Database mining of plant peptide homologues.
Ontology highlight
ABSTRACT:
SUBMITTER: Yuan N
PROVIDER: S-EPMC8215471 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Plants produce a wide range of bioactive peptides as part of their innate defense mechanisms. With the explosive growth of plant-derived peptides, verifying the therapeutic function using traditional experimental methods are resources and time consuming. Therefore, it is necessary to predict the therapeutic function of plant-derived peptides more effectively and accurately with reduced waste of resources and thus expedite the development of plant peptides. We herein developed a repository of plant peptides predicted to have multiple therapeutic functions, named as MFPPDB (multi-functional plant peptide database). MFPPDB including 1,482,409 single or multiple functional plant origin therapeutic peptides derived from 121 fundamental plant species. The functional categories of these therapeutic peptides include 41 different features such as anti-bacterial, anti-fungal, anti-HIV, anti-viral, and anti-cancer. The detailed physicochemical information of these peptides was presented in functional search and physicochemical property search module, which can help users easily access the peptide information by the plant peptide species, ID, and functions, or by their peptide ID, isoelectric point, peptide sequence, and molecular weight through web-friendly interface. We further matched the predicted peptides to nine state-of-the-art curated functional peptide databases and found that at least 293,408 of the peptides possess functional potentials. Overall, MFPPDB integrated a massive number of plant peptides have single or multiple therapeutic functions, which will facilitate the comprehensive research in plant peptidomics. MFPPDB can be freely accessed through http://124.223.195.214:9188/mfppdb/index.
| S-EPMC10613858 | biostudies-literature
Project description:Meiosis is a crucial process of sexual reproduction by forming haploid gametes from diploid precursor cells. It involves 2 subsequent divisions (meiosis I and meiosis II) after one initial round of DNA replication. Homologous monocentric chromosomes are separated during the first and sister chromatids during the second meiotic division. The faithful segregation of monocentric chromosomes is realized by mono-orientation of fused sister kinetochores at metaphase I and by bi-orientation of sister kinetochores at metaphase II. Conventionally this depends on a 2-step loss of cohesion, along chromosome arms during meiosis I and at sister centromeres during meiosis II.
| S-EPMC4613655 | biostudies-other
Project description:BACKGROUND: The Pubchem Database is a large-scale resource for chemical information, containing millions of chemical compound activities derived by high-throughput screening (HTS). The ability to extract characteristic substructures from such enormous amounts of data is steadily growing in importance. Compounds with shared basic active structures (BASs) exhibiting G-protein coupled receptor (GPCR) activity and repeated dose toxicity have been mined from small datasets. However, the mining process employed was not applicable to large datasets owing to a large imbalance between the numbers of active and inactive compounds. In most datasets, one active compound will appear for every 1000 inactive compounds. Most mining techniques work well only when these numbers are similar. RESULTS: This difficulty was overcome by sampling an equal number of active and inactive compounds. The sampling process was repeated to maintain the structural diversity of the inactive compounds. An interactive KNIME workflow that enabled effective sampling and data cleaning processes was created. The application of the cascade model and subsequent structural refinement yielded the BAS candidates. Repeated sampling increased the ratio of active compounds containing these substructures. Three samplings were deemed adequate to identify all of the meaningful BASs. BASs expressing similar structures were grouped to give the final set of BASs. This method was applied to HIV integrase and protease inhibitor activities in the MDL Drug Data Report (MDDR) database and to procaspase-3 activators in the PubChem BioAssay database, yielding 14, 12, and 18 BASs, respectively. CONCLUSIONS: The proposed mining scheme successfully extracted meaningful substructures from large datasets of chemical structures. The resulting BASs were deemed reasonable by an experienced medicinal chemist. The mining itself requires about 3 days to extract BASs with a given physiological activity. Thus, the method described herein is an effective way to analyze large HTS databases.
| S-EPMC3618305 | biostudies-other
Project description:The Plant snoRNA database (http://www.scri.sari.ac.uk/plant_snoRNA/) provides information on small nucleolar RNAs from Arabidopsis and eighteen other plant species. Information includes sequences, expression data, methylation and pseudouridylation target modification sites, initial gene organization (polycistronic, single gene and intronic) and the number of gene variants. The Arabidopsis information is divided into box C/D and box H/ACA snoRNAs, and within each of these groups, by target sites in rRNA, snRNA or unknown. Alignments of orthologous genes and gene variants from different plant species are available for many snoRNA genes. Plant snoRNA genes have been given a standard nomenclature, designed wherever possible, to provide a consistent identity with yeast and human orthologues.
| S-EPMC165456 | biostudies-literature
Project description:MicroRNAs (miRNA) are approximately 21 nucleotide-long non-coding small RNAs, which function as post-transcriptional regulators in eukaryotes. miRNAs play essential roles in regulating plant growth and development. In recent years, research into the mechanism and consequences of miRNA action has made great progress. With whole genome sequence available in such plants as Arabidopsis thaliana, Oryza sativa, Populus trichocarpa, Glycine max, etc., it is desirable to develop a plant miRNA database through the integration of large amounts of information about publicly deposited miRNA data. The plant miRNA database (PMRD) integrates available plant miRNA data deposited in public databases, gleaned from the recent literature, and data generated in-house. This database contains sequence information, secondary structure, target genes, expression profiles and a genome browser. In total, there are 8433 miRNAs collected from 121 plant species in PMRD, including model plants and major crops such as Arabidopsis, rice, wheat, soybean, maize, sorghum, barley, etc. For Arabidopsis, rice, poplar, soybean, cotton, medicago and maize, we included the possible target genes for each miRNA with a predicted interaction site in the database. Furthermore, we provided miRNA expression profiles in the PMRD, including our local rice oxidative stress related microarray data (LC Sciences miRPlants_10.1) and the recently published microarray data for poplar, Arabidopsis, tomato, maize and rice. The PMRD database was constructed by open source technology utilizing a user-friendly web interface, and multiple search tools. The PMRD is freely available at http://bioinformatics.cau.edu.cn/PMRD. We expect PMRD to be a useful tool for scientists in the miRNA field in order to study the function of miRNAs and their target genes, especially in model plants and major crops.
| S-EPMC2808885 | biostudies-literature
Project description:BACKGROUND:Blood chemicals are routinely measured in clinical or preclinical research studies to diagnose diseases, assess risks in epidemiological research, or use metabolomic phenotyping in response to treatments. A vast volume of blood-related literature is available via the PubMed database for data mining. OBJECTIVES:We aimed to generate a comprehensive blood exposome database of endogenous and exogenous chemicals associated with the mammalian circulating system through text mining and database fusion. METHODS:Using NCBI resources, we retrieved PubMed abstracts, PubChem chemical synonyms, and PMC supplementary tables. We then employed text mining and PubChem crowdsourcing to associate phrases relating to blood with PubChem chemicals. False positives were removed by a phrase pattern and a compound exclusion list. RESULTS:A query to identify blood-related publications in the PubMed database yielded 1.1 million papers. Matching a total of 15 million synonyms from 6.5 million relevant PubChem chemicals against all blood-related publications yielded 37,514 chemicals and 851,999 publications records. Mapping PubChem compound identifiers to the PubMed database yielded 49,940 unique chemicals linked to 676,643 papers. Analysis of open-access metabolomics papers related to blood phrases in the PMC database yielded 4,039 unique compounds and 204 papers. Consolidating these three approaches summed up to a total of 41,474 achiral structures that were linked to 65,957 PubChem CIDs and to over 878,966 PubMed articles. We mapped these compounds to 50 databases such as those covering metabolites and pathways, governmental and toxicological databases, pharmacology resources, and bioassay repositories. In comparison, HMDB, the Human Metabolome Database, links 1,075 compounds to blood-related primary publications. CONCLUSION:This new Blood Exposome Database can be used for prioritizing chemicals for systematic reviews, developing target assays in exposome research, identifying compounds in untargeted mass spectrometry, and biological interpretation in metabolomics data. The database is available at http://bloodexposome.org. https://doi.org/10.1289/EHP4713.
| S-EPMC6794490 | biostudies-literature
Project description:BACKGROUND: Sireviruses are an ancient genus of the Copia superfamily of LTR retrotransposons, and the only one that has exclusively proliferated within plant genomes. Based on experimental data and phylogenetic analyses, Sireviruses have successfully infiltrated many branches of the plant kingdom, extensively colonizing the genomes of grass species. Notably, it was recently shown that they have been a major force in the make-up and evolution of the maize genome, where they currently occupy ~21% of the nuclear content and ~90% of the Copia population. It is highly likely, therefore, that their life dynamics have been fundamental in the genome composition and organization of a plethora of plant hosts. To assist studies into their impact on plant genome evolution and also facilitate accurate identification and annotation of transposable elements in sequencing projects, we developed MASiVEdb (Mapping and Analysis of SireVirus Elements Database), a collective and systematic resource of Sireviruses in plants. DESCRIPTION: Taking advantage of the increasing availability of plant genomic sequences, and using an updated version of MASiVE, an algorithm specifically designed to identify Sireviruses based on their highly conserved genome structure, we populated MASiVEdb (http://bat.infspire.org/databases/masivedb/) with data on 16,243 intact Sireviruses (total length >158Mb) discovered in 11 fully-sequenced plant genomes. MASiVEdb is unlike any other transposable element database, providing a multitude of highly curated and detailed information on a specific genus across its hosts, such as complete set of coordinates, insertion age, and an analytical breakdown of the structure and gene complement of each element. All data are readily available through basic and advanced query interfaces, batch retrieval, and downloadable files. A purpose-built system is also offered for detecting and visualizing similarity between user sequences and Sireviruses, as well as for coding domain discovery and phylogenetic analysis. CONCLUSION: MASiVEdb is currently the most comprehensive directory of Sireviruses, and as such complements other efforts in cataloguing plant transposable elements and elucidating their role in host genome evolution. Such insights will gradually deepen, as we plan to further improve MASiVEdb by phylogenetically mapping Sireviruses into families, by including data on fragments and solo LTRs, and by incorporating elements from newly-released genomes.
| S-EPMC3414828 | biostudies-other
Project description:Volatile organic compounds (VOCs) are small molecules that exhibit high vapor pressure under ambient conditions and have low boiling points. Although VOCs contribute only a small proportion of the total metabolites produced by living organisms, they play an important role in chemical ecology specifically in the biological interactions between organisms and ecosystems. VOCs are also important in the health care field as they are presently used as a biomarker to detect various human diseases. Information on VOCs is scattered in the literature until now; however, there is still no available database describing VOCs and their biological activities. To attain this purpose, we have developed KNApSAcK Metabolite Ecology Database, which contains the information on the relationships between VOCs and their emitting organisms. The KNApSAcK Metabolite Ecology is also linked with the KNApSAcK Core and KNApSAcK Metabolite Activity Database to provide further information on the metabolites and their biological activities. The VOC database can be accessed online.
| S-EPMC4606137 | biostudies-literature
Project description:In this article, we describe the presence of genes encoding close homologues of an endogenous plant peptide, rapid alkalinization factor (RALF), within the genomes of 26 species of phytopathogenic fungi. Members of the RALF family are key growth factors in plants, and the sequence of the RALF active region is well conserved between plant and fungal proteins. RALF1-like sequences were observed in most cases; however, RALF27-like sequences were present in the Sphaerulina musiva and Septoria populicola genomes. These two species are pathogens of poplar and, interestingly, the closest relative to their respective RALF genes is a poplar RALF27-like sequence. RALF peptides control cellular expansion during plant development, but were originally defined on the basis of their ability to induce rapid alkalinization in tobacco cell cultures. To test whether the fungal RALF peptides were biologically active in plants, we synthesized RALF peptides corresponding to those encoded by two sequenced genomes of the tomato pathogen Fusarium oxysporum f. sp. lycopersici. One of these peptides inhibited the growth of tomato seedlings and elicited responses in tomato and Nicotiana benthamiana typical of endogenous plant RALF peptides (reactive oxygen species burst, induced alkalinization and mitogen-activated protein kinase activation). Gene expression analysis confirmed that a RALF-encoding gene in F. oxysporum f. sp. lycopersici was expressed during infection on tomato. However, a subsequent reverse genetics approach revealed that the RALF peptide was not required by F. oxysporum f. sp. lycopersici for infection on tomato roots. This study has demonstrated the presence of functionally active RALF peptides encoded within phytopathogens that harbour an as yet undetermined role in plant-pathogen interactions.
| S-EPMC6638259 | biostudies-literature
Project description:BackgroundThe signal peptide plays an important role in protein targeting and protein translocation in both prokaryotic and eukaryotic cells. This transient, short peptide sequence functions like a postal address on an envelope by targeting proteins for secretion or for transfer to specific organelles for further processing. Understanding how signal peptides function is crucial in predicting where proteins are translocated. To support this understanding, we present SPdb signal peptide database http://proline.bic.nus.edu.sg/spdb, a repository of experimentally determined and computationally predicted signal peptides.ResultsSPdb integrates information from two sources (a) Swiss-Prot protein sequence database which is now part of UniProt and (b) EMBL nucleotide sequence database. The database update is semi-automated with human checking and verification of the data to ensure the correctness of the data stored. The latest release SPdb release 3.2 contains 18,146 entries of which 2,584 entries are experimentally verified signal sequences; the remaining 15,562 entries are either signal sequences that fail to meet our filtering criteria or entries that contain unverified signal sequences.ConclusionSPdb is a manually curated database constructed to support the understanding and analysis of signal peptides. SPdb tracks the major updates of the two underlying primary databases thereby ensuring that its information remains up-to-date.
| S-EPMC1276010 | biostudies-literature