MPI-INF D3 Publications: Journal Article: {IRECS}: A new algorithm for the selection of most probable ensembles of side-chain conformations in protein models.

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Author(s):

Hartmann, Christoph
Antes, Iris
Lengauer, Thomas

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BibTeX cite key*:

Hartmann2007

Title

Title*:

IRECS: A new algorithm for the selection of most probable ensembles of side-chain conformations in protein models.

Journal

Journal Title*:	Protein Science	Journal's URL:	http://www.proteinscience.org/
Download URL for the article:	http://www.proteinscience.org/cgi/reprint/16/7/1294	Language:	English

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Publisher's Name:	Protein Society	Publisher's URL:	http://www.proteinsociety.org/
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Vol, No, pp, Date

Volume*:	16	Number:
Publishing Date:	2007
Pages*:	1294-1307	Number of VG Pages:
Page Start:		Page End:
Sequence Number:		DOI:	10.1110/ps.062658307

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(LaTeX) Abstract:	We introduce a new algorithm, IRECS (Iterative REduction of Conformational Space), for identifying ensembles of most probable side-chain conformations for homology modeling. On the basis of a given rotamer library, IRECS ranks all side-chain rotamers of a protein according to the probability with which each side chain adopts the respective rotamer conformation. This ranking enables the user to select small rotamer sets that are most likely to contain a near-native rotamer for each side chain. IRECS can therefore act as a fast heuristic alternative to the Dead-End-Elimination algorithm (DEE). In contrast to DEE, IRECS allows for the selection of rotamer subsets of arbitrary size, thus being able to define structure ensembles for a protein. We show that the selection of more than one rotamer per side chain is generally meaningful, since the selected rotamers represent the conformational space of flexible side chains. A knowledge-based statistical potential ROTA was constructed for the IRECS algorithm. The potential was optimized to discriminate between side-chain conformations of native and rotameric decoys of protein structures. By restricting the number of rotamers per side chain to one, IRECS can optimize side chains for a single conformation model. The average accuracy of IRECS for the $\chi_1$ and $\chi_{1+2}$ dihedral angles amounts to 84.7\% and 71.6\%, respectively, using a 40 degrees cutoff. When we compared IRECS with SCWRL and SCAP, the performance of IRECS was comparable to that of both methods. IRECS and the ROTA potential are available for download from the URL http://irecs.bioinf.mpi-inf.mpg.de.
URL for the Abstract:	http://www.ncbi.nlm.nih.gov/sites/entrez?db=pubmed&uid=17567749&cmd=showdetailview&indexed=google
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Correlation

MPG Unit:	Max-Planck-Institut für Informatik

MPG Subunit:	Computational Biology and Applied Algorithmics
Appearance:	MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort

BibTeX Entry:

@ARTICLE{Hartmann2007,
AUTHOR = {Hartmann, Christoph and Antes, Iris and Lengauer, Thomas},
TITLE = {{IRECS}: A new algorithm for the selection of most probable ensembles of side-chain conformations in protein models.},
JOURNAL = {Protein Science},
PUBLISHER = {Protein Society},
YEAR = {2007},
VOLUME = {16},
PAGES = {1294--1307},
DOI = {10.1110/ps.062658307},
}

Entry last modified by Joachim Büch, 02/28/2008

Edit History (please click the blue arrow to see the details)

	Editor(s) Christoph Hartmann	Created 12/11/2007 16:38:50
Revision 1. 0.	Editor Joachim Büch Christoph Hartmann	Edit Date 02.01.2008 18:53:40 12/11/2007 04:38:50 PM