The Milestoning algorithm created by Ron Elber et al. is a method for determining the time scale of processes too complex to be studied using brute force simulation methods. The fundamental objects implemented in the Milestoning algorithm are the first passage time distributions between adjacent protein configuration milestones. The method proposed herein aims to further enhance Milestoning by employing an artificial applied force, akin to wind, which pushes the trajectories from their initial states to their final states, and subsequently re-weights the trajectories to yield the true first passage time distributions in a fraction of the computation time required for unassisted calculations. The re-weighting method, rooted in Itos stochastic calculus, was adapted from previous work by Andricioaei et al. The theoretical basis for this technique and numerical examples are presented.
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