impact of ultrafine air - NU Repository

Time evolution of the oligomerization of four Aβ42 peptide monomers (water molecules and ions not shown): A) in the absence of carbonaceous UFPs, B) in the presence of C60, C) in the presence of C60/B[a]P, D) in the presence of C60/4B[a]P. Representative snapshots of the simulated system on the last trajectory (ions and water molecules are not shown): A) system without carbonaceous UFPs, B) system with C60, C) system with C60/B[a]P, D) system with C60 / 4B[a]P.

Introduction

Air Pollution and neurodegenerative diseases
Objectives and Hypotheses
Role of the external collaborators
Research outputs
Thesis overview

Stabilization of the central Aβ24-27 turn region was found to be important for the oligomerization of peptides (Jokar et al., 2020). Schematic representation of the impact of ambient UFPs on human health [adapted from (Longhin et al., 2020, Stone et al., 2017)].

Figure 1. Aβ peptides aggregation and AD pathology [adapted from (Magzoub, 2020)].

Literature Review

Particulate matter (PM), ultrafine particles (UFPs), and its composition
Nanotoxicology and impact of UFPs on human health
Alzheimer’s Disease progression and its relation to Aβ peptide
Experimental studies on the effect of air pollutants and nanoparticles (NPs) on the

In-vitro studies on the effect of air pollutants and NPs
In-vivo effect of air pollutants on neurodegenerative diseases

Computational studies on the effect of air pollutants and NPs on Aβ peptides

Schematic representation of the effect of PM on human health [adapted from (Longhin et al., 2020)]. According to the amyloid cascade theory, Aβ peptide is the main initiator of AD progression (Sun et al., 2015).

Figure 3. Schematic representation of the composition of an ultrafine particle [adapted from (Stone et al., 2017)]

Methodology

MD simulations

In general, the forces acting on all atoms are calculated using a combination of bonded and nonbonded interactions. Similarly, the total forces acting on all atoms are calculated from the potential energy of the system, followed by the calculation of atomic velocity and position.

MD parameters implemented in this study

Simulation box
Energy Minimization
NVT-equilibration
NPT-equilibration
MD production run
Methods of analysis of the MD simulations

The coordinates of the peptide structures used for the MD study were downloaded from the Protein Data Bank (PDB) website. Visual Molecular dynamics (VMD) software was used to visualize the systems under study (Humphrey et al., 1996).

Figure 9. A representative snapshot of the file with the coordinates of atoms in the SO 4 2-

Effect of inorganic water-soluble ions and C 60 on the oligomerization of Aβ 16-21

Introduction

Simulation Methodology

Varying C 60 concentration and composition of water-soluble ions
Effect of ammonium nitrate concentration and presence of C 60
MD study with experimental validations

Particularly considering that the aggregation of the peptides leads to the decrease of the total. The intermolecular interactions were also evaluated using the RDF analysis for the last 10 ns of the MD runs when the systems were equilibrated. Similarly, the average percent composition of the β-sheets in the peptide aggregates was studied in the last 10 ns of the MD runs.

In particular, the time when the total SASA of the peptides would reach the limit values of 60 nm2 (SASA60nm2) and 55 nm2 (SASA55nm2) was estimated. In addition, RDF analysis was used to investigate interactions between peptide segments and ions during the last 10 ns of the simulations when the systems were stabilized.

Table 2. Free energy of hydration of the ion models used in this study.

Results and discussion

Impact of varying C 60 concentration on the peptide oligomerization
Effect of water-soluble ions and the presence of C 60
Effect of ammonium nitrate concentration and presence of C 60
Experimental validations

Time evolution of the total SASA of eight Aβ16-21 peptides in the system without C60 [retrieved from (Kaumbekova et al., 2021)]. According to Figure 15A, the interpeptide interactions were slightly reduced in the presence of the elemental carbon model. Furthermore, the kinetics of early oligomerization was altered by the presence of the C60 molecule.

Moreover, the presence of both nitrates and elemental carbon increased the early oligomerization of the peptides and interpeptide interactions. According to Figure 28B, the fastest kinetics of the early oligomerization was observed in the presence of 0.15 M NH4Cl (SASA34nm2 was reached within 8 ns).

Figure 11. A representative snapshot of the early oligomerization of eight Aβ 16-21 peptides at the beginning and the end of the MD simulations (Aβ 16-21 : blue, water molecules: red and white, C 60 : black): A) solvated in water, in the presence of 0.1

Concluding remarks

Effect of the polycyclic aromatic hydrocarbons (PAHs) and nicotine on the structure

Introduction

Typical PAHs used in our research are B[a]P and phenanthrene (C14H10, with three aromatic rings), which differ in size, number of aromatic rings, and hydrophobicity. They hypothesized that the structure of the peptide monomer would change in the presence of the two PAHs and nicotine, mainly depending on the size and hydrophobicity of the air pollutants. In addition, this chapter studied the aggregation kinetics of four Aβ42 monomers in the presence of B[a]P at different PAH concentrations to examine the effect of increasing the concentration of B[a]P from 5 mM to 50 mM on the early oligomerization of Aβ42 peptides.

It should be noted that high concentrations of Aβ42 peptide monomers and organic pollutants were used to perform MD simulations, compared to concentrations found in human blood or concentrations commonly used for in-vivo studies (Gao et al., 2015), obtain statistically significant results within the constraints of simulation box size and computational time.

Methodology

Effect of PAHs and nicotine on Aβ monomer
Effect of benzo[a]pyrene on the oligomerization

The number of molecules in the studied systems on the effects of PAHs and nicotine on A42 monomer. However, because equilibrium was not established for 200 ns in the system with the phenanthrene molecule, the MD simulation was extended for an additional 100 ns. The results of the simulations were analyzed by SASA, RoG, RMSD, RMSF, H-bonds, secondary structure analyses, intermolecular distances, and intermolecular cluster analyses, as previously mentioned in Section 3.2.

A larger box size was chosen to accommodate an increase in the size of the peptide in the box. Although the amounts of A42 peptide and B[a]P molecules in the simulated systems were significantly higher than the molecular concentrations typically found in human blood (Wirnkor et al., 2019), the ratio of B[a ]P to A 42 monomers, which was 10:1, is equivalent to the molecular ratio used in in vitro research (Wallin et al., 2017).

Table 11. The density of B[a]P, nicotine, and phenanthrene molecules computed at the reference temperature and compared with the literature values

Results and discussion

Structural variation in Aβ monomer in the presence of PAHs and nicotine
Effect of benzo[a]pyrene on the oligomerization

Averaged over the last 20 ns of the MD run, the secondary structure of the A42 peptide monomer in the simulated systems. Furthermore, in the last 20 ns of the simulation, a -bend  region was formed in the A26-32 segment. Compared to the secondary structure of the peptide in the system without any air pollutants with 43% helices, the presence of B[a]P, nicotine and phenanthrene in the simulated systems reduced the percentage of helices to 27%, 31% and 28% respectively (Table 14).

Representative snapshots of simulated systems (ions and water molecules not shown) with specific peptide ends: A) A42 peptide monomerate at the beginning of MD runs, B) A42 peptide monomerate at the end of the simulation in a system with no air pollutants, C) A 42 peptide monomer at the end of the simulation in the system with B[a]P, D) A42 peptide monomer at the end of the simulation in the system with nicotine, E) A 42 peptide monomer at the end of the simulation in the system with phenanthrene. Coulombic and short-range (SR) and long-range (LR) Coulombic and Lennard-Jones potentials between peptides and peptide-B[a]P observed over the last 10 ns of simulations in the systems under study.

Table 14. Averaged throughout the last 20 ns of the MD run, the secondary structure of the A 42 peptide monomer in the simulated systems

Concluding remarks

The molecular interactions were further investigated by performing an energy analysis for the last 10 ns of the MD runs (Table 17). Overall, the presence of PAHs and nicotine changed the secondary structure of the A42 monomer, resulting in the formation of more turns (increasing the percentage amount by 20%), coils (by 17%), bends (by 20%), and -sheets (by 10%) and reduce the alpha helices by 25-50%. Accordingly, the undergone changes in the secondary structure of the peptide monomer indicated that B[a]P, nicotine and phenanthrene can accelerate the progression of AD.

In particular, the presence of four B[a]P molecules at low concentration (5 mM) accelerated peptide tetramerization by 30% and strengthened electrostatic interactions within A42 tetramers. Furthermore, the presence of four B[a]P molecules stabilized the C-terminus of the peptides, suggesting AD progression.

Effect of the carbonaceous ultrafine particles (UFPs) on the structure and

Introduction

Methodology

Modeling elemental and organic carbonaceous UFPs mimic UFP
Effect of the carbonaceous UFPs on the oligomerization

The initial positions of the molecules were changed for each run, while the distances between the peptides and the UFP carbon templates were kept constant at 5 nm at the beginning of the simulations. In addition, Excel's Data Analysis function was used to perform one-factor and two-factor ANOVA analyses, which were used to validate the statistical significance of the results obtained from the SASA, secondary structure, and energies analyses. interaction. A threshold value of 0.05 was used for each ANOVA test and the resulting p-values less than 0.05 were used to confirm the statistical significance of the results.

The concentrations of the A42 monomers were 5 mM, while the concentrations of the carbonaceous UFP models were 1.25 mM in the corresponding systems with UFPs. Representative snapshots of Aβ42 peptide oligomers and carbonaceous UFPs at the beginning of the MD simulations (water molecules and ions not shown): A) in the absence of carbonaceous UFPs, B) in the presence of C60, C) in the presence of C60 /B[a]P, D) in the presence of C60/4B[a]P.

Table 19. The number of molecules in the systems under study on the effect of carbonaceous UFPs on the oligomerization

Results and discussion

Impact of conjugated particles on Aβ monomer
Effect of the carbonaceous UFPs on the oligomerization

Time evolution of the secondary structure of Aβ42 peptide monomer and representative snapshots of the final trajectories in the system with C60 (water molecules and ions are not shown): A) in Run 1, B) in Run 2, C) in Run 3 According to Figure 51 The binding of the peptide monomer and C60/4B[a]P also significantly promoted the formation of bend (18%), bend (24%), and spiral (39%) regions in the structure of the peptide monomers. Time evolution of the secondary structure of four Aβ42 peptides and representative snapshot of the final trajectory in the system with C60 (water molecules and ions not shown).

Time evolution of the secondary structure of the four Aβ42 peptides and a representative snapshot of the final trajectory in the system with C60/B[a]P (water molecules and ions not shown). Helices decreased while turns, turns, and coils increased in the structure of Aβ42.

Figure 46. Representative snapshots of the time-evolution of Aβ 42 peptide monomer structure in three runs of the system with no carbonaceous UFPs: A) Run 1, B) Run 2, C) Run 3

Concluding remarks

Summary of the effects of the studied carbonaceous UFPs on the structure of Aβ42 peptides and the resulting oligomerization. The formation of the helices and bending regions in the structure of the Aβ42 monomer had increased by the end of the simulations. The number of helices in the structure of the Aβ42 monomer was reduced, while the number of turns, turns, and coils was increased.

In comparison, the model of the carbonaceous UFP with OC on the surface of the EC core, represented by C60/B[a]P with a higher specific surface area and lower curvature, facilitated the unfolding of the peptides with the rapid formation of the UFP monomer cluster. Overall, the carbonaceous UFP models used in Chapter 6 increased the kinetics of early oligomerization of the monomers into dimers, with the fastest formation of the tetramer-UFP cluster in the presence of C60/B[a]P .

Conclusion

Summary and main findings

Considering the synergistic effect of ultrafine air pollutants, the presence of two types of air pollutants, such as EC and nitrate ions, accelerated the early oligomerization of the Aβ16-21 peptides. The carbonaceous UFP models used in this MD study affected the structure of the Aβ42 peptide monomer and increased the early oligomerization of the monomers into dimers. Cleaning the air: a review of the effects of particulate air pollution on human health.

The hazardous effects of environmental toxic gases on amyloid beta-peptide aggregation: A theoretical perspective. Role of the N-terminus for the stability of an amyloid-β fibril with threefold symmetry.

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