Free Energy Landscape (FEL) Analysis of MD Trajectories: From RMSD and Rg to Gibbs Surfaces

By BioDockify Computational Research Team · October 17, 2026 · MD Analysis

How to turn an MD trajectory into a free energy landscape: choosing reaction coordinates (RMSD, radius of gyration, distances), binning and Boltzmann inversion, sham-style 2D Gibbs surfaces, reading basins and barriers, and the sampling-time trap that invalidates most student FEL plots.

Read the complete article with tables, code and references on BioDockify.

Key References

• Abraham, M.J. et al. GROMACS: high performance molecular simulations through multi-level parallelism. SoftwareX 1-2, 19-25 (2015). DOI: 10.1016/j.softx.2015.06.001
• Eastman, P. et al. OpenMM 7. PLoS Comput. Biol. 13, e1005659 (2017). DOI: 10.1371/journal.pcbi.1005659
• Shaw, D.E. et al. Atomic-level characterization of the structural dynamics of proteins. Science 330, 341-346 (2010).
• Bottaro, S., Bengtsen, T. & Lindorff-Larsen, K. Integrating molecular dynamics and experimental data with Bayesian/maximum-entropy reweighting. Methods Mol. Biol. 2112, 219-240 (2020).

Scope & Limitations

An FEL is only as meaningful as its sampling - landscapes from under-sampled trajectories show structure that is noise, not physics Two-dimensional projections can hide basins that are distinct in higher dimensions; treat FEL surfaces as maps, not proofs