scholarly journals Sequence Analysis and Structure Prediction of Malaysia SARS-CoV-2 Strain’s Structural and Accessory Proteins

2021 ◽  
Vol 12 (3) ◽  
pp. 3259-3304
Keyword(s):  
Structure Prediction ◽  
Active Sites ◽  
Homo Sapiens ◽  
Functional Characterization ◽  
Protein Structures ◽  
Three Dimensional ◽  
Experimental Models ◽  
Amino Acid Sequences ◽  
Accessory Proteins ◽  
Evolutionary Analysis

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that transmitted from animal to human became a life-threatening pandemic in 2020. Scientists are currently testing several drugs to eradicate the COVID-19 outbreak. However, there is no 100 % effective drug or vaccine against SARS-CoV-2 has been discovered so far. In this study, we explored the structure prediction and functional analysis of 75 Malaysia SARS-CoV-2 strain’s structural and accessory proteins without the presence of experimental models. Physiochemical analysis, secondary structure analysis, structure prediction, functional characterization, active site identification, and evolutionary analysis based on the amino acid sequences retrieved from National Centre for Biotechnology Information (NCBI). Three-dimensional (3-D) protein structures were built using the Swiss model. The quality of protein models was verified by ERRAT, PROCHECK, and Verify 3D tools. Active prediction analysis revealed the high potential active sites of proteins where the anti-viral drug or vaccine may bind and inhibit the viral activities. Molecular phylogenetic analysis of ORF10, ORF8, and ORF6 proteins from five different species was analyzed. The results from this analysis proved that Homo sapiens SARS-CoV-2 had high genetic similarity with the bat coronavirus. These analyses may help in designing structure-based anti-viral drugs or to develop potential vaccines for SARS-CoV-2.

scholarly journals Sequence Analysis and Structure Prediction of SARS-CoV-2 Accessory Proteins 9b and ORF14: Evolutionary Analysis Indicates Close Relatedness to Bat Coronavirus

2020 ◽  
Author(s):  
CHITTARANJAN BARUAH ◽  
PAPARI DEVI ◽  
DHIRENDRA K SHARMA
Keyword(s):  
Functional Analysis ◽  
Amino Acid ◽  
Sequence Analysis ◽  
Structure Prediction ◽  
Functional Characterization ◽  
Amino Acid Sequences ◽  
Accessory Proteins ◽  
Evolutionary Analysis ◽  
Bat Coronavirus ◽  
Close Relatedness

<p>This paper has attempted into the structure prediction and functional analysis of two such accessory proteins, 9b and ORF14, in the absence of experimental structures. Sequence analysis, structure prediction, functional characterization, and evolutionary analysis based on the UniProtKB reviewed the amino acid sequences of SARS-CoV-2 9b (P0DTD2) and ORF14 (P0DTD3) proteins. Modeling has been presented with the introduction of hybrid comparative and <i>ab-initio</i> modeling. The evolutionary analysis of both the proteins of human SARS-CoV-2 indicates close relatedness to the bat coronavirus.</p> <p> </p>

scholarly journals Sequence Analysis and Structure Prediction of SARS-CoV-2 Accessory Proteins 9b and ORF14: Evolutionary Analysis Indicates Close Relatedness to Bat Coronavirus

2020 ◽  
Author(s):  
CHITTARANJAN BARUAH ◽  
PAPARI DEVI ◽  
DHIRENDRA K SHARMA
Keyword(s):  
Functional Analysis ◽  
Amino Acid ◽  
Sequence Analysis ◽  
Structure Prediction ◽  
Functional Characterization ◽  
Amino Acid Sequences ◽  
Accessory Proteins ◽  
Evolutionary Analysis ◽  
Bat Coronavirus ◽  
Close Relatedness

<p>This paper has attempted into the structure prediction and functional analysis of two such accessory proteins, 9b and ORF14, in the absence of experimental structures. Sequence analysis, structure prediction, functional characterization, and evolutionary analysis based on the UniProtKB reviewed the amino acid sequences of SARS-CoV-2 9b (P0DTD2) and ORF14 (P0DTD3) proteins. Modeling has been presented with the introduction of hybrid comparative and <i>ab-initio</i> modeling. The evolutionary analysis of both the proteins of human SARS-CoV-2 indicates close relatedness to the bat coronavirus.</p> <p> </p>

In silico Proteome analysis of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (Preprint)

2020 ◽  
Author(s):  
Chittaranjan Baruah ◽  
PAPARI DEVI ◽  
DHIRENDRA K SHARMA
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
In Silico ◽  
Structure Prediction ◽  
Active Sites ◽  
Tertiary Structure ◽  
Functional Characterization ◽  
Protein Structures ◽  
Reference Sequence ◽  
Significant Similarity ◽  
Drug Designing

BACKGROUND Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive-sense, single-stranded RNA coronavirus. The virus is the causative agent of coronavirus disease 2019 (COVID-19) and is contagious through human-to-human transmission. The RNA genome of SARS-CoV-2 encodes 29 proteins, though one may not get expressed. 15 proteins are not yet having experimental structures for investigation on possible drug targets. OBJECTIVE The present study reports sequence analysis, complete coordinate tertiary structure prediction and in silico sequence-based and structure-based functional characterization of full SARS-CoV-2 proteome based on the NCBI reference sequence NC_045512 (29903 bp ss-RNA). METHODS A total of 25 polypeptides have been analyzed out of which 15 proteins are not yet having experimental structures and only 10 are having experimental structures with known PDB IDs. Out of 15 newly predicted structures six (6) were predicted using comparative modeling and nine (09) proteins having no significant similarity with so far available PDB structures were modeled using ab-initio modeling. QMEANDisCo 4.0.0 and ProQ3 for global and local (per-residue) quality estimates is used for structure verification. RESULTS The all-atom model of tertiary structure of high quality and may be useful for structure-based drug designing targets. The study has identified along with nine major targets sixteen nonstructural proteins (NSPs), which may be equally important from the drug design angle. Tunnel analysis revealed the presence of large number of tunnels in NSP3, ORF 6 protein and membrane glycoprotein indicating a large number of transport pathways for small ligands influencing their reactivity. CONCLUSIONS The 15 theoretical structures would perhaps be useful for the scientific community for advanced computational analysis on interactions of each protein for detailed functional analysis of active sites towards structure based drug designing or to study potential vaccines, if at all, towards preventing epidemics and pandemics in absence of complete experimental structure. CLINICALTRIAL The protein structures have been deposited to ModelArchive.

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.

Prediction of Structural and Functional Aspects of Protein

2014 ◽  
pp. 317-333
Author(s):  
Arun G. Ingale
Keyword(s):  
Protein Structure ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Sequence Information ◽  
Predict Protein Structure ◽  
Basic Ideas

To predict the structure of protein from a primary amino acid sequence is computationally difficult. An investigation of the methods and algorithms used to predict protein structure and a thorough knowledge of the function and structure of proteins are critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this chapter sheds light on the methods used for protein structure prediction. This chapter covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, it presents an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction, giving unique insight into the future applications of the modeled protein structures. In this chapter, current protein structure prediction methods are reviewed for a milieu on structure prediction, the prediction of structural fundamentals, tertiary structure prediction, and functional imminent. The basic ideas and advances of these directions are discussed in detail.

scholarly journals Protein Structure Determination in Living Cells

2019 ◽  
Vol 20 (10) ◽  
pp. 2442 ◽  
Author(s):  
Teppei Ikeya ◽  
Peter Güntert ◽  
Yutaka Ito
Keyword(s):  
Protein Structure ◽  
Structure Determination ◽  
Structure Prediction ◽  
Structural Information ◽  
Nuclear Overhauser Effect ◽  
Protein Structures ◽  
Three Dimensional ◽  
Structural Data ◽  
Sample Tube ◽  
In Cells

To date, in-cell NMR has elucidated various aspects of protein behaviour by associating structures in physiological conditions. Meanwhile, current studies of this method mostly have deduced protein states in cells exclusively based on ‘indirect’ structural information from peak patterns and chemical shift changes but not ‘direct’ data explicitly including interatomic distances and angles. To fully understand the functions and physical properties of proteins inside cells, it is indispensable to obtain explicit structural data or determine three-dimensional (3D) structures of proteins in cells. Whilst the short lifetime of cells in a sample tube, low sample concentrations, and massive background signals make it difficult to observe NMR signals from proteins inside cells, several methodological advances help to overcome the problems. Paramagnetic effects have an outstanding potential for in-cell structural analysis. The combination of a limited amount of experimental in-cell data with software for ab initio protein structure prediction opens an avenue to visualise 3D protein structures inside cells. Conventional nuclear Overhauser effect spectroscopy (NOESY)-based structure determination is advantageous to elucidate the conformations of side-chain atoms of proteins as well as global structures. In this article, we review current progress for the structure analysis of proteins in living systems and discuss the feasibility of its future works.

CooPPS: A SYSTEM FOR THE COOPERATIVE PREDICTION OF PROTEIN STRUCTURES

2004 ◽  
Vol 02 (03) ◽  
pp. 471-495 ◽  
Author(s):  
LUIGI PALOPOLI ◽  
GIORGIO TERRACINA
Keyword(s):  
Structure Prediction ◽  
Protein Structures ◽  
Three Dimensional ◽  
Quality Parameters ◽  
Dimensional Structure ◽  
Prediction Problem ◽  
Common Reference ◽  
Prediction Tools ◽  
Definition Of

Predicting the three-dimensional structure of proteins is a difficult task. In the last few years several approaches have been proposed for performing this task taking into account different protein chemical and physical properties. As a result, a growing number of protein structure prediction tools is becoming available, some of them specialized to work on either some aspects of the predictions or on some categories of proteins; however, they are still not sufficiently accurate and reliable for predicting all kinds of proteins. In this context, it is useful to jointly apply different prediction tools and combine their results in order to improve the quality of the predictions. However, several problems have to be solved in order to make this a viable possibility. In this paper a framework and a tool is proposed which allows: (i) definition of a common reference applicative domain for different prediction tools; (ii) characterization of prediction tools through evaluating some quality parameters; (iii) characterization of the performances of a team of predictors jointly applied over a prediction problem; (iv) the singling out of the best team for a prediction problem; and (v) the integration of predictor results in the team in order to obtain a unique prediction. A system implementing the various steps of the proposed framework (CooPPS) has been developed and several experiments for testing the effectiveness of the proposed approach have been carried out.

scholarly journals The breakthrough in protein structure prediction

2021 ◽  
Vol 478 (10) ◽  
pp. 1885-1890
Author(s):  
Andrei N. Lupas ◽  
Joana Pereira ◽  
Vikram Alva ◽  
Felipe Merino ◽  
Murray Coles ◽  
...  
Keyword(s):  
Structure Prediction ◽  
Life Sciences ◽  
Three Dimensional ◽  
Critical Assessment ◽  
Amino Acid Sequences ◽  
Prediction Problem ◽  
Linear Chains ◽  
Single Protein ◽  
Artificial Intelligence Laboratory ◽  
The Relationship

Proteins are the essential agents of all living systems. Even though they are synthesized as linear chains of amino acids, they must assume specific three-dimensional structures in order to manifest their biological activity. These structures are fully specified in their amino acid sequences — and therefore in the nucleotide sequences of their genes. However, the relationship between sequence and structure, known as the protein folding problem, has remained elusive for half a century, despite sustained efforts. To measure progress on this problem, a series of doubly blind, biennial experiments called CASP (critical assessment of structure prediction) were established in 1994. We were part of the assessment team for the most recent CASP experiment, CASP14, where we witnessed an astonishing breakthrough by DeepMind, the leading artificial intelligence laboratory of Alphabet Inc. The models filed by DeepMind's structure prediction team using the program AlphaFold2 were often essentially indistinguishable from experimental structures, leading to a consensus in the community that the structure prediction problem for single protein chains has been solved. Here, we will review the path to CASP14, outline the method employed by AlphaFold2 to the extent revealed, and discuss the implications of this breakthrough for the life sciences.

scholarly journals Analytical tools in protein structure determination

2021 ◽  
Vol 8 (3) ◽  
pp. 103-111
Author(s):  
Krishna R Gupta ◽  
Uttam Patle ◽  
Uma Kabra ◽  
P. Mishra ◽  
Milind J Umekar
Keyword(s):  
Protein Structure ◽  
Structure Determination ◽  
Structure Prediction ◽  
Protein Structures ◽  
Three Dimensional ◽  
Protein Structure Determination ◽  
Computational Techniques ◽  
Determination Process ◽  
Structure Databases ◽  
Analytical Tools

Three-dimensional protein structure prediction from amino acid sequence has been a thought-provoking task for decades, but it of pivotal importance as it provides a better understanding of its function. In recent years, the methods for prediction of protein structures have advanced considerably. Computational techniques and increase in protein sequence and structure databases have influence the laborious protein structure determination process. Still there is no single method which can predict all the protein structures. In this review, we describe the four stages of protein structure determination. We have also explored the currenttechniques used to uncover the protein structure and highpoint best suitable method for a given protein.

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>

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