RESUMO
Recently, body fluids have widely become an important target for proteomic research and proteomic study has produced more and more body fluid related protein data. A database is needed to collect and analyze these proteome data. Thus, we developed this web-based body fluid proteome database Sys-BodyFluid. It contains eleven kinds of body fluid proteomes, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, seminal fluid, human milk and amniotic fluid. Over 10,000 proteins are presented in the Sys-BodyFluid. Sys-BodyFluid provides the detailed protein annotations, including protein description, Gene Ontology, domain information, protein sequence and involved pathways. These proteome data can be retrieved by using protein name, protein accession number and sequence similarity. In addition, users can query between these different body fluids to get the different proteins identification information. Sys-BodyFluid database can facilitate the body fluid proteomics and disease proteomics research as a reference database. It is available at http://www.biosino.org/bodyfluid/.
Assuntos
Líquidos Corporais/química , Bases de Dados de Proteínas , Proteoma/análise , Proteômica , Líquidos Corporais/metabolismo , Humanos , Proteínas/química , Proteínas/genética , Proteínas/metabolismo , PesquisaRESUMO
SUMMARY: We design and implement an integrated database system called 'multi-protein survey system' (MPSS), which provides a platform to retrieve information about many proteins at a time. This system integrates several important and widely used databases including SwissProt, TrEMBL, PDB and InterPro, plus useful references such as GO and KEGG to other databases. Users may submit a group of protein IDs, entry names, SwissProt/TrEMBL accession numbers or GenBank GIs through MPSS' web interface, and obtain protein annotation information from public databases and pre-computed molecular properties speedily. MPSS can also supply comprehensive information about query proteins, including 3D structures, domains, pathway, gene ontology and visual presentation of mapping to the GO tree and KEGG pathway, to provide an up-to-date view of available knowledge with regard to the structures and molecular functions of proteins under study. AVAILABILITY: MPSS is freely accessible at http://www.scbit.org/mpss/
Assuntos
Sistemas de Gerenciamento de Base de Dados , Bases de Dados de Proteínas , Documentação/métodos , Armazenamento e Recuperação da Informação/métodos , Proteínas/química , Proteínas/metabolismo , Interface Usuário-Computador , Proteínas/classificação , Integração de SistemasRESUMO
AIM: To obtain the information of ligand-receptor binding between the S protein of SARS-CoV and CD13, identify the possible interacting domains or motifs related to binding sites, and provide clues for studying the functions of SARS proteins and designing anti-SARS drugs and vaccines. METHODS: On the basis of comparative genomics, the homology search, phylogenetic analyses, and multi-sequence alignment were used to predict CD13 related interacting domains and binding sites in the S protein of SARS-CoV. Molecular modeling and docking simulation methods were employed to address the interaction feature between CD13 and S protein of SARS-CoV in validating the bioinformatics predictions. RESULTS: Possible binding sites in the SARS-CoV S protein to CD13 have been mapped out by using bioinformatics analysis tools. The binding for one protein-protein interaction pair (D757-R761 motif of the SARS-CoV S protein to P585-A653 domain of CD13) has been simulated by molecular modeling and docking simulation methods. CONCLUSION: CD13 may be a possible receptor of the SARS-CoV S protein, which may be associated with the SARS infection. This study also provides a possible strategy for mapping the possible binding receptors of the proteins in a genome.
