Assessing Exhaustiveness of Stochastic Sampling for Integrative Modeling of Macromolecular Structures

Modeling of macromolecular structures involves structural sampling guided by a scoring function, resulting in an ensemble of good-scoring models. By necessity, the sampling is often stochastic, and must be exhaustive at a precision sufficient for accurate modeling and assessment of model uncertainty