CBB seminar
Tuesday, March 14
11 am, B2 Library

Tom Madej and Jie Chen

Performance evaluation of protein structural similarity measures

Abstract

To discover remote evolutionary relationships between proteins, biologists rely on comparative 
sequence analysis, and when structures are available, on structural alignments and various measures
 of structural similarity.  The measures/scores that have most commonly been used for this purpose 
include: alignment length, percent sequence identity, superposition RMSD and their different combinations. 
 More recently, we have introduced the "Homologous core structure overlap score" (HCS) and the 
"Loop Hausdorff Measure" (LHM). The HCS score uses pre-defined lists of homologous structures 
together with structural alignments in order to characterize the conserved structure of the homologs.  
The LHM score does not make a priori use of homologous structures and quantifies the structural
 (dis)similarity of unaligned loop regions in proteins.  Along with these measures we also
 consider the "gapped structural alignment score" (GSAS), which was introduced earlier by other researchers. 
 In this talk we consider the performance of these and other conventional measures at the task of
 ranking structure neighbors by homology, and we show that the LHM, HCS, and GSAS scores display 
considerably improved performance over the conventional measures of sequence or structural similarity.


We will also demo/preview new additions to the VAST structure neighbor
 web server: the new scoring options for structure neighbors and filtering of neighbor
 lists using the Entrez history feature.

(joint work with Anna Panchenko and Steve Bryant)