Multidimensional Langevin Modeling of Nonoverdamped Dynamics.
Based on a given time series, data-driven Langevin modeling aims to construct a low-dimensional dynamical model of the underlying system. When dealing with physical data as provided by, e.g., all-atom molecular dynamics simulations, effects due to small damping may be important to correctly describe the statistics (e.g., the energy landscape) and the dynamics (e.g., transition times). To include these effects in a dynamical model, an algorithm that propagates a second-order Langevin scheme is derived, which facilitates the treatment of multidimensional data. Adopting extensive molecular dynamics simulations of a peptide helix, a five-dimensional model is constructed that successfully forecasts the complex structural dynamics of the system. Neglect of small damping effects, on the other hand, is shown to lead to significant errors and inconsistencies.
Biomolecular Dynamics, Institute of Physics, Albert Ludwigs University, 79104 Freiburg, Germany.
Norbert
N
Schaudinnus
Biomolecular Dynamics, Institute of Physics, Albert Ludwigs University, 79104 Freiburg, Germany.
Björn
B
Bastian
Institute of Physical and Theoretical Chemistry, Goethe University, 60438 Frankfurt, Germany.
Rainer
R
Hegger
Biomolecular Dynamics, Institute of Physics, Albert Ludwigs University, 79104 Freiburg, Germany.
Gerhard
G
Stock
D000465:Algorithms; D000621:Aminoisobutyric Acids / Q000737:chemistry; D008390:Markov Chains; D008962:Models, Theoretical; D056004:Molecular Dynamics Simulation; D010455:Peptides / Q000737:chemistry*; D017433:Protein Structure, Secondary
D000621:Aminoisobutyric Acids; D010455:Peptides; C100049:2-aminoisobutyric acid