TollML: A database of toll-like receptor structural motifs

Jing Gong, Tiandi Wei, Ning Zhang, Ferdinand Jamitzky, Wolfgang M. Heckl, Shaila C. Rössle, Robert W. Stark

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Toll-like receptors (TLRs) play a key role in the innate immune system. TLRs recognize pathogenassociated molecular patterns and initiate an intracellular kinase cascade to induce an immediate defensive response. During recent years TLRs have become the focus of tremendous research interest. A central repository for the growing amount of relevant TLR sequence information has been created. Nevertheless, structural motifs of most sequenced TLR proteins, such as leucine-rich repeats (LRRs), are poorly annotated in the established databases. A database that organizes the structural motifs of TLRs could be useful for developing pattern recognition programs, structural modeling and understanding functional mechanisms of TLRs. We describe TollML, a database that integrates all of the TLR sequencing data from the NCBI protein database. Entries were first divided into TLR families (TLR1-23) and then semi-automatically subdivided into three levels of structural motif categories: (1) signal peptide (SP), ectodomain (ECD), transmembrane domain (TD) and Toll/IL-1 receptor (TIR) domain of each TLR; (2) LRRs of each ECD; (3) highly conserved segment (HCS), variable segment (VS) and insertions of each LRR. These categories can be searched quickly using an easy-to-use web interface and dynamically displayed by graphics. Additionally, all entries have hyperlinks to various sources including NCBI, Swiss-Prot, PDB, LRRML and PubMed in order to provide broad external information for users. The TollML database is available at http://tollml.lrz.de.

Original languageEnglish
Pages (from-to)1283-1289
Number of pages7
JournalJournal of Molecular Modeling
Volume16
Issue number7
DOIs
StatePublished - Jul 2010

Keywords

  • Homology modeling
  • Leucine-rich repeats
  • Toll-like receptor
  • TollML
  • XML database

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