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Communication: Estimating the initial biasing potential for λ-local-elevation umbrella-sampling (λ-LEUS) simulations via slow growth
2. H. Liu, A. E. Mark, and W. F. van Gunsteren, “Estimating the relative free energy of different molecular states with respect to a single reference state,” J. Phys. Chem. 100, 9485 (1996).
3. J. Chen, W. Im, and C. L. Brooks III, “Balancing solvation and intramolecular interactions: Toward a consistent generalized Born force field,” J. Am. Chem. Soc. 128, 3728 (2006).
4. C. D. Christ and W. F. van Gunsteren, “Multiple free energies from a single simulation: Extending enveloping distribution sampling to nonoverlapping phase-space distributions,” J. Chem. Phys. 128, 174112-1 (2008).
9. B. Tidor, “Simulated annealing on free energy surfaces by a combined molecular dynamics and Monte Carlo approach,” J. Phys. Chem. 97, 1069 (1993).
11. N. S. Bieler, R. Häuselmann, and P. H. Hünenberger, “Local elevation umbrella sampling applied to the calculation of alchemical free-energy changes via λ-dynamics: The λ-LEUS scheme,” J. Chem. Theory Comput. 10, 3006 (2014).
12. J. L. Knight and C. L. Brooks III, “Applying efficient implicit nongeometric constraints in alchemical free energy simulations,” J. Comput. Chem. 32, 3423 (2011).
13. J. L. Knight and C. L. Brooks III, “Multisite λ-dynamics for simulated structure-activity relationship studies,” J. Chem. Theory Comput. 7, 2728 (2011).
14. S. Donnini, F. Tegeler, G. Groenhof, and H. Grubmüller, “Constant pH molecular dynamics in explicit solvent with λ-dynamics,” J. Chem. Theory Comput. 7, 1962 (2011).
15. P. Wu, X. Hu, and W. Yang, “λ-metadynamics approach to compute absolute solvation free energy,” J. Phys. Chem. Lett. 2, 2099 (2011).
16. L. Zheng and W. Yang, “Practically efficient and robust free energy calculations: Double-integration orthogonal space tempering,” J. Chem. Theory Comput. 8, 810 (2012).
17. S. Donnini, F. Tegeler, G. Groenhof, and H. Grubmüller, “Correction to constant pH molecular dynamics in explicit solvent with λ-dynamics,” J. Chem. Theory Comput. 9, 3261 (2013).
18. H. S. Hansen and P. H. Hünenberger, “Using the local elevation method to construct optimized umbrella sampling potentials: Calculation of the relative free energies and interconversion barriers of glucopyranose ring conformers in water,” J. Comput. Chem. 31, 1 (2010).
21. G. J. Martyna, M. L. Klein, and M. Tuckerman, “Nosé-Hoover chains: The canonical ensemble via continuous dynamics,” J. Chem. Phys. 97, 2635 (1992).
22. D. Steiner, C. Oostenbrink, F. Diederich, M. Zürcher, and W. F. van Gunsteren, “Calculation of binding free energies of inhibitors to plasmepsin II,” J. Comput. Chem. 32, 1801 (2011).
23. D. A. Pearlman and P. A. Kollman, “The lag between the Hamiltonian and the system configuration in free energy perturbation calculations,” J. Chem. Phys 91, 7831 (1989).
24. H. S. Hansen and P. H. Hünenberger, “Ball-and-stick local elevation umbrella sampling: Molecular simulations involving enhanced sampling within conformational or alchemical subspaces of low internal dimensionalities, minimal irrelevant volume and problem-adapted geometries,” J. Chem. Theory Comput. 6, 2622 (2010).
25. T. P. Straatsma and H. J. C. Berendsen, “Free energy of ionic hydration: Analysis of a thermodynamic integration technique to evaluate free energy differences by molecular dynamics simulations,” J. Chem. Phys. 89, 5876 (1988).
28. V. Babin, C. Roland, and C. Sagui, “Adaptively biased molecular dynamics for free energy calculations,” J. Chem. Phys. 128, 134101-1 (2008).
29. G. H. Golub and C. F. van Loan, Matrix Computations (Johns Hopkins University Press, London, 1996).
32. I. Dabo, B. Kozinsky, N. E. Singh-Miller, and N. Marzari, “Electrostatics in periodic boundary conditions and real-space corrections,” Phys. Rev. B 77, 115139-1 (2008).
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In a recent article [Bieler et al. , J. Chem. Theory Comput.10, 3006–3022 (2014)], we introduced a combination of the λ-dynamics (λD) approach for calculating alchemical free-energy differences and of the local-elevation umbrella-sampling (LEUS) memory-based biasing method to enhance the sampling along the alchemical coordinate. The combined scheme, referred to as λ-LEUS, was applied to the perturbation of hydroquinone to benzene in water as a test system, and found to represent an improvement over thermodynamic integration (TI) in terms of sampling efficiency at equivalent accuracy. However, the preoptimization of the biasing potential required in the λ-LEUS method requires “filling up” all the basins in the potential of mean force. This introduces a non-productive pre-sampling time that is system-dependent, and generally exceeds the corresponding equilibration time in a TI calculation. In this letter, a remedy is proposed to this problem, termed the slow growth memory guessing (SGMG) approach. Instead of initializing the biasing potential to zero at the start of the preoptimization, an approximate potential of mean force is estimated from a short slow growth calculation, and its negative used to construct the initial memory. Considering the same test system as in the preceding article, it is shown that of the application of SGMG in λ-LEUS permits to reduce the preoptimization time by about a factor of four.
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