ARP/wARP is a software suite to build macromolecular models in X-ray crystallography electron density maps. Structural genomics initiatives and the study of complex macromolecular assemblies and membrane proteins all rely on advanced methods for 3D structure determination. ARP/wARP meets these needs by providing the tools to obtain a macromolecular model automatically, with a reproducible computational procedure. ARP/wARP 7.0 tackles several tasks: iterative protein model building including a high-level decision-making control module; fast construction of the secondary structure of a protein; building flexible loops in alternate conformations; fully automated placement of ligands, including a choice of the best fitting ligand from a "cocktail"; and finding ordered water molecules. All protocols are easy to handle by a non-expert user through a graphical user interface or a command line. The time required is typically a few minutes although iterative model building may take a few hours.

Methods for automated identi®cation and building of proteinbound ligands in electron-density maps are described. An error model of the geometrical features of the molecular structure of a ligand based on a lattice distribution of positional parameters is obtained via simulation and is used for the construction of an approximate likelihood scoring function. This scoring function combined with a graph-based search technique provides a¯exible model-building scheme and its application shows promising initial results. Several ligands with sizes ranging from 9 to 44 non-H atoms have been identi®ed in various X-ray structures and built in an automatic way using a minimal amount of prior stereochemical knowledge.

Automated model-building software aims at the objective interpretation of crystallographic diffraction data by means of the construction or completion of macromolecular models. Automated methods have rapidly gained in popularity as they are easy to use and generate reproducible and consistent results. However, the process of model building has become increasingly hidden and the user is often left to decide on how to proceed further with little feedback on what has preceded the output of the built model. Here, ArpNavigator, a molecular viewer tightly integrated into the ARP/wARP automated model-building package, is presented that directly controls model building and displays the evolving output in real time in order to make the procedure transparent to the user.

The efficiency of the ligand-building module of ARP/wARP version 6.1 has been assessed through extensive tests on a large variety of protein-ligand complexes from the PDB, as available from the Uppsala Electron Density Server. Ligand building in ARP/wARP involves two main steps: automatic identification of the location of the ligand and the actual construction of its atomic model. The first step is most successful for large ligands. The second step, ligand construction, is more powerful with X-ray data at high resolution and ligands of small to medium size. Both steps are successful for ligands with low to moderate atomic displacement parameters. The results highlight the strengths and weaknesses of both the method of ligand building and the large-scale validation procedure and help to identify means of further improvement.

The Structural Proteomics In Europe (SPINE) consortium contained a workpackage to address the automated X-ray analysis of macromolecules. The aim of this workpackage was to increase the throughput of three-dimensional structures while maintaining the high quality of conventional analyses. SPINE was able to bring together developers of software with users from the partner laboratories. Here, the results of a workshop organized by the consortium to evaluate software developed in the member laboratories against a set of bacterial targets are described. The major emphasis was on molecular-replacement suites, where automation was most advanced. Data processing and analysis, use of experimental phases and model construction were also addressed, albeit at a lower level.