#RAPIDMAPS PROPERTY MAP FREE#
#RAPIDMAPS PROPERTY MAP WINDOWS#

#RAPIDMAPS PROPERTY MAP WINDOWS#

These capabilities open windows into biologically relevant information not included in current x-ray structural models.ġ) END and RAPID are dependent on the external programs CCP4 and Phenix. This new information about structural distributions in crystals increases the power of x-ray crystallography to facilitate inhibitor development, visualize structural ensembles and connect macromolecular motions to functions. A current challenge remains to automatically model alternative conformations. By analogy to the Beer–Lambert–Bouguer Law in spectroscopy, which defines the relationship between molecular concentration and optical absorbance, END maps report the concentration of scattering electrons at each point in space. END and RAPID maps enable a unified, quantitative interpretation of electron density that reveals not only low-occupancy ligands, but also dynamic structural features and alternative solvent constellations.

#RAPIDMAPS PROPERTY MAP FREE#

Comparing the electron density maps in the free and nucleotide-bound structures of three human protein kinases suggested that substrate binding perturbs distinct intrinsic allosteric networks that link the active site to surfaces that recognize regulatory proteins. These results illustrate general approaches to identify and analyze alternative conformations, low-occupancy small molecules, solvent distributions, communication pathways and protein motions.Īnalyzing the new electron density maps from 485 representative proteins revealed unmodeled conformations above the noise for 45% of side chains and a previously hidden, low-occupancy inhibitor of HIV capsid protein. Analyzing the new electron density maps from 485 representative proteins revealed unmodeled conformations above the noise for 45% of side chains and a previously hidden, low-occupancy inhibitor of HIV capsid protein. We find that noise varies with position and is generally 6-8 times lower than thresholds currently used in model building. Over several trials using different random number seeds, the RMS change in electron density observed at each point in the map in response to the changes in F obs was used to calculate a “RAPID map” of the spatial distribution of errors in the electron density. In this general, analytical approach, which we call refinement against perturbed input data (RAPID), errors in the experimental measurements (σ(F obs)) or the model (|F obs-F calc|) were used to add simulated noise to Fobs before re-refining the structure. The noise level at every position in the unit cell was determined by empirically propagating errors from the structure factors into the electron density map. With the electron density maps on an absolute scale, we searched for an approximate electron density threshold to distinguish signal from noise. In contrast to σ-scaled maps, where zero corresponds to the average electron density, in END maps, zero corresponds to vacuum. END maps were calculated by scaling the experimental structure factors (F obs) to structure factors calculated from the model (F calc, which are intrinsically on an absolute scale) and adding the average electron density of the crystal (including bulk solvent and the ordered model) to each map voxel. To overcome this classic limitation, we developed a general computational method to calculate F 000 and render maps on an absolute scale of electron number density (END) in units of electrons per cubic angstrom (e-/A 3). It is also impossible to quantitatively compare features in different maps, because the scale and offset relating σ to the absolute electron density varies among crystals of different molecules or even of the same molecular species with different symmetries or crystallization solvents. These “σ-scaled” maps are sufficient for structural modeling, but it is difficult to determine which density features are signal versus noise because the σ unit has little to do with the uncertainty in the electron density. The standard practice to circumvent this limitation is to represent electron density in relative units of the root mean square (RMS) deviation of map values from the mean density. Because crystals differ in composition, the absence of F 000 puts each map on a different scale. The structure factor of this reflection, F 000, is equal to the total number of electrons in the unit cell, including the contribution from disordered solvent. Why use absolute-scale and noise maps?Įlectron density maps are contoured on a relative scale because X-ray crystallographic diffraction experiments cannot measure a key, forward-scattered reflection that is swamped by the transmitted beam.

Rapidmaps property map