On the improvement of free-energy calculation from steered molecular dynamics simulations using adaptive stochastic perturbation protocols

PLoS One. 2014 Sep 18;9(9):e101810. doi: 10.1371/journal.pone.0101810. eCollection 2014.

Abstract

The potential of mean force (PMF) calculation in single molecule manipulation experiments performed via the steered molecular dynamics (SMD) technique is a computationally very demanding task because the analyzed system has to be perturbed very slowly to be kept close to equilibrium. Faster perturbations, far from equilibrium, increase dissipation and move the average work away from the underlying free energy profile, and thus introduce a bias into the PMF estimate. The Jarzynski equality offers a way to overcome the bias problem by being able to produce an exact estimate of the free energy difference, regardless of the perturbation regime. However, with a limited number of samples and high dissipation the Jarzynski equality also introduces a bias. In our previous work, based on the Brownian motion formalism, we introduced three stochastic perturbation protocols aimed at improving the PMF calculation with the Jarzynski equality in single molecule manipulation experiments and analogous computer simulations. This paper describes the PMF reconstruction results based on full-atom molecular dynamics simulations, obtained with those three protocols. We also want to show that the protocols are applicable with the second-order cumulant expansion formula. Our protocols offer a very noticeable improvement over the simple constant velocity pulling. They are able to produce an acceptable estimate of PMF with a significantly reduced bias, even with very fast perturbation regimes. Therefore, the protocols can be adopted as practical and efficient tools for the analysis of mechanical properties of biological molecules.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Mechanotransduction, Cellular / physiology*
  • Molecular Dynamics Simulation*
  • Proteins / physiology*
  • Stress, Mechanical*
  • Thermodynamics*

Substances

  • Proteins

Grants and funding

The project was funded by the National Natural Science Foundation of China, grant No. 31071167. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.