# Recent Advances in Maximum Entropy Biasing Techniques for Molecular Dynamics

## TL;DR

This review discusses recent maximum entropy biasing techniques in molecular dynamics that incorporate experimental data to enhance simulation accuracy, especially for approximate force fields and multiscale processes.

## Contribution

It introduces and reviews the latest experiment directed simulation (EDS) and experiment directed metadynamics (EDM) methods for improved data integration in molecular simulations.

## Key findings

- Applications to ab initio water simulations
- Incorporation of environmental fluctuations in protein complexes
- Enhancement of RNA force fields

## Abstract

This review describes recent advances by the authors and others on the topic of incorporating experimental data into molecular simulations through maximum entropy methods. Methods which incorporate experimental data improve accuracy in molecular simulation by minimally modifying the thermodynamic ensemble. This is especially important where force fields are approximate, such as when employing coarse-grain models, or where high accuracy is required, such as when attempting to mimic a multiscale self-assembly process. The authors review here the experiment directed simulation (EDS) and experiment directed metadynamics (EDM) methods that allow matching averages and distributions in simulations, respectively. Important system-specific considerations are discussed such as using enhanced sampling simultaneously, the role of pressure, treating uncertainty, and implementations of these methods. Recent examples of EDS and EDM are reviewed including applications to ab initio molecular dynamics of water, incorporating environmental fluctuations inside of a macromolecular protein complex, improving RNA force fields, and the combination of enhanced sampling with minimal biasing to model peptides.