The CCP4 (Collaborative Computational Project, Number 4) software suite is a collection of programs and associated data and software libraries which can be used for macromolecular structure determination by X-ray crystallography. The suite is designed to be flexible, allowing users a number of methods of achieving their aims. The programs are from a wide variety of sources but are connected by a common infrastructure provided by standard file formats, data objects and graphical interfaces. Structure solution by macromolecular crystallography is becoming increasingly automated and the CCP4 suite includes several automation pipelines. After giving a brief description of the evolution of CCP4 over the last 30 years, an overview of the current suite is given. While detailed descriptions are given in the accompanying articles, here it is shown how the individual programs contribute to a complete software package.

iMOSFLM is a graphical user interface to the diffraction dataintegration program MOSFLM. It is designed to simplify data processing by dividing the process into a series of steps, which are normally carried out sequentially. Each step has its own display pane, allowing control over parameters that influence that step and providing graphical feedback to the user. Suitable values for integration parameters are set automatically, but additional menus provide a detailed level of control for experienced users. The image display and the interfaces to the different tasks (indexing, strategy calculation, cell refinement, integration and history) are described. The most important parameters for each step and the best way of assessing success or failure are discussed.

Processing diffraction data falls naturally into three distinct steps: First, determining an initial estimate of the unit cell and orientation of the crystal; second, obtaining refined values for these parameters; and third, integrating the diffraction images. The basic principles underlying autoindexing, parameter refinement, and spot integration by summation integration and profile fitting are described.

The fast Fourier transform (FFT) autoindexing routines written by the Rossmann group at Purdue University have been incorporated in MOSFLM, providing a rapid and reliable method of indexing oscillation images. This is a procedure which extracts direct-space information about the unit cell from the FFT. The method and its implementation in MOSFLM are discussed.

An overview of autoindexing diffraction images based on one-dimensional fast Fourier transforms is presented. The implementation of the algorithm in the Mosflm/iMosflm program suite is described with a discussion of practical issues that may arise and ways of assessing the success or failure of the procedure. Recent developments allow indexing of images that show multiple lattices, and several examples demonstrate the success of this approach in real cases.