sDFIRE : Sequence-specific statistical energy function for protein structure prediction by decoy selections

© 2016 Wiley Periodicals, Inc.

Bibliographische Detailangaben
Veröffentlicht in:Journal of computational chemistry. - 1984. - 37(2016), 12 vom: 05. Mai, Seite 1119-24
1. Verfasser: Hoque, Md Tamjidul (VerfasserIn)
Weitere Verfasser: Yang, Yuedong, Mishra, Avdesh, Zhou, Yaoqi
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2016
Zugriff auf das übergeordnete Werk:Journal of computational chemistry
Schlagworte:News Research Support, Non-U.S. Gov't decoy sets energy function genetic algorithm optimization protein structure Proteins
LEADER 01000naa a22002652 4500
001 NLM257207767
003 DE-627
005 20231224182319.0
007 cr uuu---uuuuu
008 231224s2016 xx |||||o 00| ||eng c
024 7 |a 10.1002/jcc.24298  |2 doi 
028 5 2 |a pubmed24n0857.xml 
035 |a (DE-627)NLM257207767 
035 |a (NLM)26849026 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Hoque, Md Tamjidul  |e verfasserin  |4 aut 
245 1 0 |a sDFIRE  |b Sequence-specific statistical energy function for protein structure prediction by decoy selections 
264 1 |c 2016 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Completed 13.12.2016 
500 |a Date Revised 30.12.2016 
500 |a published: Print-Electronic 
500 |a Citation Status MEDLINE 
520 |a © 2016 Wiley Periodicals, Inc. 
520 |a An important unsolved problem in molecular and structural biology is the protein folding and structure prediction problem. One major bottleneck for solving this is the lack of an accurate energy to discriminate near-native conformations against other possible conformations. Here we have developed sDFIRE energy function, which is an optimized linear combination of DFIRE (the Distance-scaled Finite Ideal gas Reference state based Energy), the orientation dependent (polar-polar and polar-nonpolar) statistical potentials, and the matching scores between predicted and model structural properties including predicted main-chain torsion angles and solvent accessible surface area. The weights for these scoring terms are optimized by three widely used decoy sets consisting of a total of 134 proteins. Independent tests on CASP8 and CASP9 decoy sets indicate that sDFIRE outperforms other state-of-the-art energy functions in selecting near native structures and in the Pearson's correlation coefficient between the energy score and structural accuracy of the model (measured by TM-score) 
650 4 |a News 
650 4 |a Research Support, Non-U.S. Gov't 
650 4 |a decoy sets 
650 4 |a energy function 
650 4 |a genetic algorithm 
650 4 |a optimization 
650 4 |a protein structure 
650 7 |a Proteins  |2 NLM 
700 1 |a Yang, Yuedong  |e verfasserin  |4 aut 
700 1 |a Mishra, Avdesh  |e verfasserin  |4 aut 
700 1 |a Zhou, Yaoqi  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t Journal of computational chemistry  |d 1984  |g 37(2016), 12 vom: 05. Mai, Seite 1119-24  |w (DE-627)NLM098138448  |x 1096-987X  |7 nnns 
773 1 8 |g volume:37  |g year:2016  |g number:12  |g day:05  |g month:05  |g pages:1119-24 
856 4 0 |u http://dx.doi.org/10.1002/jcc.24298  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 37  |j 2016  |e 12  |b 05  |c 05  |h 1119-24