The conservation of amino acids implies in most cases a biological significance. Therefore, several sequence-based initiatives have been successful for instance, to: i) establish sequence evolutionary relationships, ii) detect functional sites and iii) organizes proteins sequences and their annotations. However, these approaches have certain limitations related with the divergent nature of the biological sequences. Indeed, the fact of that the structure of proteins is several times more conserved than their sequence is relevant, and for example, it has been shown that some conserved structural patterns between related proteins do not preserve their sequences.

This situation, together with the increasing availability of structural data (more than 100.000 structures in the Protein Data Bank and more than 3 millions of homology models in the SWISS-MODEL Repository), represents an opportunity to use and develop structure-based methods for the classification, description and searching of tridimensional (3D) amino acid patterns. Although several tools have been developed for these requirements, they usually demand a known query (e.g. orthosteric binding sites, annotated motif, ligands, among others). Nevertheless, for considering all unknown 3D patterns (e.g. allosteric binding sites, putative binding sites), it is precise to have new tools to discover, instead of just describe, search or detect.

3D-PP, is a free access web service to discover all conserved 3D amino acid patterns among a set of protein structures, including those coming from both, X-ray crystallographic experiments and in silico comparative modelling.

If you have any question about 3D-PP, please send us an email to avaldes@utalca.cl

School of Bioinformatics Engineering | Department of Bioinformatics | Universidad de Talca | Talca, Chile