Web server to identify similarity of amino acid motifs to compounds (SAAMCO)
| Authors | |
|---|---|
| Year of publication | 2008 |
| Type | Article in Periodical |
| Magazine / Source | Journal of Chemical Information and Modeling |
| MU Faculty or unit | |
| Citation | |
| Field | Physical chemistry and theoretical chemistry |
| Keywords | amino acid motifs; proteins; similarity; web server; chemopeptidomics |
| Description | Protein-protein interactions are fundamental in mediating biological processes including metabolism, cell growth and signalling. To be able to selectively inhibit or induce protein activity or complex formation is a key feature in controlling disease. For those situations in which protein-protein interactions derive substantial affinity from short linear peptide sequences, or motifs, we can develop search algorithms for peptidomimetic compounds that resemble the short peptide’s structure but are not compromised by poor pharmacological properties. SAAMCO is a web service that facilitates the screening of motifs with known structures against bioactive compound databases. It is built on an algorithm that defines compound similarity based on the presence of appropriate amino acid side chain fragments and a favourable Root Mean Squared Deviation (RMSD) between compound and motif structure. The methodology is efficient as the available compound databases are pre-processed and fast regular expression searches filter potential matches before time- intensive 3D superposition is performed. The required input information is minimal and the compound databases have been selected to maximize the availability of information on biological activity. “Hits” are accompanied with a visualization window and links to source database entries. Motif matching can be defined on partial or full similarity which will increase or reduce respectively the number of potential mimetic compounds. The web server provides the functionality for rapid screening of known or putative interaction motifs against prepared compound libraries using a novel search algorithm. The tabulated results can be analyzed by linking to appropriate databases and by visualization. |
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