Structural Analysis of the SARS-CoV-2 Omicron Variant Proteins

The spread of the latest SARS-CoV-2 variant Omicron is particularly concerning because of the large number of mutations present in its genome and lack of knowledge about how these mutations would affect the current SARS-CoV-2 vaccines and treatments. Here, by performing phylogenetic analysis using the Omicron spike (S) protein sequence, we found that the Omicron S protein presented the longest evolutionary distance in relation to the other SARS-CoV-2 variants. We predicted the structures of S, M, and N proteins of the Omicron variant using AlphaFold2 and investigated how the mutations have affected the S protein and its parts, S1 NTD and RBD, in detail. We found many amino acids on RBD were mutated, which may influence the interactions between the RBD and ACE2, while also showing the S309 antibody could still be capable of neutralizing Omicron RBD. The Omicron S1 NTD structures display significant differences from the original strain, which could lead to reduced recognition by antibodies resulting in potential immune escape and decreased effectiveness of the existing vaccines. However, this study of the Omicron variant was mainly limited to structural predictions, and these findings should be explored and verified by subsequent experiments. This study provided basic data of the Omicron protein structures that lay the groundwork for future studies related to the SARS-CoV-2 Omicron variant.

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DECREASED BREADTH OF THE ANTIBODY RESPONSE TO THE SPIKE PROTEIN OF SARS-CoV-2 AFTER VACCINATION

10.1101/2021.08.12.21261952 ◽

2021 ◽

Author(s):

Lydia Horndler ◽

Pilar Delgado ◽

Salvador Romero-Pinedo ◽

Marina Quesada ◽

Ivaylo Balabanov ◽

...

Keyword(s):

Flow Cytometry ◽

Protein Sequence ◽

Rapid Development ◽

Humoral Response ◽

Spike Protein ◽

Relative Reduction ◽

Original Strain ◽

S Protein ◽

Highly Sensitive ◽

Igg1 Isotype

The rapid development of vaccines to prevent infection by SARS-CoV-2 virus causing COVID-19 makes necessary to compare the capacity of the different vaccines in terms of development of a protective humoral response. Here, we have used a highly sensitive and reliable flow cytometry method to measure the titers of antibodies of the IgG1 isotype in blood of volunteers after receiving one or two doses of the vaccines being administered in Spain. We took advantage of the multiplexed capacity of the method to measure simultaneously the reactivity of antibodies with the S protein of the original strain Wuhan-1 and the variant B.1.1.7 (Alpha). We found significant differences in the titer of anti-S antibodies produced after a first dose of the vaccines ChAdOx1 nCov-19/AstraZeneca, mRNA-1273/Moderna, BNT162b2/Pfizer-BioNTech and Ad26.COV.S/Janssen. Most important, we found a relative reduction in the reactivity of the sera with the B.1.1.7 versus the Wuhan-1 variant after the second boosting immunization. These data allow to make a comparison of different vaccines in terms of anti-S antibody generation and cast doubts about the convenience of repeatedly immunizing with the same S protein sequence.

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DV-Curve Representation of Protein Sequences and Its Application

Computational and Mathematical Methods in Medicine ◽

10.1155/2014/203871 ◽

2014 ◽

Vol 2014 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Wei Deng ◽

Yihui Luan

Keyword(s):

Amino Acids ◽

Protein Sequence ◽

Graphical Representation ◽

Protein Sequences ◽

Quantitative Comparison ◽

The Other ◽

Hp Model ◽

Dual Vector ◽

Numerical Characterization ◽

Curve Representation

Based on the detailed hydrophobic-hydrophilic(HP) model of amino acids, we propose dual-vector curve (DV-curve) representation of protein sequences, which uses two vectors to represent one alphabet of protein sequences. This graphical representation not only avoids degeneracy, but also has good visualization no matter how long these sequences are, and can reflect the length of protein sequence. Then we transform the 2D-graphical representation into a numerical characterization that can facilitate quantitative comparison of protein sequences. The utility of this approach is illustrated by two examples: one is similarity/dissimilarity comparison among different ND6 protein sequences based on their DV-curve figures the other is the phylogenetic analysis among coronaviruses based on their spike proteins.

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Rapidly emerging SARS-CoV-2 B.1.1.7 sub-lineage in the United States of America with spike protein D178H and membrane protein V70L mutations

10.1101/2021.05.14.21257247 ◽

2021 ◽

Author(s):

Lishuang Shen ◽

Jennifer Dien Bard ◽

Timothy J Triche ◽

Alexander R Judkins ◽

Jaclyn A Biegel ◽

...

Keyword(s):

United States ◽

Phylogenetic Analysis ◽

Structural Analysis ◽

United States Of America ◽

The United States ◽

Spike Protein ◽

M Protein ◽

Receptor Binding Domain ◽

S Protein ◽

The U.S

The SARS-CoV-2 B.1.1.7 lineage is highly infectious and as of April 2021 accounted for 92% of COVID-19 cases in Europe and 59% of COVID-19 cases in the U.S. It is defined by the N501Y mutation in the receptor binding domain (RBD) of the Spike (S) protein, and a few other mutations. These include two mutations in the N terminal domain (NTD) of the S protein, HV69-70del and Y144del (also known as Y145del due to the presence of tyrosine at both positions). We recently identified several emerging SARS-CoV-2 variants of concerns, characterized by Membrane (M) protein mutations, including I82T and V70L. We now identify a sub-lineage of B.1.1.7 that emerged through sequential acquisitions of M:V70L in November 2020 followed by a novel S:D178H mutation first observed in early February 2021. The percentage of B.1.1.7 isolates in the U.S. that belong to this sub-lineage increased from 0.15% in February 2021 to 1.8% in April 2021. To date this sub-lineage appears to be U.S.-specific with reported cases in 31 states, including Hawaii. As of April 2021 it constituted 36.8% of all B.1.1.7 isolates in Washington. Phylogenetic analysis and transmission inference with Nextstrain suggests this sub-lineage likely originated in either California or Washington. Structural analysis revealed that the S:D178H mutation is in the NTD of the S protein and close to two other signature mutations of B.1.1.7, HV69-70del and Y144del. It is surface exposed and may alter NTD tertiary configuration or accessibility, and thus has the potential to affect neutralization by NTD directed antibodies.

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Structuralism as a Pamphlet (On the Book by E. Reinert “How Rich CountriesGot Rich... And Why Poor Countries Stay Poor”. 2nd ed.)

Voprosy Ekonomiki ◽

10.32609/0042-8736-2014-12-147-153 ◽

2014 ◽

pp. 147-153

Author(s):

P. Orekhovsky

Keyword(s):

Economic Theory ◽

Economic Development ◽

Structural Analysis ◽

Increasing Returns ◽

The Other ◽

Static Theory ◽

Poor Countries ◽

Historical School ◽

Socio Economic Development ◽

The Relationship

The review outlines the connection between E. Reinert’s book and the tradition of structural analysis. The latter allows for the heterogeneity of industries and sectors of the economy, as well as for the effects of increasing and decreasing returns. Unlike the static theory of international trade inherited from the Ricardian analysis of comparative advantage, this approach helps identify the relationship between trade, production, income and population growth. Reinert rehabilitates the “other canon” of economic theory associated with the mercantilist tradition, F. Liszt and the German historical school, as well as a reconside ration of A. Marshall’s analysis of increasing returns. Empirical illustrations given in the book reveal clear parallels with the path of Russian socio-economic development in the last twenty years.

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Nglyc: A Random Forest Method for Prediction of N-Glycosylation Sites in Eukaryotic Protein Sequence

Protein and Peptide Letters ◽

10.2174/0929866526666191002111404 ◽

2020 ◽

Vol 27 (3) ◽

pp. 178-186 ◽

Cited By ~ 2

Author(s):

Ganesan Pugalenthi ◽

Varadharaju Nithya ◽

Kuo-Chen Chou ◽

Govindaraju Archunan

Keyword(s):

Random Forest ◽

Protein Sequence ◽

Glycosylation Site ◽

Computational Method ◽

The Other ◽

Eukaryotic Protein ◽

Random Forest Method ◽

Glycosylation Sites ◽

Human And Mouse ◽

Better Than

Background: N-Glycosylation is one of the most important post-translational mechanisms in eukaryotes. N-glycosylation predominantly occurs in N-X-[S/T] sequon where X is any amino acid other than proline. However, not all N-X-[S/T] sequons in proteins are glycosylated. Therefore, accurate prediction of N-glycosylation sites is essential to understand Nglycosylation mechanism. Objective: In this article, our motivation is to develop a computational method to predict Nglycosylation sites in eukaryotic protein sequences. Methods: In this article, we report a random forest method, Nglyc, to predict N-glycosylation site from protein sequence, using 315 sequence features. The method was trained using a dataset of 600 N-glycosylation sites and 600 non-glycosylation sites and tested on the dataset containing 295 Nglycosylation sites and 253 non-glycosylation sites. Nglyc prediction was compared with NetNGlyc, EnsembleGly and GPP methods. Further, the performance of Nglyc was evaluated using human and mouse N-glycosylation sites. Results: Nglyc method achieved an overall training accuracy of 0.8033 with all 315 features. Performance comparison with NetNGlyc, EnsembleGly and GPP methods shows that Nglyc performs better than the other methods with high sensitivity and specificity rate. Conclusion: Our method achieved an overall accuracy of 0.8248 with 0.8305 sensitivity and 0.8182 specificity. Comparison study shows that our method performs better than the other methods. Applicability and success of our method was further evaluated using human and mouse N-glycosylation sites. Nglyc method is freely available at https://github.com/bioinformaticsML/ Ngly.

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Analysis of Oncogene Protein Structure Using Small World Network Concept

Current Bioinformatics ◽

10.2174/1574893614666191113143840 ◽

2020 ◽

Vol 15 (7) ◽

pp. 732-740

Author(s):

Neetu Kumari ◽

Anshul Verma

Keyword(s):

Amino Acids ◽

Protein Structure ◽

Degree Distribution ◽

Protein Structures ◽

Small World ◽

Extreme Condition ◽

Centrality Measures ◽

Small World Network ◽

Network Concept ◽

Oncogene Protein

Background: The basic building block of a body is protein which is a complex system whose structure plays a key role in activation, catalysis, messaging and disease states. Therefore, careful investigation of protein structure is necessary for the diagnosis of diseases and for the drug designing. Protein structures are described at their different levels of complexity: primary (chain), secondary (helical), tertiary (3D), and quaternary structure. Analyzing complex 3D structure of protein is a difficult task but it can be analyzed as a network of interconnection between its component, where amino acids are considered as nodes and interconnection between them are edges. Objective: Many literature works have proven that the small world network concept provides many new opportunities to investigate network of biological systems. The objective of this paper is analyzing the protein structure using small world concept. Methods: Protein is analyzed using small world network concept, specifically where extreme condition is having a degree distribution which follows power law. For the correct verification of the proposed approach, dataset of the Oncogene protein structure is analyzed using Python programming. Results: Protein structure is plotted as network of amino acids (Residue Interaction Graph (RIG)) using distance matrix of nodes with given threshold, then various centrality measures (i.e., degree distribution, Degree-Betweenness correlation, and Betweenness-Closeness correlation) are calculated for 1323 nodes and graphs are plotted. Conclusion: Ultimately, it is concluded that there exist hubs with higher centrality degree but less in number, and they are expected to be robust toward harmful effects of mutations with new functions.

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Diversity of pathogenic Pseudomonas isolated from citrus in Tunisia

AMB Express ◽

10.1186/s13568-020-01134-z ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Maroua Oueslati ◽

Magdalena Mulet ◽

Mohamed Zouaoui ◽

Charlotte Chandeysson ◽

Jorge Lalucat ◽

...

Keyword(s):

Phylogenetic Analysis ◽

Pseudomonas Syringae ◽

Ice Nucleation ◽

Phylogenetic Study ◽

Future Studies ◽

Citrus Orchards ◽

First Time ◽

New Cultivars

Abstract The damages observed in Tunisian citrus orchards have prompted studies on the Pseudomonas spp. responsible for blast and black pit. Prospective orchards between 2015 and 2017 showed that the diseases rapidly spread geographically and to new cultivars. A screening of Pseudomonas spp. isolated from symptomatic trees revealed their wide diversity according to phylogenetic analysis of their housekeeping rpoD and cts genes. The majority of strains were affiliated to Pseudomonas syringae pv. syringae (Phylogroup PG02b), previously described in Tunisia. However, they exhibited various BOX-PCR fingerprints and were not clonal. This work demonstrated, for the first time in Tunisia, the involvement of Pseudomonas cerasi (PG02a) and Pseudomonas congelans (PG02c). The latter did not show significant pathogenicity on citrus, but was pathogenic on cantaloupe and active for ice nucleation that could play a role in the disease. A comparative phylogenetic study of citrus pathogens from Iran, Montenegro and Tunisia revealed that P. syringae (PG02b) strains are closely related but again not clonal. Interestingly P. cerasi (PG02a) was isolated in two countries and seems to outspread. However, its role in the diseases is not fully understood and it should be monitored in future studies. The diversity of pathogenic Pseudomonas spp. and the extension of the diseases highlight that they have become complex and synergistic. It opens questions about which factors favor diseases and how to fight against them efficiently and with sustainable means.

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Amino Acids 1055 to 1192 in the S2 Region of Severe Acute Respiratory Syndrome Coronavirus S Protein Induce Neutralizing Antibodies: Implications for the Development of Vaccines and Antiviral Agents

Journal of Virology ◽

10.1128/jvi.79.6.3289-3296.2005 ◽

2005 ◽

Vol 79 (6) ◽

pp. 3289-3296 ◽

Cited By ~ 59

Author(s):

Choong-Tat Keng ◽

Aihua Zhang ◽

Shuo Shen ◽

Kuo-Ming Lip ◽

Burtram C. Fielding ◽

...

Keyword(s):

Amino Acids ◽

Severe Acute Respiratory Syndrome ◽

Viral Entry ◽

Neutralizing Antibodies ◽

Antiviral Agents ◽

Host Cells ◽

Heptad Repeat ◽

Antigenic Determinants ◽

Amino Acid Residues ◽

S Protein

ABSTRACT The spike (S) protein of the severe acute respiratory syndrome coronavirus (SARS-CoV) interacts with cellular receptors to mediate membrane fusion, allowing viral entry into host cells; hence it is recognized as the primary target of neutralizing antibodies, and therefore knowledge of antigenic determinants that can elicit neutralizing antibodies could be beneficial for the development of a protective vaccine. Here, we expressed five different fragments of S, covering the entire ectodomain (amino acids 48 to 1192), as glutathione S-transferase fusion proteins in Escherichia coli and used the purified proteins to raise antibodies in rabbits. By Western blot analysis and immunoprecipitation experiments, we showed that all the antibodies are specific and highly sensitive to both the native and denatured forms of the full-length S protein expressed in virus-infected cells and transfected cells, respectively. Indirect immunofluorescence performed on fixed but unpermeabilized cells showed that these antibodies can recognize the mature form of S on the cell surface. All the antibodies were also able to detect the maturation of the 200-kDa form of S to the 210-kDa form by pulse-chase experiments. When the antibodies were tested for their ability to inhibit SARS-CoV propagation in Vero E6 culture, it was found that the anti-SΔ10 antibody, which was targeted to amino acid residues 1029 to 1192 of S, which include heptad repeat 2, has strong neutralizing activities, suggesting that this region of S carries neutralizing epitopes and is very important for virus entry into cells.

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Phylogenetic analysis and predicted functional effect of protein mutations of E6 and E7 HPV16 strains isolated in Indonesia

Medical Journal of Indonesia ◽

10.13181/mji.v24i4.1197 ◽

2015 ◽

Vol 24 (4) ◽

pp. 197-205

Author(s):

Dwi Wulandari ◽

Lisnawati Rachmadi ◽

Tjahjani M. Sudiro

Keyword(s):

Amino Acids ◽

Phylogenetic Analysis ◽

Amino Acid ◽

Asian American ◽

Protein Function ◽

Single Amino Acid ◽

Hpv16 E6 ◽

E6 And E7 ◽

Neutral Mutations

Background: E6 and E7 are oncoproteins of HPV16. Natural amino acid variation in HPV16 E6 can alter its carcinogenic potential. The aim of this study was to analyze phylogenetically E6 and E7 genes and proteins of HPV16 from Indonesia and predict the effects of single amino acid substitution on protein function. This analysis could be used to reduce time, effort, and research cost as initial screening in selection of protein or isolates to be tested in vitro or in vivo.Methods: In this study, E6 and E7 gene sequences were obtained from 12 samples of Indonesian isolates, which were compared with HPV16R (prototype) and 6 standard isolates in the category of European (E), Asian (As), Asian-American (AA), African-1 (Af-1), African-2 (Af-2), and North American (NA) branch from Genbank. Bioedit v.7.0.0 was used to analyze the composition and substitution of single amino acids. Phylogenetic analysis of E6 and E7 genes and proteins was performed using Clustal X (1.81) and NJPLOT softwares. Effects of single amino acid substitutions on protein function of E6 and E7 were analysed by SNAP.Results: Java variants and isolate ui66* belonged to European branch, while the others belonged to Asian and African branches. Twelve changes of amino acids were found in E6 and one in E7 proteins. SNAP analysis showed two non neutral mutations, i.e. R10I and C63G in E6 proteins. R10I mutations were found in Af-2 genotype (AF472509) and Indonesian isolates (Af2*), while C63G mutation was found only in Af2*.Conclusion: E6 proteins of HPV16 variants were more variable than E7. SNAP analysis showed that only E6 protein of African-2 branch had functional differences compared to HPV16R.

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Dreams of Truck Drivers: A Test of the Continuity Hypothesis of Dreaming

Imagination Cognition and Personality ◽

10.2190/578d-mlha-78r2-htnw ◽

2005 ◽

Vol 25 (2) ◽

pp. 179-186 ◽

Cited By ~ 2

Author(s):

Michael Schredl ◽

Arthur Funkhouser ◽

Nicole Arn

Keyword(s):

Empirical Studies ◽

Truck Drivers ◽

The Other ◽

Continuity Hypothesis ◽

Future Studies ◽

Daytime Activity ◽

Close Relationship ◽

The One ◽

Dream Emotions ◽

The Relationship

Empirical studies largely support the continuity hypothesis of dreaming. The present study investigated the frequency and emotional tone of dreams of truck drivers. On the one hand, the findings of the present study partly support the continuity regarding the time spent with driving/being in the truck and driving dreams and, on the other hand, a close relationship was found between daytime mood (feelings of stress, job satisfaction) and dream emotions, i.e., different dream characteristics were affected by different aspects of daytime activity. The results, thus, indicate that it is necessary to define very clearly how this continuity is to be conceptualized. The approach of formulating a mathematical model (cf. [1]) should be adopted in future studies in order to specify the factors and their magnitude in the relationship between waking and dreaming.

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