CPHmodels-3.0--remote homology modeling using structure-guided sequence profiles

Morten Nielsen, Claus Lundegaard, Ole Lund, Thomas Nordahl Petersen

    Research output: Contribution to journalJournal articleResearchpeer-review

    351 Downloads (Pure)

    Abstract

    CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template homology modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote homology-modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close homology modeling. The new computational costly remote homology-modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is
    Original languageEnglish
    JournalNucleic Acids Research
    Volume38
    Pages (from-to)W576-W581
    ISSN0305-1048
    DOIs
    Publication statusPublished - 2010

    Bibliographical note

    This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

    Fingerprint

    Dive into the research topics of 'CPHmodels-3.0--remote homology modeling using structure-guided sequence profiles'. Together they form a unique fingerprint.

    Cite this