Enhanced Sampling Methods for Molecular Dynamics

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.

Table of Contents:
1. Introduction: “To understand it, simulate it” 2. Coarse variables and reaction coordinates 3. Rough energy landscapes, why is it a problem? 4. Computational statistical mechanics of equilibrium 5. Computational and experimental observables in equilibrium 7. The first enhanced sampling method is umbrella sampling 8. Computing free energy differences 9. Flattening free energy landscapes as a function of coarse variables 10. The energy as a reaction coordinate 11. The temperature as a reaction coordinate 12. Sampling kinetic observables with trajectories 13. Computing reaction coordinates from reactive trajectories 14. Statistical Learning of reaction space 15. Enhancing the sampling of complete trajectories 16. Exact estimation of the fluxes of reactive trajectories 17. The first hitting point distribution 18. Approximating the first hitting point distribution 19. Computing kinetic observables with trajectory fragments 20. Kinetics on a network 21. Experimental data as a tool to enhance simulations 22. Simulating very large systems 23. Which method should I use? 24. Discussion of remaining challenges

About the Author :
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.