Proteins databases, list

If a monoclonal antibody was generated by immunization with a full-length native protein rather than a peptide, then the immunized mouse will generate antibodies that recognize both linear and conformationally dependent epitopes. Only a small subset of these monoclonal antibodies will likely be useful for clinical use on formalin-fixed, paraffin-embedded tissue (FFPE) samples. Those that are useful tend to have epitopes that are linear the epitopes are not dependent on the protein s three-dimensional conformation (see Chapter 16). Therefore, for antibodies generated in response to immunization with full-length proteins, the peptides that serve as positive controls will be linear stretches of amino acids derived from the native protein sequence, as listed in protein databases. 

The obtained peak list together with other data (biological species, possible posttransla-tional modifications of amino acids, etc.) is then submitted to a software tool (usually publicly available) and searched against a certain protein database, which leads to protein identification. The majority of available software tools also offer information on the statistical probability of protein identification. 

The Swiss-Prot database is probably the most widely used protein database. It is maintained collaboratively by the European Bioinformatics Institute (EBI) and the Swiss Institute for Bioinformatics. It is relatively easy to access and search via the World Wide Web (Table 2.4). A sample entry for human insulin is provided in Figure 2.4. Additional information detailing such databases is available via the web addresses provided in Table 2.4 and in the bioinformatics publications listed at the end of this chapter. 

List of Abbreviations GPCRs, G-protein coupled receptors PDB, protein database SCRs, structurally conserved regions SVRs, structurally variable regions... 

To Study interactions between proteins and drugs, an available tool is the Drug Absorption, Distribution, Metabolism, and Excretion (ADME) Associated Protein Database (see Table 1.5). The database contains information about relevant proteins, functions, similarities, substrates and hgands, tissue distributions, and other features of targets. Eor the understanding of pharmacokinetic (PK) and pharmacodynamic (PD) features, some available resources are listed in Table 1.5. For example, the Pharmacokinetic and Pharmacodynamic Resources site provides links to relevant software, courses, textbooks, and journals (see Note 5). For quantitative structure-activity relationship (QSAR), the QSAR Datasets site collects data sets that are available in a structural format (see Table 1.5). 

Other databases, including DNA and protein databases, the Human Genome Database (GDB), and Medline. Two relatively new query systems in OMIM, OMIM Gene Map and OMDVt Morbid Map, provide cytogenetic map locations of diseases and gene lists organized by diseases, respectively. 

In Table 1 the arehaeal r-proteins are listed whose sequences were available at the time this chapter was prepared. These data were obtained from the RIBO database of the Max-Planck-Institut fur Molekulare Genetik, Berlin, whieh contains over 860 published and unpublished r-protein sequences as well as partial protein sequences (December, 1991). Using this database, the similarity (identical amino acids at comparable locations) of the r-proteins from the three domains (archaea, bacteria and eucarya) was calculated and the results are shown in Table 2. 

Primary and even tertiary structures are now known for many of the hemostatic system proteins. Gene structures have been identified for all of the known components of the hemostatic system. Databases listing mutations and their related hemorrhagic or thrombotic risks are growing rapidly. For many reactions, the molecular mechanisms responsible for the properties of the hemostatic... 

V Output of protein database search lists the best protein match ... 

Other useful sites for yeast genome analysis include Saccharomyces cerevisiae Promoter Database, listing known regulatory elements and transcriptional factors in yeast TRansposon-Insertion Phenotypes, Localization, and Expression in Saccharomyces (TRIPLES) database, which tracks the expression of transposon-induced mutants and the cellular localization of transposon-tagged proteins, and the Saccharomyces Cell Cycle Expression Database, presenting the first results on changes in mRNA transcript levels dming the yeast cell cycle. 

There are two options to query the HCC-M database either (1) protein search by NCBI/SWISS-PROT Accession number. Protein name and Protein ID (ID as published in Scow et al., 2000) or (2) interactive protein spots query on the original 2-DE image maps (Fig. 5). The availability of this protein database and the integrated proteome database of Cho et ah (2002) should serve as a useful resource for other groups involved in HCC research. They will now join a list of databases dedicated to cancer proteomics (Simpson and Dorow, 2001). 

Conceptually, the amino and carboxyl termini of a polypeptide chain are flexible and amendable to form a peptide bond. The formation of the terminally linked peptide bond yields circular (cyclic) proteins with circular backbones. Cyclic peptides such as cyclosporin are known. These peptides tend to be less than 12 amino acids in size, contain modifled amino acids and are generally metabolic products. Whereas circular proteins are 14-70 amino acids in size, true gene products (encoded by DNA) with well-defined 3D structures. They occur in microorganisms, plants and animals, as products for an enhanced stability or involvement in host defense (Trabi and Craik, 2002). Several naturally occurring circular proteins are listed in Table 5.10. CyBase (http //research.imb.uq.edu.au/ cybase) is the curated database for cyclic proteins. 

The databases listed in Table 8.2 are maintained by independent research groups and can be accessed through the Internet. Some of these databases are nucleotide databases, and some protein databases that have been translated from the nucleotide databases. They are updated frequently and contain comprehensive lists of protein and nucleotide sequences. The choice of a particular database is dictated by the extensiveness of sequence entries, low redundancy rate, low error rate, and a high degree of annotation. A custom-made database can be assembled into a composite nonredundant database by including entries from all protein databases and translated-nucleotide databases (into protein sequences) and removing any duplicate entries. 

Table II lists the proteins used in the training set, a subset of the PDB Select database of nonhomologous proteins [21]. We avoided inclusion of proteins that form dimers (or other oligomers) in solution because one would expect the distributions in this case to be significantly altered due to the oligomerization process. For each protein we list the PDB code, number of residues, radius of gyration, and classification in our size bin scheme.

---