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Parallel tempering protein

Other exciting applications involved using parallel tempering in connection with available experimental data. For example, Falcioni and Deem [57] used X-ray data to refine structures of zeolites, and Haliloglu et al. [58] refined NMR structural data for proteins (in particular using residual dipolar coupling constraints). [Pg.290]

Another practical limitation in complex applications lies in the fact that, if temperature is used as a control parameter, one needs to worry about the integrity of a system that is heated too much (e.g., water-membrane systems or a protein heated above its denaturation temperature). When issues such as those mentioned above are addressed, parallel tempering can be turned into a powerful and effective means of enhanced conformational sampling for free energies over a range of temperatures for various systems. [Pg.290]

Schug, A. Herges, T. Wenzel, W., All-atom folding of the three-helix HIV accessory protein with an adaptive parallel tempering method, Proteins-Struct. Funct. Bioinform. 2004, 57, 792-798... [Pg.317]

We also folded this protein with the parallel tempering method [12]. We found that the standard approach, which preserves the thermodynamic equilibrium of the simulated populations, did not reach very low energies even for... [Pg.562]

Figure 2. Energies (upper panel) and temperatures (lower panel) of the 30 replica modified parallel tempering simulation of the trp-cage protein reported in the text. The dotted line in the upper panel corresponds to the estimate of the global optimum of the free energy (obtained independently). The lower panel demonstrates a rapid equilibration of the temperatures during the simulation. The upper panel demonstrates the convergence of the energy and the rapid exchange of information between the different replicas as discussed in the text. Figure 2. Energies (upper panel) and temperatures (lower panel) of the 30 replica modified parallel tempering simulation of the trp-cage protein reported in the text. The dotted line in the upper panel corresponds to the estimate of the global optimum of the free energy (obtained independently). The lower panel demonstrates a rapid equilibration of the temperatures during the simulation. The upper panel demonstrates the convergence of the energy and the rapid exchange of information between the different replicas as discussed in the text.
We also performed a simulation of the HIV accessory protein using the adapted parallel tempering method [13]. We used 20 processors of an INTEL XEON PC cluster and ran the simulation for a total of 30 x 10 energy evaluations for each configuration, which corresponds to approximately 500 CPU hours on an 2.4 GHz INTEL XEON processor. All simulations were started... [Pg.565]

The feedback-optimized parallel tempering technique [26] outlined in the previous section has recently been applied to study the folding of the 36-residue chicken villin headpiece sub-domain HP-36 [27]. Since HP-36 is one of the smallest proteins with well-defined secondary and tertiary structure [28] and at the same time with 596 atoms still accessible to numerical simulations, it has recently attracted considerable interest as an example to test novel numerical techniques, including molecular dynamics [29,30] and Monte Carlo [31,32] methods. The experimentally determined structure [28] which is deposited in the Protein Data Bank (PDB code Ivii) is illustrated in the left panel of Fig. 6. [Pg.611]

Applying an all-atom parallel tempering simulation of the protein HP-36 in the ECEPP/2 force field [33] using an implicit solvent model [34] the authors of [27] have measured the diffusion of labeled replicas in temperature space. The simulated temperature interval is chosen such that at the lowest temperature = 250 K the protein is in a folded state and the highest temperature T ax = 1000 K ensures that the protein can fully unfold for the simulated force field. The measured local diffusivity for the random walk between these two extremal temperatures is shown in Fig. 7. A very strong modulation of the local diffusivity is found along the temperature. Note the logarithmic scale of the ordinate. The pronounced minimum of the local diffusivity around T 500 K points to a severe bottleneck in the simulation which by measurements of the specific heat has been identified as the helix-coil... [Pg.611]

Fig. 8. Optimized temperature sets with 20 temperature points for the parallel tempering simnlation of the 36-residue protein HP-36. The initial temperatnre set covers a temperatnre range 250 K < T < 1000 K and concentrates temperatnre points at low temperatures similar to a geometric progression. After the feedback of the local diffusivity temperature points accumulate around the hehx-coil transition at T fs 500 K where the strong suppression of the local diffusivity points to a severe bottleneck... Fig. 8. Optimized temperature sets with 20 temperature points for the parallel tempering simnlation of the 36-residue protein HP-36. The initial temperatnre set covers a temperatnre range 250 K < T < 1000 K and concentrates temperatnre points at low temperatures similar to a geometric progression. After the feedback of the local diffusivity temperature points accumulate around the hehx-coil transition at T fs 500 K where the strong suppression of the local diffusivity points to a severe bottleneck...

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