Christopher Lockhart

Alzheimer’s Aβ10–40 Peptide Binds and Penetrates DMPC Bilayer: An Isobaric–Isothermal Replica Exchange Molecular Dynamics Study

Using all-atom explicit solvent model and isobaric-isothermal replica exchange molecular dynamics, we studied binding of Aβ10-40 monomers to zwitterionic DMPC bilayer. Our simulations suggest three main conclusions. First, binding of Aβ10-40 monomer to the DMPC bilayer causes dramatic structural transition in the peptide resulting in the formation of stable helical structure in the C-terminal. In addition, binding to the lipid bilayer induces the formation of intrapeptide Asp23-Lys28 salt bridge. We argue that the emergence of helix is the consequence of hidden helix propensity harbored in the Aβ10-40 C-terminal. This propensity is revealed by the lipids cross-bridging amino acids in helical conformations and by significant hydrophobic moment of the C-terminal. Second, the central hydrophobic cluster and, particularly, the C-terminal of Aβ10-40 not only govern binding to the bilayer but also penetrate into bilayer core. In contrast, the polar N-terminal and turn region form interactions mainly with the bilayer surface. Third, our simulations suggest that upon Aβ10-40 binding to the bilayer a highly heterogeneous local environment emerges along Aβ10-40 chain. The N-terminal is exposed to polar well-hydrated medium, whereas the C-terminal is largely shielded from water residing in mostly hydrophobic environment. The implication of our results is that Aβ aggregation mediated by zwitterionic lipid bilayer is likely to be different from that in bulk water.

Molecular Interactions of Alzheimer's Biomarker FDDNP with Aβ Peptide

All-atom explicit solvent model and replica exchange molecular dynamics were used to investigate binding of Alzheimers biomarker FDDNP to the Aβ(10-40) monomer. At low and high concentrations, FDDNP binds with high affinity to two sites in the Aβ(10-40) monomer located near the central hydrophobic cluster and in the C-terminal. Analysis of ligand- Aβ(10-40) interactions at both concentrations identifies hydrophobic effect as a main binding factor. However, with the increase in ligand concentration the interactions between FDDNP molecules also become important due to strong FDDNP self-aggregation propensity and few specific binding locations. As a result, FDDNP ligands partially penetrate the core of the Aβ(10-40) monomer, forming large self-aggregated clusters. Ligand self-aggregation does not affect hydrophobic interactions as a main binding factor or the location of binding sites in Aβ(10-40). Using the Aβ(10-40) conformational ensemble in ligand-free water as reference, we show that FDDNP induces minor changes in the Aβ(10-40) secondary structure at two ligand concentrations studied. At the same time, FDDNP significantly alters the peptide tertiary fold in a concentration-dependent manner by redistributing long-range, side-chain interactions. We argue that because FDDNP does not change Aβ(10-40) secondary structure, its antiaggregation effect is likely to be weak. Our study raises the possibility that FDDNP may serve as a biomarker of not only Aβ fibril species, but of monomers as well.

Revealing hidden helix propensity in Aβ peptides by molecular dynamics simulations.

Using all-atom explicit solvent model and exhaustive replica exchange molecular dynamics simulations we studied the conformational ensembles of several amino-truncated Aβ peptides. In our simulations we specifically monitored the formation of helix structure in the C-terminals of various Aβ fragments. We show that the equilibrium distributions of structures adopted by Aβ23-40 and Aβ10-40 are similar, but sharply distinct from the conformational ensemble of Aβ29-40. The latter features a stable helical structure not present in longer fragments. Because the λ-expansion method applied to Aβ23-40 identified Lys28 as the residue producing the strongest impact on the C-terminal helix structure, we hypothesized that addition of a single Lys28 to Aβ29-40 would change the peptides conformational ensemble. REMD simulations of Aβ28-40 confirmed this expectation by showing that in this peptide the helix conformation is destabilized and it adopts structures similar to those of Aβ23-40 and Aβ10-40. Therefore, a major conformational switch in the Aβ C-terminal occurs by truncating Aβ peptide after the position Lys28. By comparing our findings with previous studies we argue that Aβ C-terminal harbors helical propensity, which can be revealed by various factors, including environment, ligand binding, or sequence truncation.

Is the Conformational Ensemble of Alzheimer’s Aβ10-40 Peptide Force Field Dependent?

By applying REMD simulations we have performed comparative analysis of the conformational ensembles of amino-truncated Aβ10-40 peptide produced with five force fields, which combine four protein parameterizations (CHARMM36, CHARMM22*, CHARMM22/cmap, and OPLS-AA) and two water models (standard and modified TIP3P). Aβ10-40 conformations were analyzed by computing secondary structure, backbone fluctuations, tertiary interactions, and radius of gyration. We have also calculated Aβ10-40 3JHNHα-coupling and RDC constants and compared them with their experimental counterparts obtained for the full-length Aβ1-40 peptide. Our study led us to several conclusions. First, all force fields predict that Aβ adopts unfolded structure dominated by turn and random coil conformations. Second, specific TIP3P water model does not dramatically affect secondary or tertiary Aβ10-40 structure, albeit standard TIP3P model favors slightly more compact states. Third, although the secondary structures observed in CHARMM36 and CHARMM22/cmap simulations are qualitatively similar, their tertiary interactions show little consistency. Fourth, two force fields, OPLS-AA and CHARMM22* have unique features setting them apart from CHARMM36 or CHARMM22/cmap. OPLS-AA reveals moderate β-structure propensity coupled with extensive, but weak long-range tertiary interactions leading to Aβ collapsed conformations. CHARMM22* exhibits moderate helix propensity and generates multiple exceptionally stable long- and short-range interactions. Our investigation suggests that among all force fields CHARMM22* differs the most from CHARMM36. Fifth, the analysis of 3JHNHα-coupling and RDC constants based on CHARMM36 force field with standard TIP3P model led us to an unexpected finding that in silico Aβ10-40 and experimental Aβ1-40 constants are generally in better agreement than these quantities computed and measured for identical peptides, such as Aβ1-40 or Aβ1-42. This observation suggests that the differences in the conformational ensembles of Aβ10-40 and Aβ1-40 are small and the former can be used as proxy of the full-length peptide. Based on this argument, we concluded that CHARMM36 force field with standard TIP3P model produces the most accurate representation of Aβ10-40 conformational ensemble.

Calcium Enhances Binding of Aβ Monomer to DMPC Lipid Bilayer

Using isobaric-isothermal replica-exchange molecular dynamics and the all-atom explicit-solvent model, we studied the equilibrium binding of Aβ monomers to a zwitterionic dimyristoylphosphatidylcholine (DMPC) bilayer coincubated with calcium ions. Using our previous replica-exchange molecular dynamics calcium-free simulations as a control, we reached three conclusions. First, calcium ions change the tertiary structure of the bound Aβ monomer by destabilizing several long-range intrapeptide interactions, particularly the salt bridge Asp(23)-Lys(28). Second, calcium strengthens Aβ peptide binding to the DMPC bilayer by enhancing electrostatic interactions between charged amino acids and lipid polar headgroups. As a result, Aβ monomer penetrates deeper into the bilayer, making disorder in proximal lipids and bilayer thinning more pronounced. Third, because calcium ions demonstrate strong affinity to negatively charged amino acids, a considerable influx of calcium into the area proximal to the bound Aβ monomer is observed. Consequently, the localizations of negatively charged amino acids and calcium ions in the Aβ binding footprint overlap. Based on our data, we propose a mechanism by which calcium ions strengthen Aβ-bilayer interactions. This mechanism involves two factors: 1) calcium ions make the DMPC bilayer partially cationic and thus attractive to the anionic Aβ peptide; and 2) destabilization of the Asp(23)-Lys(28) salt bridge makes Lys(28) available for interactions with the bilayer. Finally, we conclude that a single Aβ monomer does not promote permeation of calcium ions through the zwitterionic bilayer.

Greedy replica exchange algorithm for heterogeneous computing grids

AbstractReplica exchange molecular dynamics (REMD) has become a valuable tool in studying complex biomolecular systems. However, its application on distributed computing grids is limited by the heterogeneity of this environment. In this study, we propose a REMD implementation referred to as greedy REMD (gREMD) suitable for computations on heterogeneous grids. To decentralize replica management, gREMD utilizes a precomputed schedule of exchange attempts between temperatures. Our comparison of gREMD against standard REMD suggests four main conclusions. First, gREMD accelerates grid REMD simulations by as much as 40 %. Second, gREMD increases CPU utilization rates in grid REMD by up to 60 %. Third, we argue that gREMD is expected to maintain approximately constant CPU utilization rates and simulation wall-clock times with the increase in the number of replicas. Finally, we show that gREMD correctly implements the REMD algorithm and reproduces the conformational ensemble of a short peptide sampled in our previous standard REMD simulations. We believe that gREMD can find its place in large-scale REMD simulations on heterogeneous computing grids. Graphical AbstractStandard replica exchange molecular dynamics (REMD) typically requires all replicas to complete prior to initiation of the replica exchange protocol. Greedy REMD decentralizes this process and therefore only requires a replica and its predetermined exchange partner to have finished simulations prior to initiating replica exchange. Because greedy REMD reduces the idle time associated with replica exchange tasks, it becomes particularly well suited for performing REMD on heterogeneous distributed computing environments.

Cholesterol Changes the Mechanisms of Aβ Peptide Binding to the DMPC Bilayer

Using isobaric-isothermal all-atom replica-exchange molecular dynamics (REMD) simulations, we investigated the equilibrium binding of Aβ10-40 monomers to the zwitterionic dimyristoylphosphatidylcholine (DMPC) bilayer containing cholesterol. Our previous REMD simulations, which studied binding of the same peptide to the cholesterol-free DMPC bilayer, served as a control, against which we measured the impact of cholesterol. Our findings are as follows. First, addition of cholesterol to the DMPC bilayer partially expels the Aβ peptide from the hydrophobic core and promotes its binding to bilayer polar headgroups. Using thermodynamic and energetics analyses, we argued that Aβ partial expulsion is not related to cholesterol-induced changes in lateral pressure within the bilayer but is caused by binding energetics, which favors Aβ binding to the surface of the densely packed cholesterol-rich bilayer. Second, cholesterol has a protective effect on the DMPC bilayer structure against perturbations caused by Aβ binding. More specifically, cholesterol reduces bilayer thinning and overall depletion of bilayer density beneath the Aβ binding footprint. Third, we found that the Aβ peptide contains a single cholesterol binding site, which involves hydrophobic C-terminal amino acids (Ile31-Val36), Phe19, and Phe20 from the central hydrophobic cluster, and cationic Lys28 from the turn region. This binding site accounts for about 76% of all Aβ-cholesterol interactions. Because cholesterol binding site in the Aβ10-40 peptide does not contain the GXXXG motif featured in cholesterol interactions with the transmembrane domain C99 of the β-amyloid precursor protein, we argued that the binding mechanisms for Aβ and C99 are distinct reflecting their different conformations and positions in the lipid bilayer. Fourth, cholesterol sharply reduces the helical propensity in the bound Aβ peptide. As a result, cholesterol largely eliminates the emergence of helical structure observed upon Aβ transition from a water environment to the cholesterol-free DMPC bilayer. We explain this effect by the formation of hydrogen bonds between cholesterol and the Aβ backbone, which prevent helix formation. Taken together, we expect that our simulations will advance understanding of a molecular-level mechanism behind the role of cholesterol in Alzheimers disease.