Mechanism for the α‐helix to β‐hairpin transition

Abstract

The aggregation of alpha-helix-rich proteins into beta-sheet-rich amyloid fibrils is associated with fatal diseases, such as Alzheimer's disease and prion disease. During an aggregation process, protein secondary structure elements-alpha-helices-undergo conformational changes to beta-sheets. The fact that proteins with different sequences and structures undergo a similar transition on aggregation suggests that the sequence nonspecific hydrogen bond interaction among protein backbones is an important factor. We perform molecular dynamics simulations of a polyalanine model, which is an alpha-helix in its native state and observe a metastable beta-hairpin intermediate. Although a beta-hairpin has larger potential energy than an alpha-helix, the entropy of a beta-hairpin is larger because of fewer constraints imposed by the hydrogen bonds. In the vicinity of the transition temperature, we observe the interconversion of the alpha-helix and beta-sheet states via a random coil state. We also study the effect of the environment by varying the relative strength of side-chain interactions for a designed peptide-an alpha-helix in its native state. For a certain range of side-chain interaction strengths, we find that the intermediate beta-hairpin state is destabilized and even disappears, suggesting an important role of the environment in the aggregation propensity of a peptide.

Hydrophobic interactions in the formation of secondary structures in small peptides

“…Our results show that both a repulsive db and a physically realistic range of cm attraction of ∼5.0Å between methyl or methylene groups tend to favor β over α structures, at least for the polyalanine, polyvaline, and polyleucine chains we have studied. This finding may help to assess prior studies that used effective ranges of cm attraction as large as 6.5Å [31,32]. db's arise from empty spaces created by water exclusion between hydrophobic groups [37][38][39][40]42] and are the hallmark of interactions between nonpolar groups [33,34,[36][37][38][39][40][41][42][43] that are partially exposed to water.…”

“…An early simulation of a 12mer polyalanine indicated that its ground state was an α helix in vacuum and a β hairpin in aqueous solution [30]. However, subsequent simulations of aqueous short hydrophobic-polar [31] and polyalanine [32] peptides using different potential functions predicted an α-helical ground state except for very high hydrophobic interaction strengths [32].…”

“…We also considered desolvation barrier (db) effects as they are critical in protein energetics [33][34][35][36][37][38][39][40][41][42][43]. db effects were neglected in many implicit-water potential functions [31,32] despite studies showing its importance for protein structure prediction [44]. For polyalanine, we found that sidechains subjected to hydrophobic interactions in α helices are constrained to the db region and thus are disfavored [45,46].…”

Fidelity of the Protein Structure Reconstruction from Inter-Residue Proximity Constraints

“…The detailed implementation of the covalent bonds and constraints that maintain the correct geometry of each residue and the peptide connectivity is described by Ding et al 34 Clustering Methods. Clustering is the procedure that categorizes or groups similar entities together on the basis of quantitative distance (similarity) measures.…”

Simple but predictive protein models

“…We describe the use of simplified protein models in conjunction with the rapid simulations methodology, discrete molecular dynamics (DMD). Despite the use of DMD in simulating polymer fluids [6,7], single homopolymers [7,8], proteins [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25], protein aggregates [13,17,23,24,26], and gases and liquids [27,28], we believe it is significantly underutilized in the molecular-modeling field.…”