%0 Journal Article %1 Ahn2017CAS-WE %A Ahn, Surl-Hee %A Grate, Jay W. %A Darve, Eric F. %B The Journal of Chemical Physics %D 2017 %I American Institute of Physics %J The Journal of Chemical Physics %K committor-probabilities enhanced-sampling md molecular-dynamics transition-path-theory transition-probabilities we weighted-ensemble %N 7 %P 074115-- %R 10.1063/1.4999097 %T Efficiently sampling conformations and pathways using the concurrent adaptive sampling (CAS) algorithm %U https://doi.org/10.1063/1.4999097 %V 147 %X Molecular dynamics simulations are useful in obtaining thermodynamic and kinetic properties of bio-molecules, but they are limited by the time scale barrier. That is, we may not obtain properties’ efficiently because we need to run microseconds or longer simulations using femtosecond time steps. To overcome this time scale barrier, we can use the weighted ensemble (WE) method, a powerful enhanced sampling method that efficiently samples thermodynamic and kinetic properties. However, the WE method requires an appropriate partitioning of phase space into discrete macrostates, which can be problematic when we have a high-dimensional collective space or when little is known a priori about the molecular system. Hence, we developed a new WE-based method, called the “Concurrent Adaptive Sampling (CAS) algorithm,” to tackle these issues. The CAS algorithm is not constrained to use only one or two collective variables, unlike most reaction coordinate-dependent methods. Instead, it can use a large number of collect...

@article{Ahn2017CAS-WE, abstract = {Molecular dynamics simulations are useful in obtaining thermodynamic and kinetic properties of bio-molecules, but they are limited by the time scale barrier. That is, we may not obtain properties’ efficiently because we need to run microseconds or longer simulations using femtosecond time steps. To overcome this time scale barrier, we can use the weighted ensemble (WE) method, a powerful enhanced sampling method that efficiently samples thermodynamic and kinetic properties. However, the WE method requires an appropriate partitioning of phase space into discrete macrostates, which can be problematic when we have a high-dimensional collective space or when little is known a priori about the molecular system. Hence, we developed a new WE-based method, called the “Concurrent Adaptive Sampling (CAS) algorithm,” to tackle these issues. The CAS algorithm is not constrained to use only one or two collective variables, unlike most reaction coordinate-dependent methods. Instead, it can use a large number of collect...}, added-at = {2018-05-11T16:17:52.000+0200}, author = {Ahn, Surl-Hee and Grate, Jay W. and Darve, Eric F.}, biburl = {https://www.bibsonomy.org/bibtex/291f9d46f51b170f61f69e5fb4004d9e9/salotz}, booktitle = {The Journal of Chemical Physics}, comment = {doi: 10.1063/1.4999097}, description = {Efficiently sampling conformations and pathways using the concurrent adaptive sampling (CAS) algorithm: The Journal of Chemical Physics: Vol 147, No 7}, doi = {10.1063/1.4999097}, interhash = {5420afbb254bfdd2d4232e1c6aac3d66}, intrahash = {91f9d46f51b170f61f69e5fb4004d9e9}, issn = {00219606}, journal = {The Journal of Chemical Physics}, keywords = {committor-probabilities enhanced-sampling md molecular-dynamics transition-path-theory transition-probabilities we weighted-ensemble}, month = aug, number = 7, pages = {074115--}, publisher = {American Institute of Physics}, timestamp = {2018-05-11T16:17:52.000+0200}, title = {Efficiently sampling conformations and pathways using the concurrent adaptive sampling (CAS) algorithm}, url = {https://doi.org/10.1063/1.4999097}, volume = 147, year = 2017 }