The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Adaptive biasing force method for scalar and vector free energy calculations
Abstract
In free energy calculations based on thermodynamic integration, it is necessary to compute the derivatives of the free energy as a function of one (scalar case) or several (vector case) order parameters. We derive in a compact way a general formulation for evaluating these derivatives as the average of a mean force acting on the order parameters, which involves first derivatives with respect to both Cartesian coordinates and time. This is in contrast with the previously derived formulas, which require first and second derivatives of the order parameter with respect to Cartesian coordinates. As illustrated in a concrete example, the main advantage of this new formulation is the simplicity of its use, especially for complicated order parameters. It is also straightforward to implement in a molecular dynamics code, as can be seen from the pseudocode given at the end. We further discuss how the approach based on time derivatives can be combined with the adaptive biasing force method, an enhanced sampling technique that rapidly yields uniform sampling of the order parameters, and by doing so greatly improves the efficiency of free energy calculations. Using the backbone dihedral angles Φ and Ψ in N-acetylalanyl-N′-methylamide as a numerical example, we present a technique to reconstruct the free energy from its derivatives, a calculation that presents some difficulties in the vector case because of the statistical errors affecting the derivatives.
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Using collective variables to drive molecular dynamics simulations
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Improved Reweighting of Accelerated Molecular Dynamics Simulations for Free Energy Calculation
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Spectral gap optimization of order parameters for sampling complex molecular systems
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CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed
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Free Energy Surface Reconstruction from Umbrella Samples Using Gaussian Process Regression
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Metadata
- Authors
- Darve, E., Rodríguez-Gómez, D., & Pohorille, A.
- Venue
- The Journal of Chemical Physics
- Publisher
- AIP Publishing
- Published
- 2008-04-11
- Volume
- 128
- Issue
- 14
- Pages
- 144120-144120
- ISSN
- 0021-9606 (ISSN-L)
- 1089-7690
- OpenAlex
- W2042821667
- Cited by
- 871
- References
- 53
- FWCI
- 5.09
- Type
- journal article
- Language
- en
- Open access
- closed
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