One of the most important methods for determining macromolecular structures is molecular replacement (Rossmann, 1972
). In this procedure, a known structure is used as a template for the target structure to be determined. An approximate position of the template is found, typically using a search procedure that optimizes the agreement between the observed structure factors and those calculated from the placed template (see, for example, Navaza, 1987
; Vagin & Teplyakov, 1997
; Read, 2001
; McCoy et al.
; Keegan et al.
). The placed template is then used to generate a starting electron-density map that can be a basis for model improvement or rebuilding.
A crucial requirement of the molecular-replacement method is that the template be quite similar to the target structure. Usually, these two structures must agree within about 1.5–2 Å root-mean-square distance (r.m.s.d.) for Cα
atoms over much of the molecules to be useful in molecular replacement (Chen et al.
). This means that the sequences of the template and target usually need to be about 25–30% identical or greater (Chothia & Lesk, 1986
). Despite this limitation, over 70% of new protein structures are already determined by molecular replacement (Evans & McCoy, 2008
). As the number and diversity of structures in the Protein Data Bank (PDB; Berman et al.
) increases, the applicability of molecular replacement will continue to broaden.
The utility of molecular replacement would be extended even further if the requirement for similarity between the template and target structures could be relaxed. Recently, several methods have been introduced that address this requirement. The use of algorithms from the structure-modeling field has yielded improved homology models based on distant templates, improved models obtained from other techniques such as NMR and even ab initio
models that are suitable for molecular replacement (Qian et al.
; Ramelot et al.
; DiMaio et al.
; Mao et al.
). Additionally, algorithms from the structure-modeling field have been combined with crystallographic tools to rebuild and improve templates that have been placed in position in the crystallographic cell using weak structural information available from initial electron-density maps calculated using these placed templates (DiMaio et al.
). Methods for the iterative improvement of models and electron-density maps have further increased the convergence of molecular replacement, particularly when data are available at resolutions finer than about 2 Å (Perrakis et al.
; Langer et al.
; Cohen et al.
). Finally, techniques that incorporate local structural information from the template as restraints have increased the amount of information available in refinement, facilitating improved refinement at low resolution and refinement starting with models that are more distant from the target structure than was previously feasible. These methods include LSSR in Buster
(Smart et al.
) and external structure restraints in REFMAC
(Murshudov et al.
), each of which uses distance restraints between nearby atoms derived from the reference model to inform the refinement. DEN restraints in CNS
(Schröder et al.
) use ‘deformable’ networks of distance restraints, permitting slow deformations of the restraints as the refinement proceeds and adjusting the degree of deformation by cross-validation with R
using multiple trials for each parameter combination, ensuring the most optimal refined structure. Other methods include the use of restraints in torsion-angle space derived from the reference model (Headd et al.
) and the use of normal-mode refinement (Kidera & Go, 1992
; Delarue, 2008
In this work, we describe a method for iterated local density-guided model deformation and refinement, a process that we will refer to here with the informal term ‘morphing’. Morphing can be applied to search models that have been placed in the crystallographic cell by molecular replacement but that are not close enough to the target structure for automated model building to be effective. Our approach for morphing builds on methods for finding fragments of structure in electron-density maps (Kleywegt & Jones, 1997
; Cowtan, 1998
; Terwilliger, 2001
), but extends these methods by allowing a different translation for each residue in a template, smoothing these translations to yield a continuously deformed model with an improved match to the electron-density map. Further, the morphing procedure includes refinement to improve model geometry and the fit to crystallographic data. We show that morphing can be useful in improving an initial molecular-replacement model after it has been placed in the crystallographic cell.