A Bioinformatics Approach to Investigate Structural and Non-Structural Proteins in Human Coronaviruses.
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ABSTRACT:
SUBMITTER: Cicaloni V
PROVIDER: S-EPMC9237418 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Coronaviruses (CoVs) are causing a number of human and animal diseases because of their zoonotic nature such as Middle East respiratory syndrome (MERS), severe acute respiratory syndrome (SARS) and coronavirus disease 2019 (COVID-19). These viruses can infect respiratory, gastrointestinal, hepatic and central nervous systems of human, livestock, birds, bat, mouse, and many wild animals. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a newly emerging respiratory virus and is causing CoVID-19 with high morbidity and considerable mortality. All CoVs belong to the order Nidovirales, family Coronaviridae, are enveloped positive-sense RNA viruses, characterised by club-like spikes on their surfaces and large RNA genome with a distinctive replication strategy. Coronavirus have the largest RNA genomes (~26-32 kilobases) and their expansion was likely enabled by acquiring enzyme functions that counter the commonly high error frequency of viral RNA polymerases. Non-structural proteins (nsp) 7-16 are cleaved from two large replicase polyproteins and guide the replication and processing of coronavirus RNA. Coronavirus replicase has more or less universal activities, such as RNA polymerase (nsp 12) and helicase (nsp 13), as well as a variety of unusual or even special mRNA capping (nsp 14, nsp 16) and fidelity regulation (nsp 14) domains. Besides that, several smaller subunits (nsp 7- nsp 10) serve as essential cofactors for these enzymes and contribute to the emerging "nsp interactome." In spite of the significant progress in studying coronaviruses structural and functional properties, there is an urgent need to understand the coronaviruses evolutionary success that will be helpful to develop enhanced control strategies. Therefore, it is crucial to understand the structure, function, and interactions of coronaviruses RNA synthesizing machinery and their replication strategies.
| S-EPMC7682334 | biostudies-literature
Project description:This article is aimed at analyzing the structure and function of the spike (S) proteins of porcine enteric coronaviruses, including transmissible gastroenteritis virus (TGEV), porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV), and swine acute diarrhea syndrome coronavirus (SADS-CoV) by applying bioinformatics methods. The physical and chemical properties, hydrophilicity and hydrophobicity, transmembrane region, signal peptide, phosphorylation and glycosylation sites, epitope, functional domains, and motifs of S proteins of porcine enteric coronaviruses were predicted and analyzed through online software. The results showed that S proteins of TGEV, PEDV, SADS-CoV, and PDCoV all contained transmembrane regions and signal peptide. TGEV S protein contained 139 phosphorylation sites, 24 glycosylation sites, and 53 epitopes. PEDV S protein had 143 phosphorylation sites, 22 glycosylation sites, and 51 epitopes. SADS-CoV S protein had 109 phosphorylation sites, 20 glycosylation sites, and 43 epitopes. PDCoV S protein had 124 phosphorylation sites, 18 glycosylation sites, and 52 epitopes. Moreover, TGEV, PEDV, and PDCoV S proteins all contained two functional domains and two motifs, spike_rec_binding and corona_S2. The corona_S2 consisted of S2 subunit heptad repeat 1 (HR1) and S2 subunit heptad repeat 2 (HR2) region profiles. Additionally, SADS-CoV S protein was predicted to contain only one functional domain, the corona_S2. This analysis of the biological functions of porcine enteric coronavirus spike proteins can provide a theoretical basis for the design of antiviral drugs.
| S-EPMC8266444 | biostudies-literature
Project description:In the twenty-first century, three new human coronaviruses have been identified with known zoonotic origins: severe acute respiratory syndrome coronavirus (SARS-CoV), SARS-CoV-2, and Middle East respiratory syndrome coronavirus (MERS-CoV). SARS-CoV-2 was identified in November 2019 and is associated with an ongoing pandemic. Molecular surveillance and monitoring studies are essential for containing viral outbreaks, epidemics, and pandemics. In addition, the development and deployment of bioinformatics resources for highly pathogenic human coronaviruses are crucial for understanding the genetic and immunogenic landscape associated with these viruses. Here, we introduce an open-access, integrated resource for SARS-CoV, SARS-CoV-2, and MERS-CoV: the Human Coronaviruses Database and Analysis Resource (hCoronavirusesDB; http://hcoronaviruses.net/), which include nucleotide and protein sequence data obtained for these viruses. The database also offers a user-friendly search interface coupled with bioinformatics analytics and visualization tools. In addition, hCoronavirusesDB contains curated, experimentally validated B cell and T cell epitope data for these viruses. This resource can assist with the molecular surveillance necessary to trace virus circulation and contribute to microevolutionary studies. This application can also serve as a valuable resource for the development of rationally designed pan-coronavirus diagnostic tools, vaccines, and therapeutic agents. Database URL:http://hcoronaviruses.net/.
| S-EPMC9216473 | biostudies-literature
Project description:BackgroundLinking structural effects of mutations to functional outcomes is a major issue in structural bioinformatics, and many tools and studies have shown that specific structural properties such as stability and residue burial can be used to distinguish neutral variations and disease associated mutations.ResultsWe have investigated 39 structural properties on a set of SNPs and disease mutations from the Uniprot Knowledge Base that could be mapped on high quality crystal structures and show that none of these properties can be used as a sole classification criterion to separate the two data sets. Furthermore, we have reviewed the annotation process from mutation to result and identified the liabilities in each step.ConclusionAlthough excellent annotation results of various research groups underline the great potential of using structural bioinformatics to investigate the mechanisms underlying disease, the interpretation of such annotations cannot always be extrapolated to proteome wide variation studies. Difficulties for large-scale studies can be found both on the technical level, i.e. the scarcity of data and the incompleteness of the structural tool suites, and on the conceptual level, i.e. the correct interpretation of the results in a cellular context.
| S-EPMC2745591 | biostudies-literature
Project description:One goal of the Human Proteome Project is to identify at least one protein product for each of the ?20,000 human protein-coding genes. As of October 2014, however, there are 3564 genes (18%) that have no or insufficient evidence of protein existence (PE), as curated by neXtProt; these comprise 2647 PE2-4 missing proteins and 616 PE5 dubious protein entries. We conducted a systematic examination of the 616 PE5 protein entries using cutting-edge protein structure and function modeling methods. Compared to a random sample of high-confidence PE1 proteins, the putative PE5 proteins were found to be over-represented in the membrane and cell surface proteins and peptides fold families. Detailed functional analyses show that most PE5 proteins, if expressed, would belong to transporters and receptors localized in the plasma membrane compartment. The results suggest that experimental difficulty in identifying membrane-bound proteins and peptides could have precluded their detection in mass spectrometry and that special enrichment techniques with improved sensitivity for membrane proteins could be important for the characterization of the PE5 "dark matter" of the human proteome. Finally, we identify 66 high scoring PE5 protein entries and find that six of them were reported in recent mass spectrometry databases; an illustrative annotation of these six is provided. This work illustrates a new approach to examine the potential folding and function of the dubious proteins comprising PE5, which we will next apply to the far larger group of missing proteins comprising PE2-4.
| S-EPMC4878405 | biostudies-literature
Project description:We have developed a protocol for identifying proteins that are predisposed to bind linear epitopes on target proteins of interest. The protocol searches through the protein database for proteins (scaffolds) that are bound to peptides with sequences similar to accessible, linear epitopes on the target protein. The sequence match is considered more significant if residues calculated to be important in the scaffold-peptide interaction are present in the target epitope. The crystal structure of the scaffold-peptide complex is then used as a template for creating a model of the scaffold bound to the target epitope. This model can then be used in conjunction with sequence optimization algorithms or directed evolution methods to search for scaffold mutations that further increase affinity for the target protein. To test the applicability of this approach we targeted three disease-causing proteins: a tuberculosis virulence factor (TVF), the apical membrane antigen (AMA) from malaria, and hemagglutinin from influenza. In each case the best scoring scaffold was tested, and binders with Kds equal to 37 ?M and 50 nM for TVF and AMA, respectively, were identified. A web server (http://rosettadesign.med.unc.edu/scaffold/) has been created for performing the scaffold search process with user-defined target sequences.
| S-EPMC3601849 | biostudies-literature
Project description:Membrane-binding peripheral proteins play important roles in many biological processes, including cell signaling and membrane trafficking. Unlike integral membrane proteins, these proteins bind the membrane mostly in a reversible manner. Since peripheral proteins do not have canonical transmembrane segments, it is difficult to identify them from their amino acid sequences. As a first step toward genome-scale identification of membrane-binding peripheral proteins, we built a kernel-based machine learning protocol. Key features of known membrane-binding proteins, including electrostatic properties and amino acid composition, were calculated from their amino acid sequences and tertiary structures, which were then incorporated into the support vector machine to perform the classification. A data set of 40 membrane-binding proteins and 230 non-membrane-binding proteins was used to construct and validate the protocol. Cross-validation and holdout evaluation of the protocol showed that the accuracy of the prediction reached up to 93.7% and 91.6%, respectively. The protocol was applied to the prediction of membrane-binding properties of four C2 domains from novel protein kinases C. Although these C2 domains have 50% sequence identity, only one of them was predicted to bind the membrane, which was verified experimentally with surface plasmon resonance analysis. These results suggest that our protocol can be used for predicting membrane-binding properties of a wide variety of modular domains and may be further extended to genome-scale identification of membrane-binding peripheral proteins.
| S-EPMC2707359 | biostudies-literature
Project description:The Zika virus (ZIKV) is a mosquito-borne Flavivirus and can be transmitted through an infected mosquito bite or through human-to-human interaction by sexual activity, blood transfusion, breastfeeding, or perinatal exposure. After the 2015-2016 outbreak in Brazil, a strong link between ZIKV infection and microcephaly emerged. ZIKV specifically targets human neural progenitor cells, suggesting that proteins encoded by ZIKV bind and inactivate host cell proteins, leading to microcephaly. Here, we present a systematic annotation of interactions between human proteins and the seven non-structural ZIKV proteins corresponding to a Brazilian isolate. The interaction network was generated by combining tandem-affinity purification followed by mass spectrometry with yeast two-hybrid screens. We identified 150 human proteins, involved in distinct biological processes, as interactors to ZIKV non-structural proteins. Our interacting network is composed of proteins that have been previously associated with microcephaly in human genetic disorders and/or animal models. Further, we show that the protein inhibitor of activated STAT1 (PIAS1) interacts with NS5 and modulates its stability. This study builds on previously published interacting networks of ZIKV and genes related to autosomal recessive primary microcephaly to generate a catalog of human cellular targets of ZIKV proteins implicated in processes related to microcephaly in humans. Collectively, these data can be used as a resource for future characterization of ZIKV infection biology and help create a basis for the discovery of drugs that may disrupt the interaction and reduce the health damage to the fetus.
| S-EPMC7016862 | biostudies-literature
Project description:BackgroundThe Nonstructural Protein (NSP) 4B of Zika virus of 251 amino acids from (ZIKV/Human/POLG_ZIKVF) with accession number (A0A024B7W1), Induces the production of Endoplasmic Reticulum ER-derived membrane vesicles, which are the sites of viral replication. To understand the physical basis of how proteins fold in nature and to solve the challenge of protein structure prediction, Ab-initio and comparative modeling are crucial tools.ResultsThe systematic in silico technique, ThreaDom, had only predicted one domain (4 - 190) of NSP4B. I-TASSER, and Alphafold were ranked as the best servers for full-length 3-D protein structure predictions of NSP4B, where the predicted models were evaluated quantitatively using benchmarked metrics including C-score (-3.43), TM-score (0.77949), RMSD (2.73), and Z-score (1.561). The functional and protein binding motifs were realized using motif databases, secondary and surface accessibility predictions combined with Post-Translational Modification Sites (PTMs) prediction. Two highly conserved protein-binding motifs (Flavi NS4B and Bacillus papRprotein), together with three (PTMs) (Casein Kinase II, Myristyl site, and ASN-Glycosylation site) were predicted utilizing the Motif scan and Scanprosite servers. These patterns and PTMs were associated with NSP4B's role in triggering the development of the viral replication complex and its participation in the localization of NS3 and NS5 on the membrane. Only one hit from Structural Classification of Protein (SCOP) matched the protein sequence at positions 10 to 397 and was categorized six-hairpin glycosidases superfamily according to CATH (Class, Architecture, Topology, and Homology). Integrating this NSP4B information with the templates' SCOP and CATH annotations achieves it easier to attribute structure-function/evolution links to both previously known and recently discovered protein structures.
| S-EPMC10860876 | biostudies-literature
Project description:BACKGROUND: A new sequence independent bioinformatics approach allowing genome-wide search for proteins with similar three dimensional structures has been developed. By utilizing the numerical output of the sequence threading it establishes putative non-obvious structural similarities between proteins. When applied to the testing set of proteins with known three dimensional structures the developed approach was able to recognize structurally similar proteins with high accuracy. RESULTS: The method has been developed to identify pathogenic proteins with low sequence identity and high structural similarity to host analogues. Such protein structure relationships would be hypothesized to arise through convergent evolution or through ancient horizontal gene transfer events, now undetectable using current sequence alignment techniques. The pathogen proteins, which could mimic or interfere with host activities, would represent candidate virulence factors. The developed approach utilizes the numerical outputs from the sequence-structure threading. It identifies the potential structural similarity between a pair of proteins by correlating the threading scores of the corresponding two primary sequences against the library of the standard folds. This approach allowed up to 64% sensitivity and 99.9% specificity in distinguishing protein pairs with high structural similarity. CONCLUSION: Preliminary results obtained by comparison of the genomes of Homo sapiens and several strains of Chlamydia trachomatis have demonstrated the potential usefulness of the method in the identification of bacterial proteins with known or potential roles in virulence.
| S-EPMC434491 | biostudies-literature