional Structure ◽  
Sequence Motifs ◽  
Restricted Boltzmann Machines ◽  
Potts Models ◽  
Maximum Entropy Models

Statistical models for families of evolutionary related proteins have recently gained interest: in particular pairwise Potts models, as those inferred by the Direct-Coupling Analysis, have been able to extract information about the three-dimensional structure of folded proteins, and about the effect of amino-acid substitutions in proteins. These models are typically requested to reproduce the one- and two-point statistics of the amino-acid usage in a protein family, i.e. to capture the so-called residue conservation and covariation statistics of proteins of common evolutionary origin. Pairwise Potts models are the maximum-entropy models achieving this. While being successful, these models depend on huge numbers of ad hoc introduced parameters, which have to be estimated from finite amount of data and whose biophysical interpretation remains unclear. Here we propose an approach to parameter reduction, which is based on selecting collective sequence motifs. It naturally leads to the formulation of statistical sequence models in terms of Hopfield-Potts models. These models can be accurately inferred using a mapping to restricted Boltzmann machines and persistent contrastive divergence. We show that, when applied to protein data, even 20-40 patterns are sufficient to obtain statistically close-to-generative models. The Hopfield patterns form interpretable sequence motifs and may be used to clusterize amino-acid sequences into functional sub-families. However, the distributed collective nature of these motifs intrinsically limits the ability of Hopfield-Potts models in predicting contact maps, showing the necessity of developing models going beyond the Hopfield-Potts models discussed here.

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