Joo K.,Center for in Silico Protein ScienceKorea Institute for Advanced StudySeoul130 722 Korea |
Joung I.,Center for in Silico Protein ScienceKorea Institute for Advanced StudySeoul130 722 Korea |
Lee S.Y.,Center for in Silico Protein ScienceKorea Institute for Advanced StudySeoul130 722 Korea |
Kim J.Y.,Center for in Silico Protein ScienceKorea Institute for Advanced StudySeoul130 722 Korea |
And 7 more authors.
Proteins: Structure, Function and Bioinformatics | Year: 2015
For the template-based modeling (TBM) of CASP11 targets, we have developed three new protein modeling protocols (nns for server prediction and LEE and LEER for human prediction) by improving upon our previous CASP protocols (CASP7 through CASP10). We applied the powerful global optimization method of conformational space annealing to three stages of optimization, including multiple sequence-structure alignment, three-dimensional (3D) chain building, and side-chain remodeling. For more successful fold recognition, a new alignment method called CRFalign was developed. It can incorporate sensitive positional and environmental dependence in alignment scores as well as strong nonlinear correlations among various features. Modifications and adjustments were made to the form of the energy function and weight parameters pertaining to the chain building procedure. For the side-chain remodeling step, residue-type dependence was introduced to the cutoff value that determines the entry of a rotamer to the side-chain modeling library. The improved performance of the nns server method is attributed to successful fold recognition achieved by combining several methods including CRFalign and to the current modeling formulation that can incorporate native-like structural aspects present in multiple templates. The LEE protocol is identical to the nns one except that CASP11-released server models are used as templates. The success of LEE in utilizing CASP11 server models indicates that proper template screening and template clustering assisted by appropriate cluster ranking promises a new direction to enhance protein 3D modeling. © 2015 Wiley Periodicals, Inc.