We present an algorithm to correct molecular dynamics non-equilibrium simulationsbased on the knowledge of time-dependent experimental data. This is inspired by a similar scheme used for equilibrium simulations , and is based on the principle of maximum caliber that guarantees that as little subjective information as possible is added to a model, besides the available experimental data. We also show that the same algorithm, in the case of simplified models, can be used to speed up the computational time needed by a simulation by one to two orders of magnitude .
Inferential methods can be used to integrate experimental informations and molecular simulations . The maximum entropy principle provides a framework for using equilibrium experimental data and it has been shown that replica-averaged simulations, restrained using a static potential, are a practical and powerful implementation of such principle. Here we show that replica-averaged simulations restrained using a time-dependent potential are equivalent to the principle of maximum caliber , the dynamic version of the principle of maximum entropy, and thus may allow to integrate time-resolved data in molecular dynamics simulations. We provide an analytical proof of the equivalence as well as a computational validation making use of simple models and synthetic data. Some limitations and possible solutions are also discussed .
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We present an algorithm to correct molecular dynamics non-equilibrium simulationsbased on the knowledge of time-dependent experimental data. This is inspired by a similar scheme used for equilibrium
Inferential methods can be used to integrate experimental informations and molecular
R
, and is based on
. The maximum entropy principle provides a framework for using equilibrium experimental data and it has been shown that replica-averaged simulations, restrained using a static potential, are a practical and powerful implementation of such principle. Here we show that replica-averaged simulations restrained using a time-dependent potential are equivalent to
R
that guarantees that as little subjective information as possible is added to a model, besides the available experimental data. We also show that the same algorithm, in the case of simplified models, can be used to speed up the computational time needed by a simulation by one to two orders of magnitude
, the dynamic version of the principle of maximum entropy, and thus may allow to integrate time-resolved data in molecular dynamics simulations. We provide an analytical proof of the equivalence as well as a computational validation making use of simple models and synthetic data. Some limitations and possible solutions are also discussed