E pluribus unum, no more: from one crystal, many conformations

Abstract

Several distinct computational approaches have recently been implemented to represent conformational heterogeneity from X-ray crystallography datasets that are averaged in time and space. As these modeling methods mature, newly discovered alternative conformations are being used to derive functional protein mechanisms. Room temperature X-ray data collection is emerging as a key variable for sampling functionally relevant conformations also observed in solution studies. Although concerns about radiation damage are warranted with higher temperature data collection, 'diffract and destroy' strategies on X-ray free electron lasers may permit radiation damage-free data collection. X-ray crystallography need not be confined to 'static unique snapshots'; these experimental and computational advances are revealing how the many conformations populated within a single crystal are used in biological mechanisms.

Figure 1. Electron density maps contain ensemble-averaged information about multiple protein conformations

a) The spread in electron density (blue mesh, 1σ high contour; cyan mesh, 0.5 σ low contour) around each atom is approximated by a B-factor, which models the thermal motion as a Gaussian displacement about the mean position. b) An electron density map with multiple maxima (blue mesh, high contour; cyan mesh, low contour) is inadequately modeled by B-factors, resulting in difference map peaks (red mesh, -1.5σ Fo-Fc peak underlying the model; green mesh, +1.5σ Fo-Fc peak indicating potential placement of alternative conformations). Because the alternative conformation partially overlaps with the primary conformation and is at lower occupancy, it is not visible at high contour. c) Sampling the electron density around the χ₁ dihedral angle of the map shown in (b) (pink dots) reveals the presence of a distinct peak at the rotameric angle of -60°, providing an anchor point for manual model building of an alternative conformation. Automated model building is further complicated by the potential for backbone motions that can shift these peaks out of rotameric angles.

Figure 2. Different model types are being used to interrogate conformational heterogeneity

a) In multiple independent refinements, each copy contributes to a distinct set of model structure factors. The distinct structures, separated here by boxes, yield an estimate of the relative precision of the refinement method. b) In multi-copy ensemble refinement, a set number of copies of the protein, represented here by different colors, are refined together. c) Similarly, in time-averaged ensemble refinement, multiple copies of the protein are selected from an MD simulation where the structure factors are averaged over a defined time window. d) In multiconformer approaches, an optimal combination of between 1 and 4 conformations with associated occupancies (represented here by the thickness of the sticks) is constrained to sum to unit occupancy for each residue.

Figure 3. Examples of functional conformational changes within a single crystal lattice

a) Bacillus DNA polymerase I can catalyze DNA synthesis in the crystal lattice. The initial complex (PDB: 1L3S) containing the polymerase domain (yellow) and exonuclease domain (blue) is soaked with dNTPs. During catalysis the nascent strands are extended (brighter colors) and the pre-existing strands are extruded towards the solvent channels (PDB: 1L3V). b) The head domain of α_IIbβ₃ integrin (PDB: 3ZDX) undergoes a large allosteric conformational change when the ligand RGD peptide (magenta) is soaked into the crystal lattice (PDB: 3ZE2). Aligning the β-propeller domains (green) reveals how the β₃ inserted and hybrid domains extend and swing away (cyan) from the initial position (grey) upon peptide binding.