How accurate are your simulations? Effects of confined aqueous volume and AMBER FF99SB and CHARMM22/CMAP force field parameters on structural ensembles of intrinsically disordered proteins: Amyloid-β₄₂ in water

Figures & data

Scheme 1. Amino acid residue sequence of Aβ₄₂.

Figure 1. Calculated cumulative potential energy (U) for Aβ₄₂ in aqueous solution with a water layer of 20 Å (dashed line) and 30 Å (dotted line) for 160 ns, respectively (A); correlation of calculated and experimental Cα chemical shift values obtained from Dr. Michael Zagorski for Aβ₄₂ in an aqueous solution with a water layer of 20 Å (B) and 30 Å (C), respectively.

Table 1. Protocols and standards used in our different simulations.

Simulation Type	Temperature (K)	Pressure (MPa)	Water Model	Potential functions for the Solute	Number of water molecules	Simulation Time	Convergence Time	Corresponding Simulation Results
Classical MD simulations using the NPT ensemble	310	0.1	explicit TIP3P	CHARMM22/CMAP	10314	160 ns	100 ns	Table 2
								Figure 1
								Figure 2
								Figure 3
								Figure 4
Classical MD simulations using the NPT ensemble	310	0.1	Explicit TIP3P	CHARMM22/CMAP	25777	160 ns	100 ns	Table 2
								Figure 1
								Figure 2
								Figure 3
								Figure 4
REMD simulations with special sampling using the NVT ensemble utilizing 24 replicas	310 (closest replica to 310 K)	0.1 (in average)	Implicit Onufriev-Bashford-Case	CHARMM22/CMAP	—	4.8 μs	60 ns	Figure 5
								Figure 6
								Figure 7
								Figure 8
								Figure 9
REMD simulations with special sampling using the NVT ensemble utilizing 24 replicas	310 (closest replica to 310 K)	0.1 (in average)	Implicit Onufriev Basford	AMBER FF99SB	—	4.8 μs	60 ns	Figure 5
								Figure 6
								Figure 7
								Figure 8
								Figure 9
REMD simulations using the NVT ensemble utilizing 32 replicas	310 (closest replica to 310 K)	0.1 (in average)	explicit TIP5P	CHARMM22/CMAP	10314	7.2 μs	60 ns	Figure S3
								Figure S4
								Figure S5
								Figure S6
REMD simulations using the NVT ensemble utilizing 32 replicas	310 (closest replica to 310 K)	0.1 (in average)	explicit TIP5P	AMBER FF99SB	25777	7.2 μs	60 ns	Figure S3
								Figure S4
								Figure S5
								Figure S6

Figure 2. Enthalpic (A) and entropic (B) contributions to the Gibbs free energy values of monomeric Aβ₄₂ conformations in aqueous solution with Vs = 330 nm³ (blue) and Vs = 810 nm³ (red) where Vs presents the volume of water in the solution.

Figure 3. Differences in secondary structure abundances in monomeric Aβ₄₂ in aqueous solution with an increase in confined aqueous volume, corresponding to an increase from Vs = 330 nm³ to Vs = 810 nm³ (Vs is the volume of water).

Figure 4. The intra-molecular peptide interaction (I), intra-molecular hydrogen bond (II), and hydrophobic interactions (III) maps for the Aβ₄₂ monomer in aqueous solution with Vs = 330 nm³ (A) and Vs = 810 nm³ (B) where Vs presents the volume of water.

Table 2. Formed salt bridges along with their abundances in monomeric Aβ₄₂ in aqueous solution with different confined aqueous volume effects, corresponding to water volumes of 330 nm³ and 810 nm³, respectively.

Figure 5. Convergence of Aβ₄₂ simulations via REMD simulations tested using the secondary structure abundances with time.

Figure 6. Radius of gyration values using AMBER FF99SB and CHARMM22/CMAP parameters in an implicit model of water. (A) Cluster 1, (B) Cluster 2, (C) Cluster 3, (D) Cluster 4, (E) Cluster 5.

Figure 7. Secondary structure properties simulated using AMBER FF99SB (Black) and CHARMM22/CMAP (Red) parameters in an implicit water environment; (A) Cluster 1, (B) Cluster 2, (C) Cluster 3, (D) Cluster 4, (E) Cluster 5.

Figure 8. Tertiary structure properties simulated using AMBER FF99SB and CHARMM22/CMAP parameters in an implicit water environment. (A) Cluster 1 using AMBER FF99SB parameters, (B) Cluster 1 using CHARMM22/CMAP parameters, (C) Cluster 2 using AMBER FF99SB parameters, (D) Cluster 2 using CHARMM22/CMAP parameters, (E) Cluster 3 using AMBER FF99SB parameters, (F) Cluster 3 using CHARMM22/CMAP parameters, (G) Cluster 4 using AMBER FF99SB parameters, (H) Cluster 4 using CHARMM22/CMAP parameters, (I) Cluster 5 using AMBER FF99SB parameters, (J) Cluster 5 using CHARMM22/CMAP parameters.

Figure 9. The calculated probability distribution of the distance between the Cγ atom of the Asp23 residue and the Nζ atom of the Lys28 residues for the Aβ₄₂ using AMBER FF99SB and CHARMM22/CMAP parameters in an implicit water environment. Simulations were conducted using AMBER FF99SB (A) and CHARMM22/CMAP parameters (B).