Several lines of evidence now well establish that unfolded peptides in general, and alanine in specific, have an intrinsic preference for the polyproline II (pPII) conformation. Investigation of local order in the unfolded state is, however, complicated by experimental limitations and the inherent dynamics of the system, which has in some cases yielded inconsistent results from different types of experiments. One method of studying these systems is the use of short model peptides, and specifically short alanine peptides, known for predominantly sampling pPII structure in aqueous solution. Recently, He et al. (J. Am. Chem. Soc. 2012, 134, 1571–1576) proposed that unblocked tripeptides may not be suitable models for studying conformational propensities in unfolded peptides due to the presence of end effect, i.e. electrostatic interactions between investigated amino acid residues and terminal charges. To determine whether changing the protonation states of the N- and C-termini influence the conformational manifold of the central amino acid residue in tripeptides, we have examined the pH-dependence of unblocked trialanine and the conformational preferences of alanine in the alanine dipeptide. To this end, we measured and globally analyzed amide I’ band profiles and NMR J-coupling constants. We described conformational distributions as the superposition of two-dimensional Gaussian distributions assignable to specific sub-spaces of the Ramachandran plot. Results show that the conformational ensemble of trialanine as a whole, and the pPII content (χpPII=0.84) in particular, remain practically unaffected by changing the protonation state. We found that compared to trialanine, the alanine dipeptide has slightly lower pPII content (χpPII=0.74) and an ensemble more reminiscent of the unblocked Gly-Ala-Gly model peptide. In addition, a two-state thermodynamic analysis of the conformational sensitive Δε(T) and 3J(HNHα)(T) data obtained from electronic circular dichroism and H-NMR spectra indicate that the free energy landscape of trialanine is similar in all protonation states. MD simulations for the investigated peptides corroborate this notion and show further that the hydration shell around unblocked trialanine is unaffected by the protonation/deprotonation of the C-terminal group. In contrast, the alanine dipeptide shows a reduced water density around the central residue as well as a less ordered hydration shell, which decreases the pPII propensity and reduces the lifetime of sampled conformations.

Amino acid residues of unfolded peptides in water sample only a few basins in the Ramachandran plot, including prominent polyproline II-like (pPII) conformations. Dynamics of guest residues, X, in GXG peptides in water were recently reported to be dominated by pPII and β-strand-like (β) conformations, resulting in an enthalpy-entropy compensation at ∼300 K. Using molecular dynamics (MD) in explicit solvent, we here examine pPII and β conformational ensembles of 15 guest residues in GXG peptides, quantify local orientation of water around their side chains through novel water orientation plots, and study their hydration and hydrogen bonding properties. We show that pPII and β ensembles are characterized by distinct water orientations: pPII ensembles are associated with an increased population of water oriented in parallel to the side chain surface whereas β ensembles exhibit more heterogeneous water orientations. The backbone hydration is significantly higher in pPII than in β ensembles. Importantly, pPII to β hydration differences and the solvent accessible surface area of Cβ hydrogens both correlate with experimental pPII propensities. We propose that pPII conformations are stabilized by a local, hydrogen-bonded clathrate-like water structure and that residue-specific intrinsic pPII propensities reflect distinct abilities of side chains to template this water structure.

In Alzheimer’s disease (AD), amyloid β-protein (Aβ) self–assembles into toxic oligomers. Of the two predominant Aβ alloforms, Aβ1–40 and Aβ1–42, the latter is particularly strongly linked to AD. N-terminally truncated and pyroglutamated Aβ peptides were recently shown to seed Aβ aggregation and contribute significantly to Aβ–mediated toxicity, yet their folding and assembly were not explored computationally. Discrete molecular dynamics (DMD) approach previously captured in vitro–derived distinct Aβ1–40 and Aβ1–42 oligomer size distributions and predicted that the more toxic Aβ1–42 oligomers had more flexible and solvent exposed N-termini than Aβ1–40 oligomers. Here, we examined oligomer formation of Aβ3–40, Aβ3–42, Aβ11–40, and Aβ11–42 by the DMD approach. The four N-terminally truncated peptides showed increased oligomerization propensity relative to the full–length peptides, consistent with in vitro findings. Conformations formed by Aβ3–40/42 had significantly more flexible and solvent–exposed N-termini than Aβ1–40/42 conformations. In contrast, in Aβ11–40/42 conformations the N-termini formed more contacts and were less accessible to the solvent. The compactness of the Aβ11–40/42 conformations was in part facilitated by Val12. Two single amino acid substitutions that reduced and abolished hydrophobicity at position 12, respectively, resulted in a proportionally increased structural variability. Our results suggest that Aβ11–40 and Aβ11–42 oligomers might be less toxic than Aβ1–40 and Aβ1–42 oligomers and offer a plausible explanation for the experimentally–observed increased toxicity of Aβ3–40 and Aβ3–42 and their pyroglutamated forms.

Various experimental and computational techniques have been employed over the past decade to provide structural and thermodynamic insights into G Protein-Coupled Receptor (GPCR) dimerization. Here, we use multiple microsecond-long, coarse-grained, biased and unbiased molecular dynamics simulations (a total of ~4 milliseconds) combined with multi-ensemble Markov state models to elucidate the kinetics of homodimerization of a prototypic GPCR, the µ-opioid receptor (MOR), embedded in a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC)/cholesterol lipid bilayer. Analysis of these computations identifies kinetically distinct macrostates comprising several different short-lived dimeric configurations of either inactive or activated MOR. Calculated kinetic rates and fractions of dimers at different MOR concentrations suggest a negligible population of MOR homodimers at physiological concentrations, which is supported by acceptor photobleaching fluorescence resonance energy transfer (FRET) experiments. This study provides a rigorous, quantitative explanation for some conflicting experimental data on GPCR oligomerization.

Computational strategies aimed at unveiling the thermodynamic and kinetic properties of G Protein-Coupled Receptor (GPCR) activation require extensive molecular dynamics simulations of the receptor embedded in an explicit lipid-water environment. A possible method for efficiently sampling the conformational space of such a complex system is metadynamics (MetaD) with path collective variables (CVs). Here, we applied well-tempered MetaD with path CVs to one of the few GPCRs for which both inactive and fully active experimental structures are available, the μ-opioid receptor (MOR), and assessed the ability of this enhanced sampling method to estimate the thermodynamic properties of receptor activation in line with those obtained by more computationally expensive adaptive sampling protocols. While n-body information theory analysis of these simulations confirmed that MetaD can efficiently characterize ligand-induced allosteric communication across the receptor, standard MetaD cannot be used directly to derive kinetic rates because transitions are accelerated by a bias potential. Applying the principle of Maximum Caliber (MaxCal) to the free-energy landscape of morphine-bound MOR reconstructed from MetaD, we obtained Markov state models that yield kinetic rates of MOR activation in agreement with those obtained by adaptive sampling. Taken together, these results suggest that the MetaD-MaxCal combination creates an efficient strategy for estimating the thermodynamic and kinetic properties of GPCR activation at an affordable computational cost.

The authors regret that the above-referenced article included an error in the calculation of the hydrophobic CG-SASA (coarse-grained solvent-accessible surface area). Instead of the intended sum of CG-SASA values over all hydrophobic residues, the sum was taken over all hydrophilic residues. Consequently, Fig (Fig. 6c and f), indicating relatively compact Aβ 11-40/42 conformations with hydrophobic residues more efficiently shielded from the solvent than in conformations formed by the other four peptides. This shift in hydrophobic CG-SASA values can be seen by comparing onedimensional probability distributions of hydrophobic CG-SASA values for Aβ 11-40/42

No abstract

Core sequences of 4-7 residues that form amyloid fibrils have been identified within natural amyloid proteins. However, the mechanism of amyloid aggregation remains unclear. We designed a new class of aliphatic peptides (with 3-6 residues) that self-assemble in water to amyloid b-type fibers via a-helical intermediates. We compared the self-assembly of our designed peptides with core sequences in Amyloid-beta, Amylin and Calcitonin using a multimodal approach. A common feature was the appearance of a-helical intermediates before the final b-turn structures. Another amyloid-beta core sequence containing the diphenylalanine motif was chosen to evaluate the role of aromatic residues in self-assembly. The repeated occurrence of aromatic residues in core sequences has led to widespread conclusions about their key role in driving self-assembly. Surprisingly, the diphenylalanine-containing sequence did not form cross-b aggregates or involve the a-helical intermediate step.Our study puts forth a new, simplified model system to study amyloidosis and indicates that aromatic interactions are not as important as previously postulated. The results provide valuable insight into the early intermediates and factors driving self-assembly, which is necessary for developing small molecule therapeutic drugs that prevent amyloidosis.