Name
Abstract | ||
|---|---|---|
Motivation: Structural genomics initiatives are increasingly leading to the determination of the 3D structure of target proteins whose catalytic function is not known. The aim of this work was that of developing a novel versatile tool for searching structural similarity, which allows to predict the catalytic function, if any, of these proteins. Results: The algorithm implemented by the tool is based on local structural comparison to find the largest subset of similar residues between an input protein and known functional sites. The method uses a geometric hashing approach where information related to residue pairs from the input structures is stored in a hash table and then is quickly retrieved during the comparison step. Tests on proteins belonging to different functional classes, done using the Catalytic Site Atlas entries as targets, indicate that the algorithm is able to identify the correct functional class of the input protein in the vast majority of the cases. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1093/bioinformatics/btt664 | BIOINFORMATICS |
Field | DocType | Volume |
Data mining,Structural genomics,Computer science,Computational mathematics,Software,Graphical user interface,Geometric hashing,Bioinformatics,Java,Java virtual machine,Hash table | Journal | 30 |
Issue | ISSN | Citations |
7 | 1367-4803 | 4 |
PageRank | References | Authors |
0.47 | 3 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Silvia Caprari | 1 | 7 | 1.21 |
| Daniele Toti | 2 | 105 | 13.86 |
| Le Viet Hung | 3 | 10 | 1.93 |
| Maurizio Di Stefano | 4 | 4 | 0.47 |
| Fabio Polticelli | 5 | 68 | 8.97 |