In integrative structural biology/hybrid modeling approaches, we integrate structural models of macromolecules and experimental data to obtain faithful representations of the structures underlying the data. For example, in ensemble refinement by reweighting we first generate structural ensembles of flexible and dynamic biological macromolecules in molecular simulations. In a subsequent reweighting step, we refine the statistical weights of the structures to strike a balance between the information provided by simulations and by experimental data. For the "Bayesian inference of ensembles" approach (BioEn), we present two complementary methods to solve the underlying challenging high-dimensional optimization problem. We systematically investigate reliability, accuracy, and efficiency of these methods and integrate molecular dynamics simulations of the disordered peptide Ala-5 and NMR J-couplings. We provide an open-source library free of charge at https://github.com/bio-phys/BioEn.
Submitted to JCTC.