Molecular Interactions of Alzheimer's Biomarker FDDNP with Aβ Peptide

Abstract

All-atom explicit solvent model and replica exchange molecular dynamics were used to investigate binding of Alzheimer's 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.

Molecular Mechanisms of Alzheimer’s Biomarker FDDNP Binding to Aβ Amyloid Fibril

“…4 Second, Aβ1-40 and Aβ10-40 peptides form similar two-fold symmetry fibril structures. 4,41 Finally, by selecting the same Aβ10-40 peptides used in our previous study 37 we can directly compare FDDNP binding to Aβ monomers and fibrils. 5 ligand-ligand contact occurs, if the distance between the centers of mass of any FDDNP structural groups from two ligands is less than 6.5Å.…”

“…1b) was performed using CHARMM General Force Field as reported previously. 37 In all, the simulation system included six amino-truncated Aβ10 − 40 peptides (P1-P6) forming a two-fold symmetry hexameric fibril fragment and six FDDNP ligands ( Fig. 1a).…”

“…[30][31][32][33][34][35][36] In our previous study, we have used replica exchange molecular dynamics (REMD) simulations to probe binding of FDDNP ligands to amino-truncated Aβ10-40 monomers. 37 We showed that at two concentrations FDDNP binds with high affinity to the two sites in Aβ10-40 monomer located near the central hydrophobic cluster and at the peptide C-terminal. In line with the experiments on FDDNP binding to Aβ fibrils, hydrophobic effect appears to be the dominant factor controlling ligand binding to Aβ monomer.…”

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

“…In all, we have investigated four all-atom protein force fields and two explicit water models [ 37 , 38 ] resulting in five simulation systems, which utilized CHARMM36 [ 39 ] with modified TIP3P water model (denoted as C36), CHARMM36 with standard TIP3P water model (C36s), CHARMM22* with modified TIP3P water model (C22*) [ 40 ], CHARMM22 with CMAP corrections and modified TIP3P water model (C22cmap) [ 41 ], and OPLS-AA with modified TIP3P water model (OPLS-AA) [ 42 ]. The C22cmap system was already studied by us previously [ 29 , 43 , 44 ] and is used here to expand the force fields comparison. All simulation systems contained a single A β 10-40 peptide, 4959 water molecules, and one sodium ion to set the net system charge to zero.…”

Recognition of the HIV Capsid by the TRIM5α Restriction Factor Is Mediated by a Subset of Pre-Existing Conformations of the TRIM5α SPRY Domain

“…28 REMD has become the method of choice for problems involving major conformational rearrangements and disorder-to-order transitions, such as chaperone-assisted folding, 29 coupled folding and binding of intrinsically disordered proteins, 30 and binding of proteins to short disordered peptides. 31 REMD may prove particularly powerful for the SPRY domain modeling because, on the one hand, the resulting trajectories can be validated using available NMR-derived relaxation and nuclear Overhauser effect (NOE) data, whereas on the other, REMD trajectories can provide a much more exhaustive picture of the conformational repertoire of the SPRY domain than the conventional simulated-annealing approaches. Simulated-annealing calculations that use NMR-derived distance and angle restraints are not optimal in the regions with significant disorder because the NOE restrains are usually sparse in the mobile protein segments and may arise from distinct protein conformations.…”