Enhanced Sampling Methods for Molecular Dynamics

Nyhet

Algorithms, Implementations, and Applications

Häftad, Engelska, 2027

2 499 kr

Kommande

Enhanced Sampling Methods for Molecular Dynamics: Algorithms, Implementations, and Applications covers sampling techniques for molecular dynamics studies of equilibrium and kinetics, discussing the theory, algorithm, and implementation of techniques for equilibrium studies, such as Umbrella Sampling, Replica Exchange, Generalized Ensembles, and Metadynamics. The book considers exact and approximate approaches of enhanced sampling, their speed, rate of convergence, and accuracy. Chapters consider path integral formulation, Weighted Ensemble, Transition Path Sampling, and Milestoning.
Finally, simple, detailed examples illustrate enhancements and prepare the reader for their use in more complex systems, making this an ideal resource for computational chemists, biochemists (graduate students and postdoctoral fellows), and computational and theoretical scientists who study molecular processes.

Outlines the rigorous formulation and comparison of different algorithms
Provides simple, practical “toy” models for practice to help readers understand how to use them for MD
Includes an analysis of “real-life," complex applications to demonstrate the capabilities of enhanced sampling approaches
Helps readers answer critical questions in their own work: what are the bottlenecks involved in simulating a system, what enhanced simulation methods would fit my specific system, what observables are computable, and how to do I analyze the results effectively?

Produktinformation

Utgivningsdatum2027-07-01
Mått191 x 235 x undefined mm
FormatHäftad
SpråkEngelska
Antal sidor560
FörlagElsevier Science
ISBN9780443328220

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Ron Elber studied chemistry and physics at the Hebrew University of Jerusalem and received his BSc degree in 1981. He continued his studies toward a Ph.D. at the Hebrew University in theoretical chemistry, which he obtained in 1984. He was on the faculty of the University of Illinois at Chicago, the Hebrew University, Cornell University, and the University of Texas at Austin. At present, He is retired from the University of Texas at Austin but is still a core faculty at the Oden Institute for Computational Engineering and Sciences at the University of Texas at Austin and a Founder of the company MiTOMED Pharma. For almost give decades he has worked in the field of computational statistical mechanics and Molecular Dynamics simulations of biological systems. He introduced several new methodologies that include techniques to compute reaction pathways in complex systems and the method of Milestoning to extend the time scales of straightforward Molecular Dynamics simulation. He has more than 220 publications and an H index of 63.

1. Introduction: “To understand it, simulate it2. Coarse variables and reaction coordinates3. Rough energy landscapes, why is it a problem?4. Computational statistical mechanics of equilibrium5. Computational and experimental observables in equilibrium7. The first enhanced sampling method is umbrella sampling8. Computing free energy differences9. Flattening free energy landscapes as a function of coarse variables10. The energy as a reaction coordinate11. The temperature as a reaction coordinate12. Sampling kinetic observables with trajectories13. Computing reaction coordinates from reactive trajectories14. Statistical Learning of reaction space15. Enhancing the sampling of complete trajectories16. Exact estimation of the fluxes of reactive trajectories17. The first hitting point distribution18. Approximating the first hitting point distribution19. Computing kinetic observables with trajectory fragments20. Kinetics on a network21. Experimental data as a tool to enhance simulations22. Simulating very large systems23. Which method should I use?24. Discussion of remaining challenges