The various physical factors affecting measured diffraction intensities are discussed, as are the scaling models which may be used to put the data on a consistent scale. After scaling, the intensities can be analysed to set the real resolution of the data set, to detect bad regions (e.g. bad images), to analyse radiation damage and to assess the overall quality of the data set. The significance of any anomalous signal may be assessed by probability and correlation analysis. The algorithms used by the CCP4 scaling program SCALA are described. A requirement for the scaling and merging of intensities is knowledge of the Laue group and point‐group symmetries: the possible symmetry of the diffraction pattern may be determined from scores such as correlation coefficients between observations which might be symmetry‐related. These scoring functions are implemented in a new program POINTLESS.

Following integration of the observed diffraction spots, the process of `data reduction' initially aims to determine the point-group symmetry of the data and the likely space group. This can be performed with the programPOINTLESS. The scaling program then puts all the measurements on a common scale, averages measurements of symmetry-related reflections (using the symmetry determined previously) and produces many statistics that provide the first important measures of data quality. A new scaling program,AIMLESS, implements scaling models similar to those inSCALAbut adds some additional analyses. From the analyses, a number of decisions can be made about the quality of the data and whether some measurements should be discarded. The effective `resolution' of a data set is a difficult and possibly contentious question (particularly with referees of papers) and this is discussed in the light of tests comparing the data-processing statistics with trials of refinement against observed and simulated data, and automated model-building and comparison of maps calculated with different resolution limits. These trials show that adding weak high-resolution data beyond the commonly used limits may make some improvement and does no harm.

The BAR (Bin/amphiphysin/Rvs) domain is the most conserved feature in amphiphysins from yeast to human and is also found in endophilins and nadrins. We solved the structure of the Drosophila amphiphysin BAR domain. It is a crescent-shaped dimer that binds preferentially to highly curved negatively charged membranes. With its N-terminal amphipathic helix and BAR domain (N-BAR), amphiphysin can drive membrane curvature in vitro and in vivo. The structure is similar to that of arfaptin2, which we find also binds and tubulates membranes. From this, we predict that BAR domains are in many protein families, including sorting nexins, centaurins, and oligophrenins. The universal and minimal BAR domain is a dimerization, membrane-binding, and curvature-sensing module.

Clathrin-mediated endocytosis involves cargo selection and membrane budding into vesicles with the aid of a protein coat. Formation of invaginated pits on the plasma membrane and subsequent budding of vesicles is an energetically demanding process that involves the cooperation of clathrin with many different proteins. Here we investigate the role of the brain-enriched protein epsin 1 in this process. Epsin is targeted to areas of endocytosis by binding the membrane lipid phosphatidylinositol-4,5-bisphosphate (PtdIns(4,5)P(2)). We show here that epsin 1 directly modifies membrane curvature on binding to PtdIns(4,5)P(2) in conjunction with clathrin polymerization. We have discovered that formation of an amphipathic alpha-helix in epsin is coupled to PtdIns(4,5)P(2) binding. Mutation of residues on the hydrophobic region of this helix abolishes the ability to curve membranes. We propose that this helix is inserted into one leaflet of the lipid bilayer, inducing curvature. On lipid monolayers epsin alone is sufficient to facilitate the formation of clathrin-coated invaginations.