A database of six eukaryotic hypothetical genes and proteins.
Ontology highlight
ABSTRACT:
SUBMITTER: Adinarayana KP
PROVIDER: S-EPMC3089888 | biostudies-other | 2011 Apr
REPOSITORIES: biostudies-other
Publications
A database of six eukaryotic hypothetical genes and proteins.
Adinarayana Katika Prabhakara Surya KP Sravani Tanuka Sai TS Hareesh Chamarthi C
Bioinformation 20110422 3
<h4>Unlabelled</h4>Assigning functions to proteins of unknown function is of considerable interest to the proteomic researchers as the genes encoding them are conserved over various species. Here, we describe HypoDB, a database of hypothetical genes and proteins in six eukaryotes. The database was collected and organized based on the number of entries in each chromosome with few annotations. Hypothetical protein database contains information related to gene and protein sequences, chromosome numb ...[more]
Similar Datasets
Project description:Originating from COMPEL, the TRANSCompel database emphasizes the key role of specific interactions between transcription factors binding to their target sites providing specific features of gene regulation in a particular cellular content. Composite regulatory elements contain two closely situated binding sites for distinct transcription factors and represent minimal functional units providing combinatorial transcriptional regulation. Both specific factor--DNA and factor--factor interactions contribute to the function of composite elements (CEs). Information about the structure of known CEs and specific gene regulation achieved through such CEs appears to be extremely useful for promoter prediction, for gene function prediction and for applied gene engineering as well. Each database entry corresponds to an individual CE within a particular gene and contains information about two binding sites, two corresponding transcription factors and experiments confirming cooperative action between transcription factors. The COMPEL database, equipped with the search and browse tools, is available at http://www.gene-regulation.com/pub/databases.html#transcompel. Moreover, we have developed the program CATCH for searching potential CEs in DNA sequences. It is freely available as CompelPatternSearch at http://compel.bionet.nsc.ru/FunSite/CompelPatternSearch.html.
| S-EPMC99108 | biostudies-literature
Project description:Eukaryotic nucleic acid binding protein database (ENPD, http://qinlab.sls.cuhk.edu.hk/ENPD/) is a library of nucleic acid binding proteins (NBPs) and their functional information. NBPs such as DNA binding proteins (DBPs), RNA binding proteins (RBPs), and DNA and RNA binding proteins (DRBPs) are involved in every stage of gene regulation through their interactions with DNA and RNA. Due to the importance of NBPs, the database was constructed based on manual curation and a newly developed pipeline utilizing both sequenced transcriptomes and genomes. In total the database has recorded 2.8 million of NBPs and their binding motifs from 662 NBP families and 2423 species, constituting the largest NBP database. ENPD covers evolutionarily important lineages which have never been included in the previous NBP databases, while lineage-specific NBP family expansions were also found. ENPD also focuses on the involvements of DBPs, RBPs and DRBPs in non-coding RNA (ncRNA) mediated gene regulation. The predicted and experimentally validated targets of NBPs have both been recorded and manually curated in ENPD, linking the interactions between ncRNAs, DNA regulatory elements and NBPs in gene regulation. This database provides key resources for the scientific community, laying a solid foundation for future gene regulatory studies from both functional and evolutionary perspectives.
| S-EPMC6324002 | biostudies-literature
Project description:Essential genes are key elements for organisms to maintain their living. Building databases that store essential genes in the form of homologous clusters, rather than storing them as a singleton, can provide more enlightening information such as the general essentiality of homologous genes in multiple organisms. In 2013, the first database to store prokaryotic essential genes in clusters, CEG (Clusters of Essential Genes), was constructed. Afterward, the amount of available data for essential genes increased by a factor >3 since the last revision. Herein, we updated CEG to version 2, including more prokaryotic essential genes (from 16 gene datasets to 29 gene datasets) and newly added eukaryotic essential genes (nine species), specifically the human essential genes of 12 cancer cell lines. For prokaryotes, information associated with drug targets, such as protein structure, ligand-protein interaction, virulence factor and matched drugs, is also provided. Finally, we provided the service of essential gene prediction for both prokaryotes and eukaryotes. We hope our updated database will benefit more researchers in drug targets and evolutionary genomics. Database URL: http://cefg.uestc.cn/ceg.
| S-EPMC7731928 | biostudies-literature
Project description:To dissect the molecular mechanism of NCBP function in the context of P. xylostella resistance, we performed a transcriptome deep sequencing (RNA-seq) analysis.
2022-12-21 | GSE161940 | GEO
Project description:Scrub typhus also known as bush typhus is a disease with symptoms similar to Chikungunya infection. It is caused by a gram-negative bacterium Orientia tsutsugamushi which resides in its vertebrate host, Mites. The genome of Orientia tsutsugamushi str. Karp encodes for 1,563 proteins, of which 344 are characterized as hypothetical ones. In the present study, we tried to identify the probable functions of these 344 hypothetical proteins (HPs). All the characterized hypothetical proteins (HPs) belong to the various protein classes like enzymes, transporters, binding proteins, metabolic process and catalytic activity and kinase activity. These hypothetical proteins (HPs) were further analyzed for virulence factors with 62 proteins identified as the most virulent proteins among these hypothetical proteins (HPs). In addition, we studied the protein sequence similarity network for visualizing functional trends across protein superfamilies from the context of sequence similarity and it shows great potential for generating testable hypotheses about protein structure-function relationships. Furthermore, we calculated toplogical properties of the network and found them to obey network power law distributions showing a fractal nature. We also identifed two highly interconnected modules in the main network which contained five hub proteins (KJV55465, KJV56211, KJV57212, KJV57203 and KJV57216) having 1.0 clustering coefficient. The structural modeling (2D and 3D structure) of these five hub proteins was carried out and the catalytic site essential for its functioning was analyzed. The outcome of the present study may facilitate a better understanding of the mechanism of virulence, pathogenesis, adaptability to host and up-to-date annotations will make unknown genes easy to identify and target for experimentation. The information on the functional attributes and virulence characteristic of these hypothetical proteins (HPs) are envisaged to facilitate effective development of novel antibacterial drug targets of Orientia tsutsugamushi.
| S-EPMC6838952 | biostudies-literature
Project description:The Eukaryotic Promoter Database (EPD) is an annotated non-redundant collection of eukaryotic POL II promoters for which the transcription start site has been determined experimentally. Access to promoter sequences is provided by pointers to positions in nucleotide sequence entries. The annotation part of an entry includes a description of the initiation site mapping data, exhaustive cross-references to the EMBL nucleotide sequence database, SWISS-PROT, TRANSFAC and other databases, as well as bibliographic references. EPD is structured in a way that facilitates dynamic extraction of biologically meaningful promoter subsets for comparative sequence analysis. WWW-based interfaces have been developed that enable the user to view EPD entries in different formats, to select and extract promoter sequences according to a variety of criteria, and to navigate to related databases exploiting different cross-references. The EPD web site also features yearly updated base frequency matrices for major eukaryotic promoter elements. EPD can be accessed at http://www.epd.isb-sib.ch
| S-EPMC102462 | biostudies-literature
Project description:Leishmaniasis is a parasitic disease caused by the protozoan Leishmania, which is active in two broad forms namely, Visceral Leishmaniasis (VL or Kala Azar) and Cutaneous Leishmaniasis (CL). The disease is most prevalent in the tropical regions and poses a threat to over 70 countries across the globe. About 200 million people are estimated to be at risk of developing VL in the Indian subcontinent, and this refers to around 67% of the global VL disease burden. The Indian state of Bihar alone accounts for 50% of the total VL cases. While no vaccination exists, several pentavalent antimonials and drugs like Paromomycin, Amphotericin, Miltefosine etc. are used in the treatment of Leishmaniasis. However, due to their low efficacies and the resistance developed by the bug to these medications, there is an urgent need to look into newer species specific targets. The proteome information available suggests that among the 7960 proteins in Leishmania donavani, a staggering 65% remains classified as a hypothetical uncharacterized set. In this background, we have attempted to assign probable functions to these hypothetical sequences present in this parasite, to explore their plausible roles as druggable receptors. Thus, putative functions have been defined to 105 hypothetical proteins, which exhibited a GO term correlation and PFAM domain coverage of more than 50% over the query sequence length. Of these, 27 sequences were found to be associated with a reference pathway in KEGG as well. Further, using homology approaches, four pathways viz., Ubiquinone biosynthesis, Fatty acid elongation in Mitochondria, Fatty Acid Elongation in ER and Seleno-cysteine Metabolism have been reconstructed. In addition, 7 new putative essential genes have been mined with the help of Eukaryotic Database of Essential Genes (DEG). All these information related to pathways and essential genes indeed show promise for exploiting the select molecules as potential therapeutic targets.
| S-EPMC4144268 | biostudies-literature
Project description:Helicobacter pylori (H. pylori) have a unique ability to survive in extreme acidic environments and to colonize the gastric mucosa. It can cause diverse gastric diseases such as peptic ulcers, chronic gastritis, mucosa-associated lymphoid tissue (MALT) lymphoma, gastric cancer, etc. Based on genomic research of H. pylori, over 1600 genes have been functionally identified so far. However, H. pylori possess some genes that are uncharacterized since: (i) the gene sequences are quite new; (ii) the function of genes have not been characterized in any other bacterial systems; and (iii) sometimes, the protein that is classified into a known protein based on the sequence homology shows some functional ambiguity, which raises questions about the function of the protein produced in H. pylori. Thus, there are still a lot of genes to be biologically or biochemically characterized to understand the whole picture of gene functions in the bacteria. In this regard, knowledge on the 3D structure of a protein, especially unknown or hypothetical protein, is frequently useful to elucidate the structure-function relationship of the uncharacterized gene product. That is, a structural comparison with known proteins provides valuable information to help predict the cellular functions of hypothetical proteins. Here, we show the 3D structures of some hypothetical proteins determined by NMR spectroscopy and X-ray crystallography as a part of the structural genomics of H. pylori. In addition, we show some successful approaches of elucidating the function of unknown proteins based on their structural information.
| S-EPMC3397514 | biostudies-literature
Project description:Selenoproteins are a diverse group of proteins usually misidentified and misannotated in sequence databases. The presence of an in-frame UGA (stop) codon in the coding sequence of selenoprotein genes precludes their identification and correct annotation. The in-frame UGA codons are recoded to cotranslationally incorporate selenocysteine, a rare selenium-containing amino acid. The development of ad hoc experimental and, more recently, computational approaches have allowed the efficient identification and characterization of the selenoproteomes of a growing number of species. Today, dozens of selenoprotein families have been described and more are being discovered in recently sequenced species, but the correct genomic annotation is not available for the majority of these genes. SelenoDB is a long-term project that aims to provide, through the collaborative effort of experimental and computational researchers, automatic and manually curated annotations of selenoprotein genes, proteins and SECIS elements. Version 1.0 of the database includes an initial set of eukaryotic genomic annotations, with special emphasis on the human selenoproteome, for immediate inspection by selenium researchers or incorporation into more general databases. SelenoDB is freely available at http://www.selenodb.org.
| S-EPMC2238826 | biostudies-other
Project description:Linear motifs are short, evolutionarily plastic components of regulatory proteins and provide low-affinity interaction interfaces. These compact modules play central roles in mediating every aspect of the regulatory functionality of the cell. They are particularly prominent in mediating cell signaling, controlling protein turnover and directing protein localization. Given their importance, our understanding of motifs is surprisingly limited, largely as a result of the difficulty of discovery, both experimentally and computationally. The Eukaryotic Linear Motif (ELM) resource at http://elm.eu.org provides the biological community with a comprehensive database of known experimentally validated motifs, and an exploratory tool to discover putative linear motifs in user-submitted protein sequences. The current update of the ELM database comprises 1800 annotated motif instances representing 170 distinct functional classes, including approximately 500 novel instances and 24 novel classes. Several older motif class entries have been also revisited, improving annotation and adding novel instances. Furthermore, addition of full-text search capabilities, an enhanced interface and simplified batch download has improved the overall accessibility of the ELM data. The motif discovery portion of the ELM resource has added conservation, and structural attributes have been incorporated to aid users to discriminate biologically relevant motifs from stochastically occurring non-functional instances.
| S-EPMC3245074 | biostudies-literature