research papers
From lows to highs: using low-resolution models to phase X-ray data
aDivision of Structural Biology, The Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Headington, Oxford OX3 7BN, England,bDiamond Light Source Ltd, Diamond House, Harwell Science and Innovation Campus, Didcot, England,cStructural Biology Unit, CIC bioGUNE, CIBERehd, Bizkaia Technology Park, Bld 800, 48160 Derio, Spain, and dIKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Spain
*Correspondence e-mail: nabrescia@cicbiogune.es
The study of virus structures has contributed to methodological advances in structural biology that are generally applicable (molecular replacement and
are just two of the best known examples). Moreover, structural virology has been instrumental in forging the more general concept of exploiting phase information derived from multiple structural techniques. This of structural methods, primarily (EM) and X-ray crystallography, but also small-angle X-ray scattering (SAXS) and nuclear magnetic resonance (NMR) spectroscopy, is central to integrative structural biology. Here, the interplay of X-ray crystallography and EM is illustrated through the example of the structural determination of the marine lipid-containing bacteriophage PM2. starting from an ∼13 Å cryo-EM reconstruction, followed by cycling density averaging, phase extension and solvent flattening, gave the X-ray structure of the intact virus at 7 Å resolution This in turn served as a bridge to phase, to 2.5 Å resolution, data from twinned crystals of the major coat protein (P2), ultimately yielding a quasi-atomic model of the particle, which provided significant insights into virus evolution and viral membrane biogenesis.1. Introduction
Tough structural problems, especially those relating to viruses, have from their very infancy required a combination of techniques such as ; Bawden & Pirie, 1938; Leonard et al., 1953; Schmidt et al., 1954; Crick & Watson, 1957; Kruger et al., 2000). Recently, EM and X-ray crystallography have taken the leading role in the development of hybrid methods (Chiu & Smith, 1994; Rossmann, 2000; Gilbert et al., 2003; Rossmann et al., 2005; Johnson, 2008; Steven & Baumeister, 2008), although useful techniques now also include nuclear magnetic resonance (NMR) spectroscopy and (MS). Together, these methods are helping to realise a vision of the cellular landscape spanning a continuum in the ångström to nanometre resolution range (Badia-Martinez et al., 2013).
(EM), X-ray crystallography and small-angle X-ray scattering (SAXS) (Stanley, 1935It has become common practice to provide quasi-atomic models by fitting the X-ray crystal structures of individual components determined at near-atomic resolution into a lower resolution density map (EM or X-ray derived) of an intact complex (Rossmann, 2000; Gilbert et al., 2003). Despite this, it is interesting to note that there remain rather few examples where high-resolution X-ray data have been phased starting from low-resolution EM reconstructions (Trapani et al., 2010).
Major contributions to these developments have come from the study of icosahedral viruses. Certain viruses are relatively easy to prepare (much early work used plant viruses, which are available in very large amounts) and crystallize, yielding crystals with high ; Harrison & Jack, 1975; Harrison et al., 1978; Rossmann, 1990). Milestones are shown in Fig. 1.
(NCS), since the fivefold axes of an icosahedron cannot be accommodated in a For these reasons, structural virology has played an important role in the development and consolidation of the molecular-replacement (MR) and NCS-averaging methods for phase determination (Rossmann & Blow, 1962Here, we briefly review the contributions of structural virology to the development of the MR technique and then describe, as an example, the MR procedures that have led to the quasi-atomic structure of the marine internal membrane-containing bacteriophage PM2 using low-resolution cryo-EM and X-ray models.
2. Structural virology and molecular replacement
The et al., 1974), although an indication of the potential can be seen in the 1964 paper on α-chymotrypsin (Blow et al., 1964). The GAPDH system was also the first example of phasing via the use of a molecular model or envelope as a search probe (interestingly, attempts at phasing GAPDH using spherical rather than molecular envelopes failed; Rossmann & Arnold, 1993). However, the idea of exploiting the high 532 of icosahedral viruses to solve the dates back to a similar time (Argos et al., 1975). Indeed, the first two virus structures solved by X-ray crystallography (Fig. 1), Tomato bushy stunt virus and Southern bean mosaic virus, used MR phases to locate the heavy-atom and prime the low-resolution phasing (Harrison et al., 1978; Abad-Zapatero et al., 1980). Soon after that, the first examples of successful phase extension of initial MR phases obtained with virus structures with almost no sequence identity (Acharya et al., 1989) or even spherical envelopes (Tsao et al., 1992) followed. This MR approach, however, had (and still has) to take into account the eventuality of phases converging to the Babinet-inverted phase solution (180° out of phase from the correct phases), a particularly risky circumstance when starting from very low resolution model phases and when using highly symmetrical envelopes (Tsao et al., 1992; Plevka et al., 2011).
of the tetrameric enzyme glyceraldehyde 3-phosphate dehydrogenase (GAPDH) provided the first illustration of successful phasing by a combination of NCS and (Buehner3. Phase interplay between EM, SAXS and X-ray crystallography
EM, SAXS and X-ray crystallography provide structural information at different but overlapping resolution ranges (Johnson, 2008; Steven & Baumeister, 2008; Badia-Martinez et al., 2013; Fig. 2). The obvious advantage of EM and SAXS over X-ray crystallography is that they do not require a crystalline array (Fig. 2), whereas (virus) crystallography has yielded higher resolution (Fry et al., 2007). However, when studying viruses, these days cryo-EM can provide three-dimensional reconstructions at ∼3.5 Å resolution (Jiang et al., 2008; Liu et al., 2010) for large and small viruses alike, including enveloped ones such as dengue (Zhang et al., 2013; Fig. 1). This is mainly owing to the availability of increasingly powerful electron microscopes with fast, sensitive detectors and increasingly powerful computational methods (Zhou & Chiu, 2003; Bai et al., 2013).
Bio-SAXS has become largely automated (Blanchet et al., 2012) and whilst work on viruses has moved from their architectural characterization towards the analysis of dynamic processes (Canady et al., 2001; Lee et al., 2004), protein SAXS is performed mainly to elucidate molecular envelopes and the spatial arrangement of binding partners (Svergun & Koch, 2002).
Since ; Badia-Martinez et al., 2013). Undeniably, the original successes in virus phasing using unrelated virus structures boosted confidence in phasing high-resolution X-ray data from low-resolution models. For instance, the structure of ornithine transcarbamoylase (OTCcase; Villeret et al., 1995), using a low-resolution 8 Å X-ray model to phase and phase-extend 3 Å resolution X-ray data, was inspired by the earlier Mengovirus and Foot-and-mouth disease virus protocols (Luo et al., 1987; Acharya et al., 1989).
works by the cross-correlation of Patterson vectors, either three-dimensional atomic models or electron-density maps can be given as search models. Thus, any structural information obtained by SAXS, EM, X-ray crystallography and NMR can, in theory, be used (for more discussion on how a one-dimensional tool such as SAXS can lead to three-dimensional results, see Svergun & Koch, 2002Cryo-EM and negative-stain EM low-resolution reconstructions provide, in principle, a general vehicle for the phasing of protein X-ray data, as shown in many test cases (Dodson, 2001; Navaza, 2008; Xiong, 2008). Although this approach is not routine, it should be considered whenever (i) the self-rotation function suggests the presence of multiple copies of the target protein in the (ii) low-resolution phases are available and (iii) the resolution ranges of the template and target structures overlap (Trapani et al., 2010). Once the operators that relate the different protein copies have been accurately determined, the NCS is exploited to improve the starting phases and for the phase extension procedure (Rossmann, 1995; Trapani et al., 2010).
Modern high-quality NMR structures can also be used as MR search probes, although they require careful preparation (Mao et al., 2011). In contrast, the phasing of nitrite reductase using a molecular envelope obtained by SAXS studies was successful to only 20 Å resolution (Hao et al., 1999), and to our knowledge there are no successful examples of SAXS phasing and phase-extension leading to reliable phases at high resolution. Finally, modern molecular-modelling software such as Rosetta can generate initial templates for MR (Terwilliger et al., 2012).
4. A case study: the quasi-atomic structure of lipid-containing bacteriophage PM2
The marine bacteriophage PM2 (molecular mass of ∼45 MDa) is one of only two membrane-containing viruses solved by X-ray crystallography to date (Abrescia et al., 2004, 2008; Cockburn et al., 2004). PM2 was crystallized by vapour diffusion in quartz capillary tubes. Data were collected from a large number of crystals directly irradiated from these capillary tubes cooled to 273 K at several synchrotron beamlines (ID14-EH1 and ID14-EH2, ESRF, Grenoble, France and PX06SA, SLS, Zurich, Switzerland; Abrescia et al., 2008). In addition, virions were labelled with selenomethionine (SeMet) by finding a strain of the host (genus Pseudoalteromonas) which was auxotrophic for methionine, and growing in a defined rich medium. Data from these labelled particles provided important information for the final structural interpretation (Kivelä et al., 2008). Finally, crystals of the isolated major capsid protein (MCP) P2 were grown using a nanoscale crystallization technique and X-ray data were collected on BM14 at ESRF, Grenoble, France (Abrescia et al., 2005, 2008, 2011).
In the next two sections, we focus on those aspects of the molecular-replacement procedures used to obtain the PM2 quasi-atomic model that might provide guidance in the use of low-resolution models as templates in MR.
4.1. Phasing low-resolution X-ray data for the PM2 virion by molecular replacement
Data processing and scaling were carried out using the HKL program suite (Otwinowski & Minor, 1997) and the data were post-processed as described in Diprose (2000) and Abrescia et al. (2008). Analysis of the (C2) and unit-cell parameters (a = 946.9, b = 677.6, c = 1067.6 Å, β = 102.9°) with prior knowledge of the virion dimensions (∼600 Å; Huiskonen et al., 2004) suggested the presence of one virus per The final data set was assembled from images taken from many hundreds of crystals, but as soon as we had accumulated ∼20% completeness we initiated because in the presence of such high NCS, NCS-related spots can essentially substitute for the ones that are as yet unmeasured, and thus afford the completeness needed. We used X-PLOR v.3.85 (Brünger, 1992) to determine the orientation and position of the virus within the unit cell.
4.1.1. Self-rotation (SR) search
The SR function (SRF) was calculated by adapting the corresponding script (self_rf.inp) in X-PLOR to search for the orientation of the PM2 virion. The X-ray data resolution range used in the search spanned 30–8.5 Å. Minimum and maximum lengths were carefully chosen between a minimum of 80 Å and a maximum of 400 Å to include predominantly intramolecular vectors. In rotation functions the higher-order symmetry axes are seen most clearly, so we inspected the κ = 72° (in spherical polar angles) section of the SRF to determine the locations of the fivefold axes. X-PLOR produced a .3dmatrix file that was then rendered using the GROPAT software (R. M. Esnouf, unpublished program; available from the author at robert@strubi.ox.ac.uk; Fig. 3a). In the hemisphere shown we would expect to see six fivefold axes for each virion in the For C2, with a whole particle in the crystallographic two sets of peaks would be expected. Notice in Fig. 3(a) that since an icosahedral axis is close to the crystallographic twofold axis, it appears as if the set of six peaks is `split'. Notice also that despite the data being weak, low-resolution and incomplete [I/σ(I) = 4.3 overall and 1.2 in the last (8.5–8.3 Å) resolution shell], and despite having included only reflections with partiality greater than 70% (for details of the data processing, please see Abrescia et al., 2008), the peaks in the SRF are sharp and well above the noise.
Next, the density from a preliminary PM2 cryo-EM reconstruction at 13 Å resolution corresponding to the capsid and spike proteins (Huiskonen et al., 2004) was filled with atoms on a 3 Å grid using the General Averaging Program (GAP; D. I. Stuart & J. M. Grimes, unpublished work; software for computers running Linux is available on request from DIS). Working with this pseudo-atomic model facilitated the application of the rotations, translation and changes in scale necessary for MR in X-PLOR.
Firstly, this PM2 pseudo-atomic model was orientated such that the icosahedral twofold axes were aligned with the Cartesian axes (Crowther 222 setting; Crowther, 1971) and this was checked by computing the SRF using the corresponding structure factors (Fcalc) calculated in X-PLOR (model_fcalc.inp) within the same resolution range as the experimental data but in P1 (Fig. 3b). Secondly, the model was rotated in such a way as to orient the fivefold axes from the initial 222 setting to the experimentally observed fivefold-axis directions (Fig. 3a). The rotated model is shown in Fig. 3(c). To confirm the correct application of this rotation, the Fcalc were calculated (in P1) and the SRF was computed (Fig. 3d). As expected, this contains six peaks, each of which exactly overlaps a peak in the SRF for the experimental data in C2 (Fig. 3a).
4.1.2. Translation search (TS)
Having determined the orientation of the pseudo-atomic model of the virus (Fig. 3c), the template virus particle in this orientation was then used to perform a translation search in X-PLOR using the E2E2 target function (Brünger, 1992; translation1.inp). The E2E2 correlation-coefficient target function essentially measures the fractional overlap of Patterson vectors between the experimental data and the model. Owing to the arbitrary origin along the y direction in the C2 the search only needed to be performed in a single xz plane. Also, from packing considerations we were able to restrict the search to between 0.2 and 0.4 (fractional coordinates) in both x and z. The TS was performed with data between 50 and 13 Å resolution and produced a single unequivocal 36σ peak (correlation coefficient = 0.146; σ = 0.004) at fractional coordinates (0.286 0.000 0.237) (see Fig. 3e).
To assess whether the magnification of the PM2 cryo-EM reconstruction (and consequently of the pseudo-atomic PM2 model) was in error, a check was performed by varying the scale of the pseudo-atomic PM2 model from 0.8 to 1.2 (in steps of 0.05) and re-running the translation search, monitoring the increase/decrease of the peak heights of the TS function. The values of the maximum Bscale (as an overall B factor added to the individual atomic B factors) was set to 300 Å2 to `expand' the atoms (placed on a 3 Å grid) and to ensure that they were sampled adequately by the coarse FFT grid set to 4.6 Å (∼1/3 of the highest resolution; Brünger, 1992).
obtained during this test were 30–70% lower than the 0.146 obtained with the original scale, thus indicating no coarse magnification error of the cryo-EM map. Since these calculations were performed at low resolution, throughout the searches and the calculation of the Fast Fourier Transform (FFT) of the atomic pseudo-PM2 model, theWith the pseudo-atomic model safely located within the X-PLOR; target function XREF, resolution range 50–13 Å) which refined the virus position (Rstart = 58.7%, Rfinal = 54.6%) by the following residual rotations and translations [rotation (°) = (−0.35 −0.23 −0.37); translation (Å) = (−0.08 −0.02 −0.09)].
a rigid-body was carried out (Phases were then determined to 13 Å resolution and the 60 NCS operators calculated and used for the phase-extension procedure. The fact that none of the icosahedral twofold axes were aligned with the crystallographic twofold axis allowed us to exploit the full 60-fold icosahedral redundancy. Real-space cycling averaging and solvent flattening were performed to 12 Å resolution, and the phases were gradually extended to 7 Å (averaging R factor start/final 28/23%; start/final 79/88%) using GAP and associated software (for further details of the phase-improvement procedures, see, for example, Fry et al., 1993; Grimes et al., 1998; Diprose, 2000; Abrescia et al., 2004, 2008). This led to a map that allowed, with the incorporation of Se positions from the SeMet-labelled virus, a tentative interpretation of the detailed structure of the viral coat proteins (Abrescia et al., 2008).
4.2. The of P2, the MCP of the PM2 virus, using a 7.6 Å resolution electron-density map as a molecular-replacement search model
Despite its very high quality, the 7.0 Å resolution of the averaged map of the virus 2w0c ; Fig. 4a; Abrescia et al., 2008) could not reliably resolve the fold of the MCP P2 protein (molecular mass 30.2 kDa; 200 copies of the trimeric molecule compose the virus capsid), although the overall morphology of the capsomers suggested that the protein subunit might possess a double jelly-roll fold as observed for other viral MCPs (Benson et al., 1999; Khayat et al., 2005). Thus, we set out to obtain the crystal structures of the individual P2 and P1 proteins (pentamers of the latter sit at the icosahedral fivefold vertices and provide the receptor-binding site (Figs. 3c and 4a).
(PDB entryWhereas P2 was isolated and purified from the virus (Abrescia et al., 2005), a range of different constructs of P1 were designed and expressed recombinantly (Abrescia et al., 2008). The recombinant P1 structures were then solved by experimental phasing using SeMet-derivatized crystals (PDB entries 2vvd and 2vve ; Abrescia et al., 2008), whilst P2 was solved by in an unusual fashion (PDB entry 2vvf ; Abrescia et al., 2011).
Preliminary X-ray data for P2 to ∼4 Å resolution showed the presence within the crystallographic et al., 2005). Improved data extending to 2.5 Å resolution were obtained from an inseparable stack of several crystals. The two principal lattices were processed independently and merged, with the rejection criteria carefully set to eliminate overlapping reflections (Abrescia et al., 2011). This led to a high-quality data set (the high redundancy allowed the robust detection of the overlapping reflections). Although the 7 Å resolution map of the complete virus had suggested that P2 belonged to the family of double jelly-roll MCPs, MR attempts using structurally related models such as the MCPs of PRD1 and STIV (Benson et al., 1999; Khayat et al., 2005) as search probes were unsuccessful (Abrescia et al., 2011). Therefore, we used the 7 Å resolution electron density from the several PM2 trimers within the virus icosahedral unit as a search model. First, we averaged the electron densities of the independent P2 trimers within the icosahedral (labelled 1, 2, 3 and 4 in Fig. 4a; trimer 3 is actually sitting on the icosahedral threefold axis) using as a mask a double jelly-roll structure manually trimmed to roughly fill the 7 Å resolution electron-density envelope (Fig. 4b). This averaged trimer map was then placed using GAP into a P1 of unit-cell parameters double the trimer diameter (a = b = c = 150 Å, trimer diameter of ∼74 Å; Fig. 4a, inset) to ensure (i) that there would be no interatomic vectors in subsequent manipulations and (ii) the molecular envelope was appropriately sampled (Rossmann & Arnold, 1993).
of two trimers related by a translation (AbresciaPhaser (McCoy et al., 2005) was used for MR via CCP4 (Winn et al., 2011). The program was asked to search for two trimers in the with the keywords `EXTENT 90 90 40' and `RMS 1.5' within the resolution range 30–7 Å (the resolution was reset automatically by Phaser between 29.8 and 7.6 Å; the `EXTENT' keyword defines the limits in x, y and z of the region of density to be considered; for details of Phaser keywords, see https://www.phaser.cimr.cam.ac.uk/index.php/Molecular_Replacement ). The top peak in the fast rotation function displayed a log-likelihood gain (LLG) of 56.5 and a Z-score of 9.0 (the number of standard deviations above the mean). The fast translation found two sites, with the top one having an LLG of 99.0 and a Z-score of 8.5 (we requested peaks over 75% of the top peak). The second trimer was then searched and located. The final of the top solution for both trimers (RFZ = 9.0, TFZ = 8.5, PAK = 0, LLG = 109; RFZ = 6.6, TFZ = 21.2, PAK = 0, LLG = 448; where RFZ is the rotation-function Z-score, TFZ is the translation-function Z-score and PAK is the number of packing clashes) had a negligible effect on the LLG.
Proof of the correctness of the MR solution (Fig. 4b) was obtained by using phases from the Phaser model to calculate an electron-density map which was then used as a starting point for a phase-improvement protocol. This consisted of NCS-operator prior to cyclic averaging, solvent flattening and gradual phase extension in resolution steps of 1/2000 Å using GAP (this step was chosen to be ∼25 times smaller than the inverse of the shortest unit-cell parameter to guarantee that no random phases would be introduced; for a mathematical formalism on the phase-extension procedure, see Rayment, 1983; Rossmann, 1990; Fry et al., 1993). This process, detailed in Abrescia et al. (2011), led to an excellent map at 2.5 Å resolution (Fig. 4c), which rendered of the double jelly-roll fold of the protein facile.
Structural superimpositions of the refined P2 atomic model with the other MCPs belonging to the same PRD1-adenoviral lineage (Abrescia et al., 2012) revealed why MR using these search models failed: they showed root-mean-square deviations (r.m.s.d.) above 2.9 Å (Fig. 4d), which are higher than expected for template models that are likely to succeed in MR (Terwilliger et al., 2012), despite the fact that all share the double jelly-roll fold.
5. Conclusions
Owing to their isometric shape, icosahedral viruses (harbouring 60 symmetry-related identical building blocks) have proved to be useful for developing the MR technique. Early successes of this method using low-resolution models as search probes encouraged the adoption of a similar workflow in cases of crystallized multimeric proteins (especially where the presence of proper NCS facilitates the derivation of accurate NCS operators) and for which low-resolution structural information is available. These low-resolution phases, either derived from (cryo-)EM or X-ray crystallographic electron density, can be used as a source of initial phases for high-resolution X-ray data, easing the solution of the phase problem.
As examples of this phasing strategy, we have detailed the procedures used in the MR
of the entire lipid-containing bacteriophage PM2 at 7 Å resolution and the subsequent use of this electron density in the determination of the structure of its major capsid protein P2 at 2.5 Å resolution. The resulting quasi-atomic model of PM2 illustrates the power of combining these phasing methods.Acknowledgements
We are grateful to D. H. Bamford (Helsinki University) for his collaboration and support during the last decade, to our colleagues J. M. Grimes, R. M. Esnouf and J. M. Diprose (Oxford University) for many useful discussions and help with the General Averaging Program and to G. C. Sutton (Oxford University) for advice on virus purification and handling. DIS is supported by the UK MRC and NGAA is supported by the Spanish Ministerio de Economia y Competitividad (BFU2012-33947) and the Basque Government (PI2010-20).
References
Abad-Zapatero, C., Abdel-Meguid, S. S., Johnson, J. E., Leslie, A. G. W., Rayment, I., Rossmann, M. G., Suck, D. & Tsukihara, T. (1980). Nature (London), 286, 33–39. CrossRef PubMed CAS Web of Science Google Scholar
Abrescia, N. G. A., Bamford, D. H., Grimes, J. M. & Stuart, D. I. (2012). Annu. Rev. Biochem. 81, 795–822. Web of Science CrossRef CAS PubMed Google Scholar
Abrescia, N. G. A., Cockburn, J. J., Grimes, J. M., Sutton, G. C., Diprose, J. M., Butcher, S. J., Fuller, S. D., San Martín, C., Burnett, R. M., Stuart, D. I., Bamford, D. H. & Bamford, J. K. H. (2004). Nature (London), 432, 68–74. Web of Science CrossRef PubMed CAS Google Scholar
Abrescia, N. G. A., Grimes, J. M., Kivelä, H. M., Assenberg, R., Sutton, G. C., Butcher, S. J., Bamford, J. K. H., Bamford, D. H. & Stuart, D. I. (2008). Mol. Cell, 31, 749–761. Web of Science CrossRef PubMed CAS Google Scholar
Abrescia, N. G. A., Grimes, J. M., Oksanen, H. M., Bamford, J. K. H., Bamford, D. H. & Stuart, D. I. (2011). Acta Cryst. D67, 228–232. Web of Science CrossRef CAS IUCr Journals Google Scholar
Abrescia, N. G. A., Kivelä, H. M., Grimes, J. M., Bamford, J. K. H., Bamford, D. H. & Stuart, D. I. (2005). Acta Cryst. F61, 762–765. Web of Science CrossRef CAS IUCr Journals Google Scholar
Acharya, R., Fry, E., Stuart, D., Fox, G., Rowlands, D. & Brown, F. (1989). Nature (London), 337, 709–716. CrossRef CAS PubMed Web of Science Google Scholar
Argos, P., Ford, G. C. & Rossmann, M. G. (1975). Acta Cryst. A31, 499–506. CrossRef CAS IUCr Journals Web of Science Google Scholar
Badia-Martinez, D., Oksanen, H. M., Stuart, D. I. & Abrescia, N. G. A. (2013). Subcell. Biochem. 68, 203–246. PubMed Google Scholar
Bai, X.-C., Fernandez, I. S., McMullan, G. & Scheres, S. H. W. (2013). Elife, 2, e00461. Web of Science CrossRef PubMed Google Scholar
Bawden, F. C. & Pirie, N. W. (1938). Nature (London), 141, 513–514. CrossRef CAS Google Scholar
Benson, S. D., Bamford, J. K. H., Bamford, D. H. & Burnett, R. M. (1999). Cell, 98, 825–833. Web of Science CrossRef PubMed CAS Google Scholar
Blanchet, C. E., Zozulya, A. V., Kikhney, A. G., Franke, D., Konarev, P. V., Shang, W., Klaering, R., Robrahn, B., Hermes, C., Cipriani, F., Svergun, D. I. & Roessle, M. (2012). J. Appl. Cryst. 45, 489–495. Web of Science CrossRef CAS IUCr Journals Google Scholar
Blow, D. M., Rossmann, M. G. & Jeffery, B. A. (1964). J. Mol. Biol. 8, 65–78. CrossRef PubMed CAS Google Scholar
Brünger, A. T. (1992). X-PLOR Version 3.1: A System for X-ray Crystallography and NMR. Yale University, Connecticut, USA. Google Scholar
Buehner, M., Ford, G. C., Moras, D., Olsen, K. W. & Rossmann, M. G. (1974). J. Mol. Biol. 82, 563–585. CrossRef CAS PubMed Web of Science Google Scholar
Canady, M. A., Tsuruta, H. & Johnson, J. E. (2001). J. Mol. Biol. 311, 803–814. Web of Science CrossRef PubMed CAS Google Scholar
Chiu, W. & Smith, T. J. (1994). Curr. Opin. Struct. Biol. 4, 219–224. CrossRef CAS Web of Science Google Scholar
Cockburn, J. J., Abrescia, N. G. A., Grimes, J. M., Sutton, G. C., Diprose, J. M., Benevides, J. M., Thomas, G. J., Bamford, J. K. H., Bamford, D. H. & Stuart, D. I. (2004). Nature (London), 432, 122–125. Web of Science CrossRef PubMed CAS Google Scholar
Crick, F. H. C. & Watson, J. D. (1957). Ciba Foundation Symposium – The Nature of Viruses, edited by G. E. W. Wolstenholme & E. C. P. Millar, pp. 5–18. London: Ciba Foundation. doi:10.1002/9780470715239.ch1. Google Scholar
Crowther, R. A. (1971). Philos. Trans. R. Soc. London Ser. B, 261, 221–230. CrossRef CAS Web of Science Google Scholar
Diprose, J. M. (2000). DPhil thesis. University of Oxford. Google Scholar
Dodson, E. J. (2001). Acta Cryst. D57, 1405–1409. Web of Science CrossRef CAS IUCr Journals Google Scholar
Fry, E. E., Abrescia, N. G. A. & Stuart, D. I. (2007). Macromolecular Crystallography: conventional and high-throughput methods, edited by M. R. Sanderson & J. V. Skelly, pp. 245–263. Oxford University Press. Google Scholar
Fry, E., Acharya, R. & Stuart, D. (1993). Acta Cryst. A49, 45–55. CrossRef Web of Science IUCr Journals Google Scholar
Gilbert, R. J., Grimes, J. M. & Stuart, D. I. (2003). Adv. Protein Chem. 64, 37–91. CrossRef PubMed CAS Google Scholar
Grimes, J. M., Burroughs, J. N., Gouet, P., Diprose, J. M., Malby, R., Ziéntara, S., Mertens, P. P. & Stuart, D. I. (1998). Nature (London), 395, 470–478. Web of Science CAS PubMed Google Scholar
Hao, Q., Dodd, F. E., Grossmann, J. G. & Hasnain, S. S. (1999). Acta Cryst. D55, 243–246. Web of Science CrossRef CAS IUCr Journals Google Scholar
Harrison, S. C. & Jack, A. (1975). J. Mol. Biol. 97, 173–191. CrossRef PubMed CAS Web of Science Google Scholar
Harrison, S. C., Olson, A. J., Schutt, C. E., Winkler, F. K. & Bricogne, G. (1978). Nature, 276, 368–373. CrossRef PubMed CAS Web of Science Google Scholar
Huiskonen, J. T., Kivelä, H. M., Bamford, D. H. & Butcher, S. J. (2004). Nature Struct. Mol. Biol. 11, 850–856. Web of Science CrossRef CAS Google Scholar
Jiang, W., Baker, M. L., Jakana, J., Weigele, P. R., King, J. & Chiu, W. (2008). Nature (London), 451, 1130–1134. Web of Science CrossRef PubMed CAS Google Scholar
Johnson, J. E. (2008). J. Struct. Biol. 163, 246–253. Web of Science CrossRef PubMed CAS Google Scholar
Khayat, R., Tang, L., Larson, E. T., Lawrence, C. M., Young, M. & Johnson, J. E. (2005). Proc. Natl Acad. Sci. USA, 102, 18944–18949. Web of Science CrossRef PubMed CAS Google Scholar
Kivelä, H. M., Abrescia, N. G. A., Bamford, J. K. H., Grimes, J. M., Stuart, D. I. & Bamford, D. H. (2008). J. Struct. Biol. 161, 204–210. Web of Science PubMed Google Scholar
Kruger, D. H., Schneck, P. & Gelderblom, H. R. (2000). Lancet, 355, 1713–1717. Web of Science CrossRef PubMed CAS Google Scholar
Lee, K. K., Gan, L., Tsuruta, H., Hendrix, R. W., Duda, R. L. & Johnson, J. E. (2004). J. Mol. Biol. 340, 419–433. Web of Science CrossRef PubMed CAS Google Scholar
Leonard, B. R., Anderegg, J. W., Shulman, S., Kaesberg, P. & Beeman, W. W. (1953). Biochim. Biophys. Acta, 12, 499–507. CrossRef PubMed CAS Web of Science Google Scholar
Liu, H., Jin, L., Koh, S. B. S., Atanasov, I., Schein, S., Wu, L. & Zhou, Z. H. (2010). Science, 329, 1038–1043. Web of Science CrossRef CAS PubMed Google Scholar
Luo, M., Vriend, G., Kamer, G., Minor, I., Arnold, E., Rossmann, M. G., Boege, U., Scraba, D. G., Duke, G. M. & Palmenberg, A. C. (1987). Science, 235, 182–191. CrossRef CAS PubMed Web of Science Google Scholar
Mao, B., Guan, R. & Montelione, G. T. (2011). Structure, 19, 757–766. Web of Science CrossRef CAS PubMed Google Scholar
McCoy, A. J., Grosse-Kunstleve, R. W., Adams, P. D., Winn, M. D., Storoni, L. C. & Read, R. J. (2007). J. Appl. Cryst. 40, 658–674. Web of Science CrossRef CAS IUCr Journals Google Scholar
McCoy, A. J., Grosse-Kunstleve, R. W., Storoni, L. C. & Read, R. J. (2005). Acta Cryst. D61, 458–464. Web of Science CrossRef CAS IUCr Journals Google Scholar
Navaza, J. (2008). Acta Cryst. D64, 70–75. Web of Science CrossRef CAS IUCr Journals Google Scholar
Otwinowski, Z. & Minor, W. (1997). Methods Enzymol. 276, 307–326. CrossRef CAS Web of Science Google Scholar
Plevka, P., Kaufmann, B. & Rossmann, M. G. (2011). Acta Cryst. D67, 568–577. Web of Science CrossRef CAS IUCr Journals Google Scholar
Rayment, I. (1983). Acta Cryst. A39, 102–116. CrossRef CAS Web of Science IUCr Journals Google Scholar
Rossmann, M. G. (1990). Acta Cryst. A46, 73–82. CrossRef CAS Web of Science IUCr Journals Google Scholar
Rossmann, M. G. (1995). Curr. Opin. Struct. Biol. 5, 650–655. CrossRef CAS PubMed Web of Science Google Scholar
Rossmann, M. G. (2000). Acta Cryst. D56, 1341–1349. Web of Science CrossRef CAS IUCr Journals Google Scholar
Rossmann, M. G. & Arnold, E. (1993). International Tables for Crystallography, edited by U. Shmueli, pp. 230–263. Dordrecht: Kluwer Academic Publishers. Google Scholar
Rossmann, M. G. & Blow, D. M. (1962). Acta Cryst. 15, 24–31. CrossRef CAS IUCr Journals Web of Science Google Scholar
Rossmann, M. G., Morais, M. C., Leiman, P. G. & Zhang, W. (2005). Structure, 13, 355–362. Web of Science CrossRef PubMed CAS Google Scholar
Schmidt, P., Kaesberg, P. & Beeman, W. W. (1954). Biochim. Biophys. Acta, 14, 1–11. CrossRef PubMed CAS Web of Science Google Scholar
Stanley, W. M. (1935). Science, 81, 644–645. CrossRef PubMed CAS Google Scholar
Steven, A. C. & Baumeister, W. (2008). J. Struct. Biol. 163, 186–195. Web of Science CrossRef PubMed CAS Google Scholar
Stuart, D. I., Levine, M., Muirhead, H. & Stammers, D. K. (1979). J. Mol. Biol. 134, 109–142. CrossRef CAS PubMed Web of Science Google Scholar
Svergun, D. I. & Koch, M. H. J. (2002). Curr. Opin. Struct. Biol. 12, 654–660. Web of Science CrossRef PubMed CAS Google Scholar
Terwilliger, T. C., DiMaio, F., Read, R. J., Baker, D., Bunkóczi, G., Adams, P. D., Grosse-Kunstleve, R. W., Afonine, P. V. & Echols, N. (2012). J. Struct. Funct. Genomics, 13, 81–90. CrossRef CAS PubMed Google Scholar
Trapani, S., Schoehn, G., Navaza, J. & Abergel, C. (2010). Acta Cryst. D66, 514–521. Web of Science CrossRef CAS IUCr Journals Google Scholar
Tsao, J., Chapman, M. S. & Rossmann, M. G. (1992). Acta Cryst. A48, 293–301. CrossRef IUCr Journals Google Scholar
Villeret, V., Tricot, C., Stalon, V. & Dideberg, O. (1995). Proc. Natl Acad. Sci. USA, 92, 10762–10766. CrossRef CAS PubMed Web of Science Google Scholar
Winn, M. D. et al. (2011). Acta Cryst. D67, 235–242. Web of Science CrossRef CAS IUCr Journals Google Scholar
Xiong, Y. (2008). Acta Cryst. D64, 76–82. Web of Science CrossRef CAS IUCr Journals Google Scholar
Zhang, X., Ge, P., Yu, X., Brannan, J. M., Bi, G., Zhang, Q., Schein, S. & Zhou, Z. H. (2013). Nature Struct. Mol. Biol. 20, 105–110. Web of Science CrossRef Google Scholar
Zhou, Z. H. & Chiu, W. (2003). Adv. Protein Chem. 64, 93–124. CrossRef PubMed CAS Google Scholar
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