Preview: Forthcoming article in Acta Crystallographica Section D: Biological Crystallography
Forthcoming article in Acta Crystallographica Section D Structural Biology
Acta Crystallographica Section D: Structural Biology welcomes the submission of articles covering any aspect of structural biology, with a particular emphasis on the structures of biological macromolecules and the methods used to determine them. Reports o
Proper modelling of ligand binding requires an ensemble of bound and unbound states
The importance of modelling the superpositions of ligand-bound and unbound states that commonly occur in crystallographic data sets is emphasized and demonstrated. The generation of an ensemble that models not only the state of interest is important for the high-quality refinement of low-occupancy ligands, as well as to explain the observed density more completely.
Tools for ligand validation in Coot
The current tools for ligand validation and comparison in Coot are presented. The user-selected ligand is assessed by ligand-distortion, map-correlation and temperature-factor metrics and compared with those of ligands from the wwPDB to create a percentile rank.
Dissecting random and systematic differences between noisy composite data sets
A multidimensional scaling analysis of pairwise correlation coefficients is presented which positions data sets in a sphere with unit radius of an abstract, low-dimensional space at radii inversely proportional to their levels of random error and at spherical angles related to their mutual systematic differences. This reduction in dimensionality can not only be used for classification purposes, but also to derive data-set relations on a continuous scale.
Data mining of iron(II) and iron(III) bond-valence parameters, and their relevance for macromolecular crystallography
Using all available metal-containing organic compound structures in the Cambridge Structural Database, a novel data-driven method to derive bond-valence R0 parameters was developed. While confirming almost all reference literature values, we observe two distinct populations of FeII—N and FeIII—N bonds, which are interpreted as low-spin and high-spin states of the coordinating iron. Based on the R0 parameters derived here, guidelines for the modeling of iron–ligand distances in macromolecular structures are suggested.