English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Intrinsic map dynamics exploration for uncharted effective free-energy landscapes

MPS-Authors
/persons/resource/persons204781

Covino,  Roberto
Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society;

/persons/resource/persons15259

Hummer,  Gerhard
Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society;
Institute of Biophysics, Goethe University, 60438 Frankfurt am Main, Germany;

Locator
There are no locators available
Fulltext (public)
There are no public fulltexts available
Supplementary Material (public)
There is no public supplementary material available
Citation

Chiavazzo, E., Covino, R., Coifman, R. R., Gear, C. W., Georgiou, A. S., Hummer, G., et al. (2017). Intrinsic map dynamics exploration for uncharted effective free-energy landscapes. Proceedings of the National Academy of Sciences of the United States of America, 114(28), E5494-E5503. doi:10.1073/pnas.1621481114.


Cite as: http://hdl.handle.net/21.11116/0000-0001-279D-3
Abstract
We describe and implement a computer-assisted approach for accelerating the exploration of uncharted effective free-energy surfaces (FESs). More generally, the aim is the extraction of coarse-grained, macroscopic information from stochastic or atomistic simulations, such as molecular dynamics (MD). The approach functionally links the MD simulator with nonlinear manifold learning techniques. The added value comes from biasing the simulator toward unexplored phase-space regions by exploiting the smoothness of the gradually revealed intrinsic low-dimensional geometry of the FES