Phosphorylation Promotes Aβ25-35 Peptide Aggregation within the DMPC Bilayer

Binding mechanism of full-length Aβ40 peptide to a mixed lipid bilayer

The destructive effect of Aβ peptides on membranes is an important source of its cytotoxicity in the pathogenesis of Alzheimer's disease. We have investigated the binding mechanism between the Aβ42 peptide and bilayer in our former work. However, as another abundant form of Aβ peptides in the physiological environment, the binding mechanism between Aβ40 peptide and the lipid bilayer still remains ambiguous. Hence, we performed all-atom simulations on the Aβ40 peptides with the lipid bilayer herein using replica exchange with the solute tempering 2 method. We obtained four major binding models with the hydrophobic C-terminus as the most preferable binding region. Hydrophobic residues and positively charged residues are the principal residues involved in the peptide-bilayer interactions. Aβ40 peptides in our simulation mainly adopt a β-rich conformation in both bound and unbound states. Besides, we determined peptide-water interactions and found that bound peptides prefer forming hydrogen bonds with water molecules than unbound peptides. Our findings herein may provide new insights for the in-depth understanding of the membrane-destructive mechanism of Aβ peptides.

Effect of Modification Strategies on the Biological Activity of Peptides/Proteins

Covalent attachment of biologically active peptides/proteins with functional moieties is an effective strategy to control their biodistribution, pharmacokinetics, enzymatic digestion, and toxicity. This review focuses on the characteristics of different modification strategies and their effects on the biological activity of peptides/proteins and illustrates their relevant applications and potential.

Lysine Acetylation Changes the Mechanism of Aβ25-35 Peptide Binding and Dimerization in the DMPC Bilayer

The impact of Lys28 acetylation on Alzheimer's Aβ peptide binding to the lipid bilayer has not been previously studied, either experimentally or computationally. To probe this common post-translational modification, we performed all-atom replica exchange molecular dynamics simulations targeting binding and aggregation of acetylated acAβ25-35 peptide within the DMPC bilayer. Using the unmodified Aβ25-35 studied previously as a reference, our results can be summarized as follows. First, Lys28 acetylation strengthens the Aβ25-35 hydrophobic moment and consequently promotes the helical structure across the peptide extending it into the N-terminus. Second, because Lys28 acetylation disrupts electrostatic contact between Lys28 and lipid phosphate groups, it reduces the binding affinity of acAβ25-35 peptides to the DMPC bilayer. Accordingly, although acetylation preserves the bimodal binding featuring a preferred inserted state and a less probable surface bound state, it decreases the stability of the former. Third, acetylation promotes acAβ25-35 aggregation and eliminates monomers as thermodynamically viable species. More importantly, acAβ25-35 retains as the most thermodynamically stable the inserted dimer with unique head-to-tail helical aggregation interface. However, due to enhanced helix structure, this dimer state becomes less stable and is less likely to propagate into higher order aggregates. Thus, acetylation is predicted to facilitate the formation of low-molecular-weight oligomers. Other post-translational modifications, including phosphorylation and oxidation, reduce helical propensity and have divergent impact on aggregation. Consequently, acetylation, when considered in its totality, has distinct consequences on Aβ25-35 binding and aggregation in the lipid bilayer.

Binding Models of Aβ42 Peptide with Membranes Explored by Molecular Simulations

One of the factors contributing to the toxicity of amyloid-β (Aβ) peptides is the destruction of membrane integrity through Aβ peptide-membrane interactions. The binding of Aβ peptides to membranes has been studied by experiments and theoretical simulations extensively. The exact binding mechanism, however, still remains elusive. In the present study, the molecular basis of the peptide-bilayer binding mechanism of the full-length Aβ42 monomer with POPC/POPS/CHOL bilayers is investigated by all-atom (AA) simulations. Three main binding models in coil, bend, and turn structures are obtained. Model 1 of the three models with the central hydrophobic core (CHC) buried inside the membrane is the dominant binding model. The structural features of the peptide, the peptide-bilayer interacting regions, the intrapeptide interactions, and peptide-water interactions are studied. The binding of the Aβ42 monomer to the POPC/POPS/CHOL bilayer is also explored by coarse-grained (CG) simulations as a complement. Both the AA and CG simulations show that residues in CHC prefer forming interactions with the bilayer, indicating the crucial role of CHC in peptide-bilayer binding. Our results can provide new insights for the investigation of the peptide-bilayer binding mechanism of the Aβ peptide.

De Novo Transmembrane Aggregation of Aβ10-40 Peptides in an Anionic Lipid Bilayer

Using the all-atom model and 10 μs serial replica-exchange molecular dynamics (SREMD), we investigated the binding of Alzheimer's Aβ10-40 peptides to the anionic dimyristoylphosphatidylcholine/dimyristoylphosphatidylglycerol (DMPC/DMPG) lipid bilayer. Our objective was to probe de novo transmembrane Aβ10-40 aggregation and to test the utility of SREMD. Our results are threefold. First, upon binding, Aβ10-40 adopts a helical structure in the C-terminus and deeply inserts into the bilayer. Binding is primarily controlled by electrostatic interactions of the peptides with water, ions, and lipids, particularly, anionic DMPG. Second, Aβ-bilayer interactions reorganize lipids in the proximity of the bound peptides, causing an influx of DMPG lipids into the Aβ binding footprint. Third and most important, computed free energy landscapes reveal that Aβ10-40 peptides partition into monomeric and dimeric species. The dimers result from transmembrane aggregation of the peptides and induce a striking lipid density void throughout both leaflets in the bilayer. There are multiple factors stabilizing transmembrane dimers, including van der Waals and steric interactions, electrostatic interactions, and hydrogen bonding, hydration, and entropic gains originating from dimer conformations and lipid disorder. We argue that helix dipole-dipole interactions underestimated in the all-atom force field must be a contributing factor to stabilizing antiparallel transmembrane dimers. We propose that transmembrane aggregates serve as mechanistic links between the populations of extra- and intracellular Aβ peptides. From the computational perspective, SREMD is found to be a viable alternative to traditional replica-exchange simulations.

Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma

Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure. Hence, they are often misconceived to present a challenge to Anfinsen's dogma. However, IDPs exist as ensembles that sample a quasi-continuum of rapidly interconverting conformations and, as such, may represent proteins at the extreme limit of the Anfinsen postulate. IDPs play important biological roles and are key components of the cellular protein interaction network (PIN). Many IDPs can interconvert between disordered and ordered states as they bind to appropriate partners. Conformational dynamics of IDPs contribute to conformational noise in the cell. Thus, the dysregulation of IDPs contributes to increased noise and "promiscuous" interactions. This leads to PIN rewiring to output an appropriate response underscoring the critical role of IDPs in cellular decision making. Nonetheless, IDPs are not easily tractable experimentally. Furthermore, in the absence of a reference conformation, discerning the energy landscape representation of the weakly funneled IDPs in terms of reaction coordinates is challenging. To understand conformational dynamics in real time and decipher how IDPs recognize multiple binding partners with high specificity, several sophisticated knowledge-based and physics-based in silico sampling techniques have been developed. Here, using specific examples, we highlight recent advances in energy landscape visualization and molecular dynamics simulations to discern conformational dynamics and discuss how the conformational preferences of IDPs modulate their function, especially in phenotypic switching. Finally, we discuss recent progress in identifying small molecules targeting IDPs underscoring the potential therapeutic value of IDPs. Understanding structure and function of IDPs can not only provide new insight on cellular decision making but may also help to refine and extend Anfinsen's structure/function paradigm.

Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design

We review the use of molecular dynamics (MD) simulation as a drug design tool in the context of the role that the lipid membrane can play in drug action, i.e., the interaction between candidate drug molecules and lipid membranes. In the standard "lock and key" paradigm, only the interaction between the drug and a specific active site of a specific protein is considered; the environment in which the drug acts is, from a biophysical perspective, far more complex than this. The possible mechanisms though which a drug can be designed to tinker with physiological processes are significantly broader than merely fitting to a single active site of a single protein. In this paper, we focus on the role of the lipid membrane, arguably the most important element outside the proteins themselves, as a case study. We discuss work that has been carried out, using MD simulation, concerning the transfection of drugs through membranes that act as biological barriers in the path of the drugs, the behavior of drug molecules within membranes, how their collective behavior can affect the structure and properties of the membrane and, finally, the role lipid membranes, to which the vast majority of drug target proteins are associated, can play in mediating the interaction between drug and target protein. This review paper is the second in a two-part series covering MD simulation as a tool in pharmaceutical research; both are designed as pedagogical review papers aimed at both pharmaceutical scientists interested in exploring how the tool of MD simulation can be applied to their research and computational scientists interested in exploring the possibility of a pharmaceutical context for their research.

Met35 Oxidation Hinders Aβ25-35 Peptide Aggregation within the Dimyristoylphosphatidylcholine Bilayer

Using all-atom explicit solvent replica exchange molecular dynamics simulations, we studied the aggregation of oxidized (ox) Aβ25-35 peptides into dimers mediated by the zwitterionic dimyristoylphosphatidylcholine (DMPC) lipid bilayer. By comparing oxAβ25-35 aggregation with that observed for reduced and phosphorylated Aβ25-35 peptides, we elucidated plausible impact of post-translational modifications on cytotoxicity of Aβ peptides involved in Alzheimer's disease. We found that Met35 oxidation reduces helical propensity in oxAβ25-35 peptides bound to the lipid bilayer and enhances backbone fluctuations. These factors destabilize the wild-type head-to-tail dimer interface and lower the aggregation propensity. Met35 oxidation diversifies aggregation pathways by adding monomeric species to the bound conformational ensemble. The oxAβ25-35 dimer becomes partially expelled from the DMPC bilayer and as a result inflicts limited disruption to the bilayer structure compared to wild-type Aβ25-35. Interestingly, the effect of Ser26 phosphorylation is largely opposite, as it preserves the wild-type head-to-tail aggregation interface and strengthens, not weakens, aggregation propensity. The differing effects can be attributed to the sequence locations of these post-translational modifications, since in contrast to Ser26 phosphorylation, Met35 oxidation directly affects the wild-type C-terminal aggregation interface. A comparison with experimental data is provided.