Počet záznamů: 1
Insights into Unfolded Proteins from the Intrinsic phi/psi Propensities of the AAXAA Host-Guest Series
- 1.0458534 - UOCHB-X 2017 RIV US eng J - Článek v odborném periodiku
Towse, C. L. - Vymětal, Jiří - Vondrášek, Jiří - Daggett, V.
Insights into Unfolded Proteins from the Intrinsic phi/psi Propensities of the AAXAA Host-Guest Series.
Biophysical Journal. Roč. 110, č. 2 (2016), s. 348-361. ISSN 0006-3495
Grant CEP: GA MŠk(CZ) LH11020
Institucionální podpora: RVO:61388963
Klíčová slova: polyproline-II helix * beta-sheet protein * random-coil behavior
Kód oboru RIV: BO - Biofyzika
Impakt faktor: 3.656, rok: 2016
Various host-guest peptide series are used by experimentalists as reference conformational states. One such use is as a baseline for random-coil NMR chemical shifts. Comparison to this random-coil baseline, through secondary chemical shifts, is used to infer protein secondary structure. The use of these random-coil data sets rests on the perception that the reference chemical shifts arise from states where there is little or no conformational bias. However, there is growing evidence that the conformational composition of natively and nonnatively unfolded proteins fail to approach anything that can be construed as random coil. Here, we use molecular dynamics simulations of an alanine-based host-guest peptide series (AAXAA) as a model of unfolded and denatured states to examine the intrinsic propensities of the amino acids. We produced ensembles that are in good agreement with the experimental NMR chemical shifts and confirm that the sampling of the 20 natural amino acids in this peptide series is be far from random. Preferences toward certain regions of conformational space were both present and dependent upon the environment when compared under conditions typically used to denature proteins, i.e., thermal and chemical denaturation. Moreover, the simulations allowed us to examine the conformational makeup of the underlying ensembles giving rise to the ensemble-averaged chemical shifts. We present these data as an intrinsic backbone propensity library that forms part of our Structural Library of Intrinsic Residue Propensities to inform model building, to aid in interpretation of experiment, and for structure prediction of natively and nonnatively unfolded states.
Trvalý link: http://hdl.handle.net/11104/0258790