Constraint Satisfaction Techniques for Modeling Large Complexes: Application to the Central Domain of 16S Ribosomal RNA

Proceedings Of The Second International Conference On Intelligent Systems For Molecular Biology

Volume

Proceedings Of The Second International Conference On Intelligent Systems For Molecular Biology

Contents

Standard experimental techniques for determining the structure of small to moderately-sized molecules are difficult to apply to large macromolecular complexes. These complexes, consisting of multiple protein and/or nucleic acid components, can contain many thousands of atoms and the experimental techniques used to study them provide relatively sparse structural information with significant measurement uncertainty. Computational technologies are required to reduce the conformational search space and synthesize the data in order to produce the structures or (more usually) sets of structures compatible with the data. In this paper, we show that a method based on the constraint satisfaction paradigm produces a three-dimensional topology for the central domain of the 16S ribosomal RNA that is generally consistent with interactively built models, although differing in significant ways. The modeling incorporates information about secondary structure of the nucleic acid, neutron diffraction data about the relative positions and uncertainties of the proteins, and protection experiments indicating proximities of segments of RNA to specific protein subunits. Unlike previously proposed models, our model contains explicit information about the range of positions for each subunit that are compatible with the data. The system uses a grid search, checks distances in a direction-dependent manner, uses disjunctive distance constraints, and checks for volume overlap violations.