Database: The Journal of Biological Databases and Curation最新文献

{"title":"Correction to: SEPDB: a database of secreted proteins.","authors":"","doi":"10.1093/database/baae024","DOIUrl":"10.1093/database/baae024","url":null,"abstract":"","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11184446/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140293078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ESKtides: a comprehensive database and mining method for ESKAPE phage-derived antimicrobial peptides.","authors":"Hongfang Wu, Rongxian Chen, Xuejian Li, Yue Zhang, Jianwei Zhang, Yanbo Yang, Jun Wan, Yang Zhou, Huanchun Chen, Jinquan Li, Runze Li, Geng Zou","doi":"10.1093/database/baae022","DOIUrl":"10.1093/database/baae022","url":null,"abstract":"<p><p>'Superbugs' have received increasing attention from researchers, such as ESKAPE bacteria (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter spp.), which directly led to about 1 270 000 death cases in 2019. Recently, phage peptidoglycan hydrolases (PGHs)-derived antimicrobial peptides were proposed as new antibacterial agents against multidrug-resistant bacteria. However, there is still a lack of methods for mining antimicrobial peptides based on phages or phage PGHs. Here, by using a collection of 6809 genomes of ESKAPE isolates and corresponding phages in public databases, based on a unified annotation process of all the genomes, PGHs were systematically identified, from which peptides were mined. As a result, a total of 12 067 248 peptides with high antibacterial activities were respectively determined. A user-friendly tool was developed to predict the phage PGHs-derived antimicrobial peptides from customized genomes, which also allows the calculation of peptide phylogeny, physicochemical properties, and secondary structure. Finally, a user-friendly and intuitive database, ESKtides (http://www.phageonehealth.cn:9000/ESKtides), was designed for data browsing, searching and downloading, which provides a rich peptide library based on ESKAPE prophages and phages. Database URL:  10.1093/database/baae022.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10965241/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140293079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to: Data sharing and ontology use among agricultural genetics, genomics, and breeding databases and resources of the Agbiodata Consortium.","authors":"","doi":"10.1093/database/baae019","DOIUrl":"10.1093/database/baae019","url":null,"abstract":"","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11184447/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140329666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ThermoPCD: a database of molecular dynamics trajectories of antibody-antigen complexes at physiologic and fever-range temperatures.","authors":"Puneet K Singh, Razvan C Stan","doi":"10.1093/database/baae015","DOIUrl":"https://doi.org/10.1093/database/baae015","url":null,"abstract":"<p><p>Progression of various cancers and autoimmune diseases is associated with changes in systemic or local tissue temperatures, which may impact current therapies. The role of fever and acute inflammation-range temperatures on the stability and activity of antibodies relevant for cancers and autoimmunity is unknown. To produce molecular dynamics (MD) trajectories of immune complexes at relevant temperatures, we used the Research Collaboratory for Structural Bioinformatics (RCSB) database to identify 50 antibody:antigen complexes of interest, in addition to single antibodies and antigens, and deployed Groningen Machine for Chemical Simulations (GROMACS) to prepare and run the structures at different temperatures for 100-500 ns, in single or multiple random seeds. MD trajectories are freely available. Processed data include Protein Data Bank outputs for all files obtained every 50 ns, and free binding energy calculations for some of the immune complexes. Protocols for using the data are also available. Individual datasets contain unique DOIs. We created a web interface, ThermoPCD, as a platform to explore the data. The outputs of ThermoPCD allow the users to relate thermally-dependent changes in epitopes:paratopes interfaces to their free binding energies, or against own experimentally derived binding affinities. ThermoPCD is a free to use database of immune complexes' trajectories at different temperatures that does not require registration and allows for all the data to be available for download. Database URL: https://sites.google.com/view/thermopcd/home.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10950042/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140174019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FGCD: a database of fungal gene clusters related to secondary metabolism.","authors":"Fuyuan Zhang, Hongzhe Cao, Helong Si, Jinping Zang, Jingao Dong, Jihong Xing, Kang Zhang","doi":"10.1093/database/baae011","DOIUrl":"10.1093/database/baae011","url":null,"abstract":"<p><p>Fungal secondary metabolites are not necessary for growth, but they are important for fungal metabolism and ecology because they provide selective advantages for competition, survival and interactions with the environment. These various metabolites are widely used as medicinal precursors and insecticides. Secondary metabolism genes are commonly arranged in clusters along chromosomes, which allow for the coordinate control of complete pathways. In this study, we created the Fungal Gene Cluster Database to store, retrieve, and visualize secondary metabolite gene cluster information across fungal species. The database was created by merging data from RNA sequencing, Basic Local Alignment Search Tool, genome browser, enrichment analysis and the R Shiny web framework to visualize and query putative gene clusters. This database facilitated the rapid and thorough examination of significant gene clusters across fungal species by detecting, defining and graphically displaying the architecture, organization and expression patterns of secondary metabolite gene clusters. In general, this genomic resource makes use of the tremendous chemical variety of the products of these ecologically and biotechnologically significant gene clusters to our further understanding of fungal secondary metabolism. Database URL: https://www.hebaubioinformatics.cn/FungalGeneCluster/.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11022746/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140174018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Best practices for the manual curation of intrinsically disordered proteins in DisProt.","authors":"Federica Quaglia, Anastasia Chasapi, Maria Victoria Nugnes, Maria Cristina Aspromonte, Emanuela Leonardi, Damiano Piovesan, Silvio C E Tosatto","doi":"10.1093/database/baae009","DOIUrl":"10.1093/database/baae009","url":null,"abstract":"<p><p>The DisProt database is a resource containing manually curated data on experimentally validated intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) from the literature. Developed in 2005, its primary goal was to collect structural and functional information into proteins that lack a fixed three-dimensional structure. Today, DisProt has evolved into a major repository that not only collects experimental data but also contributes to our understanding of the IDPs/IDRs roles in various biological processes, such as autophagy or the life cycle mechanisms in viruses or their involvement in diseases (such as cancer and neurodevelopmental disorders). DisProt offers detailed information on the structural states of IDPs/IDRs, including state transitions, interactions and their functions, all provided as curated annotations. One of the central activities of DisProt is the meticulous curation of experimental data from the literature. For this reason, to ensure that every expert and volunteer curator possesses the requisite knowledge for data evaluation, collection and integration, training courses and curation materials are available. However, biocuration guidelines concur on the importance of developing robust guidelines that not only provide critical information about data consistency but also ensure data acquisition.This guideline aims to provide both biocurators and external users with best practices for manually curating IDPs and IDRs in DisProt. It describes every step of the literature curation process and provides use cases of IDP curation within DisProt. Database URL: https://disprot.org/.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10953794/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140174017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AagingBase: a comprehensive database of anti-aging peptides.","authors":"Kunjulakshmi R, Ambuj Kumar, Keerthana Vinod Kumar, Avik Sengupta, Kavita Kundal, Simran Sharma, Ankita Pawar, Pithani Sai Krishna, Mohammad Alfatah, Sandipan Ray, Bhavana Tiwari, Rahul Kumar","doi":"10.1093/database/baae016","DOIUrl":"10.1093/database/baae016","url":null,"abstract":"<p><p>The process of aging is an intrinsic and inevitable aspect of life that impacts every living organism. As biotechnological advancements continue to shape our understanding of medicine, peptide therapeutics have emerged as a promising strategy for anti-aging interventions. This is primarily due to their favorable attributes, such as low immunogenicity and cost-effective production. Peptide-based treatments have garnered widespread acceptance and interest in aging research, particularly in the context of age-related therapies. To effectively develop anti-aging treatments, a comprehensive understanding of the physicochemical characteristics of anti-aging peptides is essential. Factors such as amino acid composition, instability index, hydrophobic areas and other relevant properties significantly determine their efficacy as potential therapeutic agents. Consequently, the creation of 'AagingBase', a comprehensive database for anti-aging peptides, aims to facilitate research on aging by leveraging the potential of peptide therapies. AagingBase houses experimentally validated 282 anti-aging peptides collected from 54 research articles and 236 patents. Employing state-of-the-art computational techniques, the acquired sequences have undergone rigorous physicochemical calculations. Furthermore, AagingBase presents users with various informative analyses highlighting atomic compositions, secondary structure fractions, tertiary structure, amino acid compositions and frequencies. The database also offers advanced search and filtering options and similarity search, thereby aiding researchers in understanding their biological functions. Hence, the database enables efficient identification and prioritization of potential peptide candidates in geriatric medicine and holds immense potential for advancing geriatric medicine research and innovations. AagingBase can be accessed without any restriction. Database URL: https://project.iith.ac.in/cgntlab/aagingbase/.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10930205/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140109597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SingleQ: a comprehensive database of single-cell expression quantitative trait loci (sc-eQTLs) cross human tissues.","authors":"Zhiwei Zhou, Jingyi Du, Jianhua Wang, Liangyi Liu, M Gracie Gordon, Chun Jimmie Ye, Joseph E Powell, Mulin Jun Li, Shuquan Rao","doi":"10.1093/database/baae010","DOIUrl":"10.1093/database/baae010","url":null,"abstract":"<p><p>Mapping of expression quantitative trait loci (eQTLs) and other molecular QTLs can help characterize the modes of action of disease-associated genetic variants. However, current eQTL databases present data from bulk RNA-seq approaches, which cannot shed light on the cell type- and environment-specific regulation of disease-associated genetic variants. Here, we introduce our Single-cell eQTL Interactive Database which collects single-cell eQTL (sc-eQTL) datasets and provides online visualization of sc-eQTLs across different cell types in a user-friendly manner. Although sc-eQTL mapping is still in its early stage, our database curates the most comprehensive summary statistics of sc-eQTLs published to date. sc-eQTL studies have revolutionized our understanding of gene regulation in specific cellular contexts, and we anticipate that our database will further accelerate the research of functional genomics. Database URL: http://www.sqraolab.com/scqtl.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10924434/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140068217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Visualization and exploration of linked data using virtual reality.","authors":"Alexander J Kellmann, Max Postema, Joris de Keijser, Pjotr Svetachov, Rebecca C Wilson, Esther J van Enckevort, Morris A Swertz","doi":"10.1093/database/baae008","DOIUrl":"10.1093/database/baae008","url":null,"abstract":"<p><p>In this report, we analyse the use of virtual reality (VR) as a method to navigate and explore complex knowledge graphs. Over the past few decades, linked data technologies [Resource Description Framework (RDF) and Web Ontology Language (OWL)] have shown to be valuable to encode such graphs and many tools have emerged to interactively visualize RDF. However, as knowledge graphs get larger, most of these tools struggle with the limitations of 2D screens or 3D projections. Therefore, in this paper, we evaluate the use of VR to visually explore SPARQL Protocol and RDF Query Language (SPARQL) (construct) queries, including a series of tutorial videos that demonstrate the power of VR (see Graph2VR tutorial playlist: https://www.youtube.com/playlist?list=PLRQCsKSUyhNIdUzBNRTmE-_JmuiOEZbdH). We first review existing methods for Linked Data visualization and then report the creation of a prototype, Graph2VR. Finally, we report a first evaluation of the use of VR for exploring linked data graphs. Our results show that most participants enjoyed testing Graph2VR and found it to be a useful tool for graph exploration and data discovery. The usability study also provides valuable insights for potential future improvements to Linked Data visualization in VR.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11184448/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140329667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SEPDB: a database of secreted proteins.","authors":"Ruiqing Wang, Chao Ren, Tian Gao, Hao Li, Xiaochen Bo, Dahai Zhu, Dan Zhang, Hebing Chen, Yong Zhang","doi":"10.1093/database/baae007","DOIUrl":"10.1093/database/baae007","url":null,"abstract":"<p><p>Detecting changes in the dynamics of secreted proteins in serum has been a challenge for proteomics. Enter secreted protein database (SEPDB), an integrated secretory proteomics database offering human, mouse and rat secretory proteomics datasets collected from serum, exosomes and cell culture media. SEPDB compiles secreted protein information from secreted protein database, UniProt and Human Protein Atlas databases to annotate secreted proteomics data based on protein subcellular localization and disease markers. SEPDB integrates the latest predictive modeling techniques to measure deviations in the distribution of signal peptide structures of secreted proteins, extends signal peptide sequence prediction by excluding transmembrane structural domain proteins and updates the validation analysis pipeline for secreted proteins. To establish tissue-specific profiles, we have also created secreted proteomics datasets associated with different human tissues. In addition, we provide information on heterogeneous receptor network organizational relationships, reflective of the complex functional information inherent in the molecular structures of secreted proteins that serve as ligands. Users can take advantage of the Refreshed Search, Analyze, Browse and Download functions of SEPDB, which is available online at https://sysomics.com/SEPDB/. Database URL:  https://sysomics.com/SEPDB/.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10878045/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139722013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}