title: Detecting evolutionary relationships across existing fold space, using sequence order-independent profile-profile alignments.
abstract: Here, a scalable, accurate, reliable, and robust protein functional site comparison algorithm is presented. The key components of the algorithm consist of a reduced representation of the protein structure and a sequence order-independent profile-profile alignment (SOIPPA). We show that SOIPPA is able to detect distant evolutionary relationships in cases where both a global sequence and structure relationship remains obscure. Results suggest evolutionary relationships across several previously evolutionary distinct protein structure superfamilies. SOIPPA, along with an increased coverage of protein fold space afforded by the structural genomics initiative, can be used to further test the notion that fold space is continuous rather than discrete.
authors.affiliation: San Diego Supercomputer Center and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA. lxie@sdsc.edu
authors.forename: Lei
authors.initials: L
authors.lastname: Xie
authors.forename: Philip E
authors.initials: PE
authors.lastname: Bourne
mesh_terms: D000465:Algorithms; D005075:Biological Evolution; D019295:Computational Biology / Q000379:methods*; D008957:Models, Genetic; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins