ArchPRED: a template based loop structure prediction server
Author(s) -
Narcís FernándezFuentes,
Jixian Zhai,
András Fiser
Publication year - 2006
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkl113
Subject(s) - loop (graph theory) , dihedral angle , similarity (geometry) , algorithm , template , biology , sequence (biology) , position (finance) , computer science , conjugate gradient method , root mean square , matching (statistics) , minification , biological system , bioinformatics , computational biology , mathematics , combinatorics , physics , artificial intelligence , genetics , molecule , statistics , image (mathematics) , hydrogen bond , finance , quantum mechanics , economics , programming language
ArchPRED server (http://www.fiserlab.org/servers/archpred) implements a novel fragment-search based method for predicting loop conformations. The inputs to the server are the atomic coordinates of the query protein and the position of the loop. The algorithm selects candidate loop fragments from a regularly updated loop library (Search Space) by matching the length, the types of bracing secondary structures of the query and by satisfying the geometrical restraints imposed by the stem residues. Subsequently, candidate loops are inserted in the query protein framework where their side chains are rebuilt and their fit is assessed by the root mean square deviation (r.m.s.d.) of stem regions and by the number of rigid body clashes with the environment. In the final step remaining candidate loops are ranked by a Z-score that combines information on sequence similarity and fit of predicted and observed [/psi] main chain dihedral angle propensities. The final loop conformation is built in the protein structure and annealed in the environment using conjugate gradient minimization. The prediction method was benchmarked on artificially prepared search datasets where all trivial sequence similarities on the SCOP superfamily level were removed. Under these conditions it was possible to predict loops of length 4, 8 and 12 with coverage of 98, 78 and 28% with at least of 0.22, 1.38 and 2.47 A of r.m.s.d. accuracy, respectively. In a head to head comparison on loops extracted from freshly deposited new protein folds the current method outperformed in a approximately 5:1 ratio an earlier developed database search method.
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