DocumentCode :
2736028
Title :
Potential function of simplified protein models for discriminating native proteins from decoys: combining contact interaction and local sequence-dependent geometry
Author :
Zhang, Jinfeng ; Chen, Rong ; Liang, Jie
Author_Institution :
Dept. of Bioeng., Illinois Univ., Chicago, IL, USA
Volume :
2
fYear :
2004
fDate :
1-5 Sept. 2004
Firstpage :
2976
Lastpage :
2979
Abstract :
An effective potential function is critical for protein structure prediction and folding simulation. For simplified models of proteins where coordinates of only Ca atoms need to be specified, an accurate potential function is important. Such a simplified model is essential for efficient search of conformational space. In this work, we present a formulation of potential function for simplified representations of protein structures. It is based on the combination of descriptors derived from residue-residue contact and sequence-dependent local geometry. The optimal weight coefficients for contact and local geometry is obtained through optimization by maximizing margins among native and decoy structures. The latter are generated by chain growth and by gapless threading. The performance of the potential function in blind test of discriminating native protein structures from decoys is evaluated using several benchmark decoy sets. This potential function have comparable or better performance than several residue-based potential functions that require in addition coordinates of side chain centers or coordinates of all side chain atoms.
Keywords :
biochemistry; calcium; molecular biophysics; proteins; Ca; Ca atom; benchmark decoy set; conformational space; contact interaction geometry; local sequence-dependent geometry; protein model; protein structure prediction; residue-based potential function; Benchmark testing; Biomedical engineering; Econometrics; Engineering profession; Information geometry; Predictive models; Proteins; Solid modeling; Statistics; Thermodynamics; Decoy discrimination; potential function; protein structure prediction; simplified protein models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-8439-3
Type :
conf
DOI :
10.1109/IEMBS.2004.1403844
Filename :
1403844
Link To Document :
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