Browse
Submit Data
Databases
API
Help

Dataset Information

15 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Understanding the mutational frequency in SARS-CoV-2 proteome using structural features.

ABSTRACT: The prolonged transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in the human population has led to demographic divergence and the emergence of several location-specific clusters of viral strains. Although the effect of mutation(s) on severity and survival of the virus is still unclear, it is evident that certain sites in the viral proteome are more/less prone to mutations. In fact, millions of SARS-CoV-2 sequences collected all over the world have provided us a unique opportunity to understand viral protein mutations and develop novel computational approaches to predict mutational patterns. In this study, we have classified the mutation sites into low and high mutability classes based on viral isolates count containing mutations. The physicochemical features and structural analysis of the SARS-CoV-2 proteins showed that features including residue type, surface accessibility, residue bulkiness, stability and sequence conservation at the mutation site were able to classify the low and high mutability sites. We further developed machine learning models using above-mentioned features, to predict low and high mutability sites at different selection thresholds (ranging 5-30% of topmost and bottommost mutated sites) and observed the improvement in performance as the selection threshold is reduced (prediction accuracy ranging from 65 to 77%). The analysis will be useful for early detection of variants of concern for the SARS-CoV-2, which can also be applied to other existing and emerging viruses for another pandemic prevention.

SUBMITTER: Rawat P

PROVIDER: S-EPMC9173821 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

A rigorous framework for detecting SARS-CoV-2 spike protein mutational ensemble from genomic and structural features.

Project description:The recent release of SARS-CoV-2 genomic data from several countries has provided clues into the potential antigenic drift of the coronavirus population. In particular, the genomic instability observed in the spike protein necessitates immediate action and further exploration in the context of viral-host interactions. By temporally tracking 527,988 SARS-CoV-2 genomes, we identified invariant and hypervariable regions within the spike protein. We evaluated combination of mutations from SARS-CoV-2 lineages and found that maximum number of lineage-defining mutations were present in the N-terminal domain (NTD). Based on mutant 3D-structural models of known Variants of Concern (VOCs), we found that structural properties such as accessibility, secondary structural type, and intra-protein interactions at local mutation sites are greatly altered. Further, we observed significant differences between intra-protein networks of wild-type and Delta mutant, with the latter showing dense intra-protein contacts. Extensive molecular dynamics simulations of D614G mutant spike structure with hACE2 further revealed dynamic features with 47.7% of mutations mapping on flexible regions of spike protein. Thus, we propose that significant changes within spike protein structure have occurred that may impact SARS-CoV-2 pathogenesis, and repositioning of vaccine candidates is required to contain the spread of COVID-19 pathogen.

| S-EPMC8590475 | biostudies-literature

Mutational analysis of structural proteins of SARS-CoV-2.

Project description:SARS-CoV-2 transmissibility is higher than that of other human coronaviruses; therefore, it poses a threat to the populated communities. We investigated mutations among envelope (E), membrane (M), and spike (S) proteins from different isolates of SARS-CoV-2 and plausible signaling influenced by mutated virus in a host. We procured updated protein sequences from the NCBI virus database. Mutations were analyzed in the retrieved sequences of the viral proteins through multiple sequence alignment. Additionally, the data was subjected to ScanPROSITE to analyse if the mutations generated a relevant sequence for host signaling. Unique mutations in E, M, and S proteins resulted in modification sites like PKC phosphorylation and N-myristoylation sites. Based on structural analysis, our study revealed that the D614G mutation in the S protein diminished the interaction with T859 and K854 of adjacent chains. Moreover, the S protein of SARS-CoV-2 consists of an Arg-Gly-Asp (RGD) tripeptide sequence, which could potentially interact with various members of integrin family receptors. RGD sequence in S protein might aid in the initial virus attachment. We speculated crucial host pathways which the mutated isolates of SARS-CoV-2 may alter like PKC, Src, and integrin mediated signaling pathways. PKC signaling is known to influence the caveosome/raft pathway which is critical for virus entry. Additionally, the myristoylated proteins might activate NF-κB, a master molecule of inflammation. Thus the mutations may contribute to the disease pathogenesis and distinct lung pathophysiological changes. Further the frequently occurring mutations in the protein can be studied for possible therapeutic interventions.

| S-EPMC7980187 | biostudies-literature

Understanding protection from SARS-CoV-2 using metabolomics.

Project description:The COVID-19 pandemic is still raging in most countries. Although the recent mass vaccination campaign has opened a new chapter in the battle against SARS-CoV-2, the world is still far from herd immunity. There is an urgent need to identify healthy people at high risk of contracting COVID-19, as well as supplements and nutraceuticals that can reduce the risk of infection or mitigate symptoms. In the present study, a metabolic phenotype that could protect individuals from SARS-CoV-2 infection or predispose them to developing COVID-19 was investigated. Untargeted metabolomics was performed on serum samples collected from 51 healthcare workers who were in good health at the beginning of the COVID-19 outbreak in Italy, and who were later exposed to the same risk of developing COVID-19. Half of them developed COVID-19 within three weeks of the blood collection. Our results demonstrate the presence of a specific signature associated with protection from SARS-CoV-2. Circulating monolaurin, which has well-known antiviral and antibacterial properties, was higher in protected subjects, suggesting a potential defensive role against SARS-CoV-2 infection; thus, dietary supplements could boost the immune system against this infection. In addition, our data demonstrate that people with higher levels of cholesterol are at higher risk of developing COVID-19. The present study demonstrates that metabolomics can be of great help for developing personalized medicine and for supporting public healthcare strategies. Studies with larger cohorts of subjects are necessary to confirm our findings.

| S-EPMC8257707 | biostudies-literature

An integrated understanding of the evolutionary and structural features of the SARS-CoV-2 spike receptor binding domain (RBD).

Project description:Conventional drug development strategies typically use pocket in protein structures as drug-target sites. They overlook the plausible effects of protein evolvability and resistant mutations on protein structure which in turn may impair protein-drug interaction. In this study, we used an integrated evolution and structure guided strategy to develop potential evolutionary-escape resistant therapeutics using receptor binding domain (RBD) of SARS-CoV-2 spike-protein/S-protein as a model. Deploying an ensemble of sequence space exploratory tools including co-evolutionary analysis and deep mutational scans we provide a quantitative insight into the evolutionarily constrained subspace of the RBD sequence-space. Guided by molecular simulation and structure network analysis we highlight regions inside the RBD, which are critical for providing structural integrity and conformational flexibility. Using fuzzy C-means clustering we combined evolutionary and structural features of RBD and identified a critical region. Subsequently, we used computational drug screening using a library of 1615 small molecules and identified one lead molecule, which is expected to target the identified region, critical for evolvability and structural stability of RBD. This integrated evolution-structure guided strategy to develop evolutionary-escape resistant lead molecules have potential general applications beyond SARS-CoV-2.

| S-EPMC9278002 | biostudies-literature

Structural understanding of SARS-CoV-2 virus entry to host cells.

Project description:Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major global health concern associated with millions of fatalities worldwide. Mutant variants of the virus have further exacerbated COVID-19 mortality and infection rates, emphasizing the urgent need for effective preventive strategies. Understanding the viral infection mechanism is crucial for developing therapeutics and vaccines. The entry of SARS-CoV-2 into host cells is a key step in the infection pathway and has been targeted for drug development. Despite numerous reviews of COVID-19 and the virus, there is a lack of comprehensive reviews focusing on the structural aspects of viral entry. In this review, we analyze structural changes in Spike proteins during the entry process, dividing the entry process into prebinding, receptor binding, proteolytic cleavage, and membrane fusion steps. By understanding the atomic-scale details of viral entry, we can better target the entry step for intervention strategies. We also examine the impacts of mutations in Spike proteins, including the Omicron variant, on viral entry. Structural information provides insights into the effects of mutations and can guide the development of therapeutics and vaccines. Finally, we discuss available structure-based approaches for the development of therapeutics and vaccines. Overall, this review provides a detailed analysis of the structural aspects of SARS-CoV-2 viral entry, highlighting its significance in the development of therapeutics and vaccines against COVID-19. Therefore, our review emphasizes the importance of structural information in combating SARS-CoV-2 infection.

| S-EPMC10683510 | biostudies-literature

SARS-CoV-2 3D database: understanding the coronavirus proteome and evaluating possible drug targets.

Project description:The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a rapidly growing infectious disease, widely spread with high mortality rates. Since the release of the SARS-CoV-2 genome sequence in March 2020, there has been an international focus on developing target-based drug discovery, which also requires knowledge of the 3D structure of the proteome. Where there are no experimentally solved structures, our group has created 3D models with coverage of 97.5% and characterized them using state-of-the-art computational approaches. Models of protomers and oligomers, together with predictions of substrate and allosteric binding sites, protein-ligand docking, SARS-CoV-2 protein interactions with human proteins, impacts of mutations, and mapped solved experimental structures are freely available for download. These are implemented in SARS CoV-2 3D, a comprehensive and user-friendly database, available at https://sars3d.com/. This provides essential information for drug discovery, both to evaluate targets and design new potential therapeutics.

| S-EPMC7929435 | biostudies-literature

Comparative mutational analysis of SARS-CoV-2 isolates from Pakistan and structural-functional implications using computational modelling and simulation approaches.

Project description:SARS-CoV-2, an RNA virus, has been prone to high mutations since its first emergence in Wuhan, China, and throughout its spread. Its genome has been sequenced continuously by many countries, including Pakistan, but the results vary. Understanding its genomic patterns and connecting them with phenotypic features will help in devising therapeutic strategies. Thus, in this study, we explored the mutation landscape of 250 Pakistani isolates of SARS-CoV-2 genomes to check the genome diversity and examine the impact of these mutations on protein stability and viral pathogenesis in comparison with a reference sequence (Wuhan NC 045512.2). Our results revealed that structural proteins mainly exhibit more mutations than others in the Pakistani isolates; in particular, the nucleocapsid protein is highly mutated. In comparison, the spike protein is the most mutated protein globally. Furthermore, nsp12 was found to be the most mutated NSP in the Pakistani isolates and worldwide. Regarding accessory proteins, ORF3A is the most mutated in the Pakistani isolates, whereas ORF8 is highly mutated in world isolates. These mutations decrease the structural stability of their proteins and alter different biological pathways. Molecular docking, the dissociation constant (KD), and MM/GBSA analysis showed that mutations in the S protein alter its binding with ACE2. The spike protein mutations D614G-S943T-V622F (-75.17 kcal/mol), D614G-Q677H (-75.78 kcal/mol), and N74K-D614G (-73.84 kcal/mol) exhibit stronger binding energy than the wild type (-66.34 kcal/mol), thus increasing infectivity. Furthermore, the simulation results strongly corroborated the predicted protein servers. Our analysis findings also showed that E, M, ORF6, ORF7A, ORF7B, and ORF10 are the most stable coding genes; they may be suitable targets for vaccine and drug development.

| S-EPMC8709794 | biostudies-literature

Structures from "Engineering Neutralizing SARS-CoV Antibodies to Bind SARS-CoV-2"

Project description: Not available

| S-BSST379 | biostudies-other

Structural conservation among variants of the SARS-CoV-2 spike postfusion bundle

Project description: Not available

| EMPIAR-10999 | biostudies-other

Identifying Structural Features of Nucleotide Analogues to Overcome SARS-CoV-2 Exonuclease Activity

Project description:With the recent global spread of new SARS-CoV-2 variants, there remains an urgent need to develop effective and variant-resistant oral drugs. Recently, we reported in vitro results validating the use of combination drugs targeting both the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) and proofreading exonuclease (ExoN) as potential COVID-19 therapeutics. For the nucleotide analogues to be efficient SARS-CoV-2 inhibitors, two properties are required: efficient incorporation by RdRp and substantial resistance to excision by ExoN. Here, we have selected and evaluated nucleotide analogues with a variety of structural features for resistance to ExoN removal when they are attached at the 3′ RNA terminus. We found that dideoxynucleotides and other nucleotides lacking both 2′- and 3′-OH groups were most resistant to ExoN excision, whereas those possessing both 2′- and 3′-OH groups were efficiently removed. We also found that the 3′-OH group in the nucleotide analogues was more critical than the 2′-OH for excision by ExoN. Since the functionally important sequences in Nsp14/10 are highly conserved among all SARS-CoV-2 variants, these identified structural features of nucleotide analogues offer invaluable insights for designing effective RdRp inhibitors that can be simultaneously efficiently incorporated by the RdRp and substantially resist ExoN excision. Such newly developed RdRp terminators would be good candidates to evaluate their ability to inhibit SARS-CoV-2 in cell culture and animal models, perhaps combined with additional exonuclease inhibitors to increase their overall effectiveness.

| S-EPMC9324094 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data