Detecting evolutionary relationships across existing fold space, using sequence order-independent profile-profile alignments
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作者:
Xie, Lei
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Univ Calif San Diego, San Diego Supercomp Ctr, La Jolla, CA 92093 USAUniv Calif San Diego, San Diego Supercomp Ctr, La Jolla, CA 92093 USA
Xie, Lei
[1
]
Bourne, Philip E.
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Univ Calif San Diego, San Diego Supercomp Ctr, La Jolla, CA 92093 USA
Univ Calif San Diego, Skaggs Sch Pharm & Pharmaceut Sci, La Jolla, CA 92093 USAUniv Calif San Diego, San Diego Supercomp Ctr, La Jolla, CA 92093 USA
Bourne, Philip E.
[1
,2
]
机构:
[1] Univ Calif San Diego, San Diego Supercomp Ctr, La Jolla, CA 92093 USA
[2] Univ Calif San Diego, Skaggs Sch Pharm & Pharmaceut Sci, La Jolla, CA 92093 USA
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.