Local elevation

(Redirected from Local Elevation)

Local elevation is a technique used in computational chemistry or physics, mainly in the field of molecular simulation (including molecular dynamics (MD) and Monte Carlo (MC) simulations). It was developed in 1994 by Huber, Torda and van Gunsteren [1] to enhance the searching of conformational space in molecular dynamics simulations and is available in the GROMOS software for molecular dynamics simulation (since GROMOS96). The method was, together with the conformational flooding method, [2] the first to introduce memory dependence into molecular simulations. Many recent methods build on the principles of the local elevation technique, including the Engkvist-Karlström, [3] adaptive biasing force, [4] Wang–Landau, metadynamics, adaptively biased molecular dynamics, [5] adaptive reaction coordinate forces, [6] and local elevation umbrella sampling [7] methods. The basic principle of the method is to add a memory-dependent potential energy term in the simulation so as to prevent the simulation to revisit already sampled configurations, which leads to the increased probability of discovering new configurations. The method can be seen as a continuous variant of the Tabu search method.

Algorithm

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Basic step

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The basic step of the algorithm is to add a small, repulsive potential energy function to the current configuration of the molecule such as to penalize this configuration and increase the likelihood of discovering other configurations. This requires the selection of a subset   of the degrees of freedom, which define the relevant conformational variables. These are typically a set of conformationally relevant dihedral angles, but can in principle be any differentiable function of the cartesian coordinates  .

The algorithm deforms the physical potential energy surface by introducing a bias energy, such that the total potential energy is defined as

 

The local elevation bias   depends on the simulation time   and is set to zero at the start of the simulation ( ) and is gradually built as a sum of small, repulsive functions, giving

 ,

where   is a scaling constant and   is a multidimensional, repulsive function with  .

The resulting bias potential will be a sum of all the added functions

 

To reduce the number of added repulsive functions, a common approach is to add the functions to grid points. The original choice of   is to use a multidimensional Gaussian function. However, due to the infinite range of the Gaussian as well as the artifacts that can occur with a sum of gridded Gaussians, a better choice is to apply multidimensional truncated polynomial functions [8] .[9]

Applications

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The local elevation method can be applied to free energy calculations as well as to conformational searching problems. In free energy calculations the local elevation technique is applied to level out the free energy surface along the selected set of variables. It has been shown by Engkvist and Karlström [3] that the bias potential built by the local elevation method will approximate the negative of the free energy surface. The free energy surface can therefore be approximated directly from the bias potential (as done in the metadynamics method) or the bias potential can be used for umbrella sampling (as done in metadynamics with umbrella sampling corrections [10] and local elevation umbrella sampling[7] methods) to obtain more accurate free energies.

References

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  1. ^ Huber, T.; Torda, A.E.; van Gunsteren, W.F. (1994). "Local elevation: A method for improving the searching properties of molecular dynamics simulation". J.Comput.-Aided Mol. Design. 8 (6): 695–708. Bibcode:1994JCAMD...8..695H. doi:10.1007/BF00124016. PMID 7738605. S2CID 15839136.
  2. ^ Grubmüller, H. (1995). "Predicting slow structural transitions in macromolecular systems: conformational flooding" (PDF). Phys. Rev. E. 52 (3): 2893–2906. Bibcode:1995PhRvE..52.2893G. doi:10.1103/PhysRevE.52.2893. hdl:11858/00-001M-0000-000E-CA15-8. PMID 9963736.
  3. ^ a b Engkvist, O.; Karlström, G. (1996). "A method to calculate the probability distribution for systems with large energy barriers". Chem. Phys. 213 (1–3): 63–76. Bibcode:1996CP....213...63E. doi:10.1016/S0301-0104(96)00247-9.
  4. ^ Darve, E.; Pohorille, A. (2001). "Calculating free energies using average force". J. Chem. Phys. 115 (20): 9169–9183. Bibcode:2001JChPh.115.9169D. doi:10.1063/1.1410978. hdl:2060/20010090348. S2CID 5310339.
  5. ^ Babin, V.; Roland, C.; Sagui, C. (2008). "Stabilization of resonance states by an asymptotic Coulomb potential". J. Chem. Phys. 128 (2): 134101/1–134101/7. Bibcode:2008JChPh.128b4101A. doi:10.1063/1.2821102. PMID 18205437.
  6. ^ Barnett, C.B.; Naidoo, K.J. (2009). "Free Energies from Adaptive Reaction Coordinate Forces (FEARCF): An application to ring puckering". Mol. Phys. 107 (8–12): 1243–1250. Bibcode:2009MolPh.107.1243B. doi:10.1080/00268970902852608. S2CID 97930008.
  7. ^ a b Hansen, H.S.; Hünenberger, P.H. (2010). "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): 1–23. doi:10.1002/jcc.21253. PMID 19412904. S2CID 7367058.
  8. ^ Hansen, H.S.; Hünenberger, P.H. (2010). "Enhanced Conformational Sampling in Molecular Dynamics Simulations of Solvated Peptides: Fragment-Based Local Elevation Umbrella Sampling". J. Chem. Theory Comput. 6 (9): 2598–2621. doi:10.1021/ct1003059. PMID 26616064.
  9. ^ Hansen, H.S.; Hünenberger, P.H. (2010). "Ball-and-Stick Local Elevation Umbrella Sampling: Molecular Simulations Involving Enhanced Sampling within Conformational or Alchemical Subspaces of Low Internal Dimensionalities, Minimal Irrelevant Volumes, and Problem-Adapted Geometries". J. Chem. Theory Comput. 6 (9): 2622–2646. doi:10.1021/ct1003065. PMID 26616065.
  10. ^ Babin, V.; Roland, C.; Darden, T.A.; Sagui, C. (2006). "The free energy landscape of small peptides as obtained from metadynamics with umbrella sampling corrections". J. Chem. Phys. 125 (20): 204909. Bibcode:2006JChPh.125t4909B. doi:10.1063/1.2393236. PMC 2080830. PMID 17144742.