Klara Kedem | PubMed Health

PubMed2005

The URMS-RMS hybrid algorithm for fast and sensitive local protein structure alignment.

We present an efficient and sensitive hybrid algorithm for local structure alignment of a pair of 3D protein structures. The hybrid algorithm employs both the URMS (unit-vector root mean squared) metric and the RMS metric. Our algorithm searches efficiently the transformation space using a fast screening protocol; initial transformations (rotations) are identified using the URMS algorithm. These rotations are then clustered and an RMS-based dynamic programming algorithm is invoked to find the maximal local similarities for representative rotations of the clusters. Statistical significance of the alignments is estimated using a model that accounts for both the score of the match and the RMS. We tested our algorithm over the SCOP classification of protein domains. Our algorithm performs very well; its main advantages are that (1) it combines the advantages of the RMS and the URMS metrics, (2) it searches extensively the transformation space, (3) it detects complex similarities and structural repeats, and (4) its results are symmetric. The software is available for download at biozon.org/ftp/software/urms/.

Algorithms↗

PubMed2004

STR2: a structure to string approach for locating G-box riboswitch shapes in pre-selected genes.

Traditional sequence-based search methods such as BLAST and FASTA can be used to identify sequence similarities. Recently, there is a growing interest in performing RNA shape similarity searches inside selected genes to locate RNA structure motifs that are known to possess functionally important roles. For example, in the newly discovered RNA genetic control elements called "riboswitches", the box domain is known to be highly conserved among various bacterial species in both its nucleotide composition and shape. However, in non-bacterial species, shape conservation is likely to become more important than sequence conservation when searching for riboswitch patterns. For this purpose, we present an approach tailored for detecting RNA shape similarities. We extend the Structure to String (ST R2) method that was initially proposed to locate shape similarities in proteins to identify predicted secondary structures of RNAs. The ST R2 for RNAs is a translation of a secondary structure to a string of characters, after which known sequence-based search algorithms with an efficient implementation are being used. We validate that the ST R2 succeeds to locate G-box riboswitches in prokaryotes, as expected. Subsequently we show running examples when attempting to detect G-box riboswitch candidates in eukaryotes.

Algorithms↗