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. 2019 Jan 16;20(2):370. doi: 10.3390/ijms20020370

Figure 2.

Figure 2

Results from simulations of dialanine peptide in SPC/E water used for the validation of the sampling along NR multiple biasing increments H(B)ab (dLabik(t), adaptive bias MD) and H(B)σ (dLσik(Lik(t)), path-sampling) to accelerate the sampling, which results in a biased action integral Ls and a modification of the un-biased Hamiltonian H(A), which results in a hybrid Hamiltonian H(C). (a) Free energy landscapes as function of backbone dihedral angles Φ and Ψ from simulations at the temperatures 300 K, 350 K, 400 K, and 450 K using multipe path sampling in combination with optimization techniques (using principal components of the biasing Hamiltonian H(B)), a number of NR=10 biases, βmd=β=103, τ1 = 0.5 ps, and τ2 = 0.1 ps. Energy values on the color bar are in units of kBT. (b) Comparison of the logarithm of the transition frequency of the dihedral angle Φ as function of the inverse temperature (300–450 K) in the biased (red and green curve) and 1 μs MD-trajectories (black curve) (blue curve, fit of the biased data to the MD-data for the determination of the linear scaling factor ln(ρ)). In this Kinetic analysis, we determined an acceleration factor ρ equal to 10.68 by which the algorithm accelerates the sampling of dialanine peptide. (c) Static permittivities ϵ(0) as function of MD-simulation time using different coupling α and αmd-parameters in the individual simulations of SPC/E and TIP3P water compared with conventional MD simulations.