A fast method for large-scale de novo peptide and miniprotein structure prediction

(c) 2009 Wiley Periodicals, Inc.

Bibliographische Detailangaben
Veröffentlicht in:Journal of computational chemistry. - 1984. - 31(2010), 4 vom: 01. März, Seite 726-38
1. Verfasser: Maupetit, Julien (VerfasserIn)
Weitere Verfasser: Derreumaux, Philippe, Tufféry, Pierre
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2010
Zugriff auf das übergeordnete Werk:Journal of computational chemistry
Schlagworte:Journal Article Peptides Proteins
LEADER 01000naa a22002652 4500
001 NLM189689013
003 DE-627
005 20231223184047.0
007 cr uuu---uuuuu
008 231223s2010 xx |||||o 00| ||eng c
024 7 |a 10.1002/jcc.21365  |2 doi 
028 5 2 |a pubmed24n0632.xml 
035 |a (DE-627)NLM189689013 
035 |a (NLM)19569182 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Maupetit, Julien  |e verfasserin  |4 aut 
245 1 2 |a A fast method for large-scale de novo peptide and miniprotein structure prediction 
264 1 |c 2010 
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 16.04.2010 
500 |a Date Revised 03.02.2010 
500 |a published: Print 
500 |a Citation Status MEDLINE 
520 |a (c) 2009 Wiley Periodicals, Inc. 
520 |a Although peptides have many biological and biomedical implications, an accurate method predicting their equilibrium structural ensembles from amino acid sequences and suitable for large-scale experiments is still missing. We introduce a new approach-PEP-FOLD-to the de novo prediction of peptides and miniproteins. It first predicts, in the terms of a Hidden Markov Model-derived structural alphabet, a limited number of local conformations at each position of the structure. It then performs their assembly using a greedy procedure driven by a coarse-grained energy score. On a benchmark of 52 peptides with 9-23 amino acids, PEP-FOLD generates lowest-energy conformations within 2.8 and 2.3 A Calpha root-mean-square deviation from the full nuclear magnetic resonance structures (NMR) and the NMR rigid cores, respectively, outperforming previous approaches. For 13 miniproteins with 27-49 amino acids, PEP-FOLD reaches an accuracy of 3.6 and 4.6 A Calpha root-mean-square deviation for the most-native and lowest-energy conformations, using the nonflexible regions identified by NMR. PEP-FOLD simulations are fast-a few minutes only-opening therefore, the door to in silico large-scale rational design of new bioactive peptides and miniproteins 
650 4 |a Journal Article 
650 7 |a Peptides  |2 NLM 
650 7 |a Proteins  |2 NLM 
700 1 |a Derreumaux, Philippe  |e verfasserin  |4 aut 
700 1 |a Tufféry, Pierre  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t Journal of computational chemistry  |d 1984  |g 31(2010), 4 vom: 01. März, Seite 726-38  |w (DE-627)NLM098138448  |x 1096-987X  |7 nnns 
773 1 8 |g volume:31  |g year:2010  |g number:4  |g day:01  |g month:03  |g pages:726-38 
856 4 0 |u http://dx.doi.org/10.1002/jcc.21365  |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 31  |j 2010  |e 4  |b 01  |c 03  |h 726-38