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. © 2013 The Author 2013. Published by Oxford University Press. All rights reserved.
Caprari, S., Toti, D., Le, V.H., DI STEFANO, M., Polticelli, F. (2014). ASSIST: A fast versatile local structural comparison tool. BIOINFORMATICS, 30(7), 1022-1024 [10.1093/bioinformatics/btt664].
ASSIST: A fast versatile local structural comparison tool
CAPRARI, SILVIA;TOTI, DANIELE;LE, VIET HUNG;DI STEFANO, MAURIZIO;POLTICELLI, Fabio
2014-01-01
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. © 2013 The Author 2013. Published by Oxford University Press. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
