The hammerhead, hairpin, hepatitis delta virus (HDV), Varkud Satellite (VS), and glmS ribozymes catalyze sequence-specific intramolecular cleavage of RNA. They range between 50 and 150 nucleotides in length, and are known as the "small self-cleaving ribozymes." Except for the glmS ribozyme that functions as a riboswitch in Gram-positive bacteria, they were originally discovered as domains of satellite RNAs. However, recent studies show that several of them are broadly distributed in genomes of organisms from many phyla. Each of these ribozymes has a unique overall architecture and active site organization. Crystal structures have revealed how RNA active sites can bind preferentially to the transition state of a reaction, whereas mechanistic studies have shown that nucleobases can efficiently perform general acid-base and electrostatic catalysis. This versatility explains the abundance of ribozymes in contemporary organisms and also supports a role for catalytic RNAs early in evolution.

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. It is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis.