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Open accessJournal ArticleDOI: 10.6026/97320630008722

Computational structural and functional analysis of hypothetical proteins of Staphylococcus aureus.

03 Aug 2012-Bioinformation (Biomedical Informatics Publishing Group)-Vol. 8, Iss: 15, pp 722-728
Abstract: Genome sequencing projects has led to an explosion of large amount of gene products in which many are of hypothetical proteins with unknown function. Analyzing and annotating the functions of hypothetical proteins is important in Staphylococcus aureus which is a pathogenic bacterium that cause multiple types of diseases by infecting various sites in humans and animals. In this study, ten hypothetical proteins of Staphylococcus aureus were retrieved from NCBI and analyzed for their structural and functional characteristics by using various bioinformatics tools and databases. The analysis revealed that some of them possessed functionally important domains and families and protein-protein interacting partners which were ABC transporter ATP-binding protein, Multiple Antibiotic Resistance (MAR) family, export proteins, Helix-Turn-helix domains, arsenate reductase, elongation factor, ribosomal proteins, Cysteine protease precursor, Type-I restriction endonuclease enzyme and plasmid recombination enzyme which might have the same functions in hypothetical proteins. The structural prediction of those proteins and binding sites prediction have been done which would be useful in docking studies for aiding in the drug discovery.

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Topics: Arsenate reductase (56%), Ribosomal protein (54%), Plasmid recombination (54%) ...read more
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Open accessJournal ArticleDOI: 10.3389/FGENE.2015.00119
Abstract: Hypothetical Proteins are the proteins that are predicted to be expressed from an open reading frame (ORF), constituting a substantial fraction of proteomes in both prokaryotes and eukaryotes. Genome projects have led to the identification of many therapeutic targets, the putative function of the protein and their interactions. In this review we have enlisted various methods. Annotation linked to structural and functional prediction of hypothetical proteins assist in the discovery of new structures and functions serving as markers and pharmacological targets for drug designing, discovery and screening. Mass spectrometry is an analytical technique for validating protein characterisation. Matrix-assisted laser desorption ionization–mass spectrometry (MALDI-MS) is an efficient analytical method. Microarrays and Protein expression profiles help understanding the biological systems through a systems-wide study of proteins and their interactions with other proteins and non-proteinaceous molecules to control complex processes in cells and tissues and even whole organism. Next generation sequencing technology accelerates multiple areas of genomics research.

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Topics: Proteome (58%), Genome project (52%), Genomics (51%)

38 Citations


Open accessJournal ArticleDOI: 10.3390/VACCINES8030423
28 Jul 2020-Vaccine
Abstract: The present study aimed to work out a peptide-based multi-epitope vaccine against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We predicted different B-cell and T-cell epitopes by using the Immune Epitopes Database (IEDB). Homology modeling of the construct was done using SWISS-MODEL and then docked with different toll-like-receptors (TLR4, TLR7, and TLR8) using PatchDock, HADDOCK, and FireDock, respectively. From the overlapped epitopes, we designed five vaccine constructs C1–C5. Based on antigenicity, allergenicity, solubility, different physiochemical properties, and molecular docking scores, we selected the vaccine construct 1 (C1) for further processing. Docking of C1 with TLR4, TLR7, and TLR8 showed striking interactions with global binding energy of −43.48, −65.88, and −60.24 Kcal/mol, respectively. The docked complex was further simulated, which revealed that both molecules remain stable with minimum RMSF. Activation of TLRs induces downstream pathways to produce pro-inflammatory cytokines against viruses and immune system simulation shows enhanced antibody production after the booster dose. In conclusion, C1 was the best vaccine candidate among all designed constructs to elicit an immune response SARS-CoV-2 and combat the coronavirus disease (COVID-19).

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Topics: Epitope (53%), Coronavirus (52%)

20 Citations


Journal ArticleDOI: 10.1007/S11274-013-1550-7
Abstract: Staphylococcus aureus (S. aureus) strains cause several diseases in humans from minor skin infections to severe lethal infections. To explore the virulence determinants of this important microorganism, two clinical isolates of methicillin susceptible S. aureus (MSSA) and methicillin resistant S. aureus (MRSA) were subjected to proteomic analysis of their extracellular products using liquid chromatography–tandem mass spectrometry. The numbers of proteins identified in MSSA and MRSA extracellular products were 168 and 261; respectively, from them 117 were shared, while 144 proteins were unique to MRSA. The shared proteins, having a higher protein score with increased number of peptide matches in MRSA over MSSA, reflect the relatively active secretory state of MRSA rather than biased analytical variances. Characteristic determinants for MRSA were identified; mostly found to play a role in the virulence. We conclude that MRSA produces distinct proteins considered as its virulence determinants and we found that the shared extracellular products are more abundant in MRSA than MSSA that supporting the high invasiveness of MRSA over MSSA in pathogenesis.

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17 Citations


Open accessJournal ArticleDOI: 10.1016/J.JIPH.2014.02.002
Shymaa Enany1Institutions (1)
Abstract: The progress in biological technologies has led to rapid accumulation of microbial genomic sequences with a vast number of uncharacterized genes. Proteins encoded by these genes are usually uncharacterized, hypothetical, and/or conserved. In Clostridium tetani (C. tetani), these proteins constitute up to 50% of the expressed proteins. In this regard, understanding the functions and the structures of these proteins is crucially important, particularly in C. tetani, which is a medically important pathogen. Here, we used a variety of bioinformatics tools and databases to analyze 10 hypothetical and conserved proteins in C. tetani. We were able to provide a detailed overview of the functional contributions of some of these proteins in several cellular functions, including (1) evolving antibiotic resistance, (2) interaction with enzymes pathways, and (3) involvement in drug transportation. Among these candidates, we postulated the involvement of one of these hypothetical proteins in the pathogenic activity of tetanus. The structural and functional prediction of these proteins should serve in uncovering and better understanding the function of C. tetani cells to ultimately discover new possible drug targets.

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Topics: Clostridium tetani (54%)

12 Citations


Open accessJournal ArticleDOI: 10.1186/S12859-018-2554-Y
Johny Ijaq1, Girik Malik2, Anuj Kumar, Partha Sarathi Das3  +4 moreInstitutions (4)
08 Jan 2019-BMC Bioinformatics
Abstract: Hypothetical proteins [HP] are those that are predicted to be expressed in an organism, but no evidence of their existence is known. In the recent past, annotation and curation efforts have helped overcome the challenge in understanding their diverse functions. Techniques to decipher sequence-structure-function relationship, especially in terms of functional modelling of the HPs have been developed by researchers, but using the features as classifiers for HPs has not been attempted. With the rise in number of annotation strategies, next-generation sequencing methods have provided further understanding the functions of HPs. In our previous work, we developed a six-point classification scoring schema with annotation pertaining to protein family scores, orthology, protein interaction/association studies, bidirectional best BLAST hits, sorting signals, known databases and visualizers which were used to validate protein interactions. In this study, we introduced three more classifiers to our annotation system, viz. pseudogenes linked to HPs, homology modelling and non-coding RNAs associated to HPs. We discuss the challenges and performance of these classifiers using machine learning heuristics with an improved accuracy from Perceptron (81.08 to 97.67), Naive Bayes (54.05 to 96.67), Decision tree J48 (67.57 to 97.00), and SMO_npolyk (59.46 to 96.67). With the introduction of three new classification features, the performance of the nine-point classification scoring schema has an improved accuracy to functionally annotate the HPs.

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11 Citations


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