Enhanced sampling in molecular dynamics: Targeting specific collective variables

Mark Tuckerman
New York University
Chemistry and Courant Institute

One of the computational grand challenge problems is the development of methodology capable of sampling conformational equilibria in systems characterized by rough energy landscapes. If met, many important problems, notably structure prediction for complex molecules and the discovery of the polymorphism in molecular crystals could be significantly impacted, to name just a few. In this tutorial, I will discuss several popular techniques used in conjunction with molecular dynamics in order to enhance sampling of conformational equilibria and generate multidimensional free energy landscapes. Specifically, the techniques I will describe targets a set of collective variables (CVs). CVs are functions of the primitive Cartesian coordinates in a system that are ostensibly capable of distinguishing different relevant structures of a system. As the barriers between these different structures in the subspace of the chosen CVs can often be quite high, which is why these CVs are targeted for the enhanced sampling. The techniques that will be the focus of this tutorial include metadynamics, adaptive force-biasing, temperature –accelerated molecular dynamics (also known as adiabatic free-energy dynamics), and the reference potential spatial warping algorithm. The basic strategy of such approaches, their advantages, and their limitations in different applications will be discussed.

Presentation (PDF File)

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