radiation damage
Conformational variation of proteins at room temperature is not dominated by radiation damage
aStanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA, bDepartment of Bioengineering and Therapeutic Sciences, UCSF, San Francisco, CA, USA, and cBioscience Department, SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
*Correspondence e-mail: ana@slac.stanford.edu
Protein crystallography data collection at synchrotrons is routinely carried out at cryogenic temperatures to mitigate radiation damage. Although damage still takes place at 100 K and below, the immobilization of free radicals increases the lifetime of the crystals by approximately 100-fold. Recent studies have shown that flash-cooling decreases the heterogeneity of the conformational ensemble and can hide important functional mechanisms from observation. These discoveries have motivated increasing numbers of experiments to be carried out at room temperature. However, the trade-offs between increased risk of radiation damage and increased observation of alternative conformations at room temperature relative to cryogenic temperature have not been examined. A considerable amount of effort has previously been spent studying radiation damage at cryo-temperatures, but the relevance of these studies to room temperature diffraction is not well understood. Here, the effects of radiation damage on the conformational landscapes of three different proteins (T. danielli thaumatin, hen egg-white lysozyme and human cyclophilin A) at room (278 K) and cryogenic (100 K) temperatures are investigated. Increasingly damaged datasets were collected at each temperature, up to a maximum dose of the order of 107 Gy at 100 K and 105 Gy at 278 K. Although it was not possible to discern a clear trend between damage and multiple conformations at either temperature, it was observed that disorder, monitored by B-factor-dependent crystallographic order parameters, increased with higher absorbed dose for the three proteins at 100 K. At 278 K, however, the total increase in this disorder was only statistically significant for thaumatin. A correlation between specific radiation damage affecting side chains and the amount of disorder was not observed. This analysis suggests that elevated conformational heterogeneity in crystal structures at room temperature is observed despite radiation damage, and not as a result thereof.
1. Introduction
The vast majority of macromolecular crystallographic data are collected at cryogenic temperatures. This practice became widely adopted during the 1990s due to the realisation that cryo-cooling reduced radiation damage to the samples during the experiment (Haas & Rossmann, 1970; Hope, 1988). Concurrently, cryostats to maintain the sample in a stable cryo-temperature environment during data collection (Cosier & Glazer, 1986) and improved and cryo-cooling methods were developed (Garman & Schneider, 1997; Teng & Moffat, 1998; Rodgers, 1997; Garman, 1999; Pflugrath, 2004). The increase in the lifetime of the crystal at 100 K compared with room temperature is around two orders of magnitude (Nave & Garman, 2005), although some variation can occur depending on the sample, solvent content and dose rate (Warkentin & Thorne, 2010; Kmetko et al., 2011; Southworth-Davies et al., 2007; Leal et al., 2013).
Despite the notable advantage of data collection at cryogenic temperatures for reducing radiation damage, there are several important considerations that can motivate collecting data at higher temperatures. The increase in mosaicity in cryo-cooled crystals can result in an excessive number of overlapped reflections in crystals with large unit cells; for example, with large macromolecular complexes and viruses (Gilbert et al., 2003; Rossmann, 1999). Experiments at multiple temperatures can provide important information about protein conformational dynamics (Frauenfelder et al., 1979; Tilton et al., 1992; Saikrishnan et al., 2005, Schmidt et al., 2009; Weik & Colletier, 2010; Woldeyes et al., 2014; Keedy et al., 2015a), and changes of temperature can be used to control chemical reactions and observe structural intermediates (Bourgeois & Royant, 2005; Colletier et al., 2008). Furthermore, because it can induce structural changes and inhibit thermal motions, crystal cryo-cooling can obscure interpretation of the structure and potentially lead to erroneous conclusions regarding functional mechanisms (Deacon et al., 1997; Scheidig et al., 1999; Dunlop et al., 2005; Fraser et al., 2011; Keedy et al., 2014; Fischer et al., 2015). For these reasons, the practice of collecting data at room temperature is likely to continue and even grow in popularity.
X-ray free-electron lasers (XFELs) can avoid radiation damage by the `diffract-before-destruct' approach (Neutze et al., 2000) which was experimentally confirmed with doses up to 400 MGy (Chapman et al., 2011, 2014; Boutet et al., 2012). At synchrotron sources, where most experiments still take place, the problems posed by the shorter lifetime of the samples at room temperature can be mitigated by combining partial datasets from multiple samples or different parts of the same sample (Brodersen et al., 2003; Axford et al., 2012; Stellato et al., 2014). However, radiation damage remains a particular concern for studies of molecular mechanisms and protein function because it could potentially reorganize the conformational distributions even at low doses. In cryo-cooled crystals, the specific effects of can be explained by reduction by photoelectrons (reduction of metal centers, separation of disulfide bridges) or oxidation by electron holes (decarboxylation of glutamate and aspartate residues). Active-site acidic side chains have been shown to be particularly sensitive (Fioravanti et al., 2007). Often, residues surrounding damaged sites reorganize (Burmeister, 2000; Ravelli & McSweeney, 2000; Weik et al., 2000; Ravelli & Garman, 2006). At room temperature, the increased mobility of free radicals and protein domains results in quantitative and qualitative differences in the sensitivity of specific residues and domains to For example, Warkentin et al. (2012) found that solvent-exposed turns are more sensitive at room temperatures, while below 180 K increased sensitivity can be correlated with poor local packing. Juers & Weik (2011) also reported higher temperature factors (B-factors) for residues near solvent channels and more types of residues being damaged at 160 K than at 100 K.
Here, we have examined the effects of radiation damage on conformational distributions to determine its impact on studies where disorder and conformational heterogeneity play an important role in the activity of a macromolecule (van den Bedem, et al., 2013; Woldeyes et al., 2014; Fischer et al., 2015; Bhabha et al., 2015). A specific aim of the experiment described below is to determine whether radiation damage could play a role in the appearance or disappearance of biologically relevant alternative conformations and how it affects the inherent disorder in structures at 100 K and room temperature. We used qFit multi-conformer models (van den Bedem et al., 2009; Keedy et al., 2015b) to interrogate differences in the conformational landscape of hen egg-white lysozyme (HEWL), Thaumatococcus daniellii thaumatin, and the human proline isomerase cyclophilin A (CypA) at 100 K and 278 K after increasing amounts of irradiation in an X-ray beam. Crystals of these proteins diffract to high resolution, which makes it possible to fit alternate conformations. CypA is of special interest, since it is a well characterized dynamic enzyme where minor active-site side-chain conformations, absent in cryogenic electron-density maps, help explain the catalytic function of the enzyme, which isomerizes its substrate via correlated motions of the side chains (Fraser et al., 2009). Comparison of radiation damage effects at cryogenic versus room temperature is complicated by the rapid decay of the crystals at room temperature. Thus, to be able to compare the structural conformational variety at roughly similar stages of decay, the crystals were subjected to very different doses at the two different temperatures, with the maximum dose at 100 K being about 30 MGy [the conventional limit for experiments at cryogenic temperatures (Owen et al., 2006)], and about two orders of magnitude less at 278 K. Within each of those dose ranges we modelled and quantified alternative conformations as a function of accumulated dose.
2. Methods
2.1. Crystal preparation
HEWL lysozyme tetragonal (P43212) crystals were grown by vapour diffusion from drops containing 40–60 mg ml−1 solution of protein and well solution (1.0 M sodium chloride in a 50 mM sodium acetate buffer pH = 4.5). The crystals used for data collection at 100 K were cryo-cooled in liquid nitrogen after dipping them in mother liquor containing 25–30% ethylene glycol.
T. daniellii thaumatin crystals belonging to P41212 were grown by vapour diffusion, as described by Nanao et al. (2005), in 0.9 M Na/K tartrate, 100 mM HEPES pH = 7.4 and 15% glycerol, and cryo-protected for data collection at 100 K in mother liquor containing 30% glycerol.
Wild-type CypA was produced and crystallized in the P212121 as reported by Fraser et al. (2009). For data collection at 100 K, the crystals were cryo-protected in paratone oil.
All the crystals used for data collection at 278 K were mounted in cryo-mounts covered with low background MicroRT capillaries from MiTeGen containing well solution in the tip.
2.2. Data collection
Data were collected following the same overall protocol for the three proteins (see details in Table S1 of the supporting information) with the beamline control and data collection software Blu-Ice (Soltis et al., 2008; McPhillips et al., 2002). Before data collection, estimates of the maximum dose for each crystal were obtained with RADDOSE v2 (Murray et al., 2004; Paithankar & Garman, 2010) via WebIce (González et al., 2008). The diffraction-weighted dose (DWD), a metric proposed by Zeldin et al. (2013a) that takes into account the different volumes of the crystal being exposed during data collection and thus better representing the average damage received by the crystal, was afterwards recalculated using RADDOSE-3D (Zeldin et al., 2013b). The dose rate was around 30 kGy s−1. HEWL and thaumatin data were collected on beamline BL14-1, with a marMosaic325 detector at an energy of 10.2 keV. CypA data were collected on beamline BL7-1, equipped with an ADSC 315 detector using an energy of 11.27 keV. An Oxford CryoJet was used to maintain the temperature constant at 100 K or 278 K during data collection.
For data collection at 100 K, several consecutive datasets were collected from the same crystal until a total maximum accumulated dose around 30 MGy was reached. At this total dose, both a noticeable decrease in diffracted intensities and specific damage are expected (Owen et al., 2006). The increase per data set of the DWD was 1.11 MGy for CypA, 1.86 MGy for thaumatin and 1.75 MGy for HEWL. At 278 K, the total maximum dose was limited to less than 0.3 MGy, almost two orders of magnitude less than for the data collection at 100 K. This dose did not permit the collection of full datasets at different stages of damage from a single-crystal to a sufficiently high resolution to model multiple conformations. We therefore used several crystals, collecting consecutive partial datasets from a small rotation wedge (typically a few degrees) that resulted in a DWD of 16 kGy per wedge for CypA, 23 kGy for thaumatin and 28 kGy for HEWL. These partial datasets were then combined to obtain fairly complete datasets. Decay of the diffraction was evidenced by a decrease in the resolution of the most damaged data.
2.3. Data processing
All the data were autoindexed and processed with XDS (Kabsch, 2010). The CCP4 programs POINTLESS and AIMLESS (Winn et al., 2011; Evans, 2006, 2011) were used to verify the symmetry and sort, scale and merge the reflections, both for single-crystal and multiple-crystal datasets. Amplitudes were calculated with TRUNCATE (Winn et al., 2011). The data processing statistics are shown in Table 1. For each protein, the same initial models were refined independently against each dataset. Initial was carried out with REFMAC (Murshudov et al., 1997). The qFit 1.0 algorithm was used to examine and model alternative interpretations of the X-ray (van den Bedem et al., 2009; Keedy et al., 2015b). Atomic position and occupancies of the qFit multiconformer models were further refined with PHENIX (Afonine et al., 2012). For HEWL and thaumatin we used all the reflections available, relying on the software to downweight the contribution of weak reflections; for CypA, however, the results were not satisfactory when including the high-resolution reflections, perhaps because of the lower completeness in the highest resolution shells, and we applied a resolution cutoff at 1.7 Å, still sufficient to model double conformations. In all cases, the resulting models were inspected with the program Coot (Emsley et al., 2010) and manual corrections were made where necessary. The are shown in Table S2.
|
2.4. Characterization of conformational redistribution
The number of individual residues with alternative conformations present in the models were counted to evaluate the conformational ensembles as a function of temperature and radiation damage. To determine which conformations represented well differentiated positions of the side chain, as opposed to oscillations around the same rotamer or energy well, the average root-mean-square difference (RMSD) between the non-hydrogen atoms of alternate conformations was calculated with LSQKAB (Kabsch, 1976). An average difference of 1.0 Å was used as the lower cutoff value.
2.5. Characterization of conformational dynamics
We examined the effects of radiation damage on conformational dynamics using the B-factor-dependent, multi-conformer crystallographic order parameters S2 proposed by Fenwick et al. (2014). These order parameters include both harmonic contributions, encoded by the temperature factors, and non-harmonic contributions, encoded by occupancies and displacements in coordinates around a given bond vector. The crystallographic order parameters correlate well with NMR-determined order parameters and provide a meaningful quantification of the degree of order in the structure. The analysis was applied to the bond most closely associated with the χ1 side-chain dihedral angle, using Cβ—Xβ (where X = C or O) for most amino acids, Cα—Cβ for Ala, and Cα—Hα for Gly (Keedy et al., 2015a). Because S2 is a measure of order, 1 − S2 was used as a measure of disorder.
The average disorder for all residues in each structure was calculated. In particular, this analysis includes the CypA active-site residues known to be involved in correlated, functional motions in the room-temperature models.
2.6. Site-specific characterization of radiation damage
To detect the sites most affected by radiation damage, the Fon − Fo1 difference maps were examined using the σ-weighted coefficients from the lowest and highest dose datasets. Peaks in the map were searched and sorted with PEAKMAX (Winn et al., 2011). The maps were visually inspected with Coot.
3. Results
Table 2 shows the number of residues with multiple conformations for each dataset. Side-chain alternative conformations are more abundant at 278 K than at 100 K for thaumatin and CypA, which is consistent with previous observations (Fraser et al., 2011; van den Bedem et al., 2013), but not for HEWL. There was no evidence found of cryoprotectant molecules binding to side chains with different conformations at 100 K. The number of multiple conformations seen even for the most damaged models indicates that conformational heterogeneity can be observed without interference from radiation damage. There is a decreasing trend for the total number of conformations as a function of dose for all three proteins at 278 K, but these trends are not statistically significant. By contrast, there is essentially no trend for number of conformations as a function of dose at 100 K for any of the three proteins.
|
Many of the alternate conformations in the structures are unaffected by increasing damage. However, for each data set a small number of conformers vanish or appear in a non-systematic manner. These changes appear to be incidental and take place in sites where there is ambiguity in the interpretation of the electron density. They fall into one of these three types:
(a) Alternate conformations clustered around a single rotamer.
(b) Side chains of solvent exposed residues, or residues with high B-factors. In these cases the electron density for the minor conformers is not very well defined.
(c) Rotamers enabled by alternate main-chain conformations (Davis et al., 2006) in buried, ordered residues, where the alternate side-chain conformations fit reasonably well in the electron density for both rotamers (see example in Fig. 1).
In general, movement of side chains was not associated with a strong peak in the Fon − Fo1 based on the lowest and highest dose datasets (see Table S3). We also examined the sites with large peaks in the Fon − Fo1 maps to look for conformational variation. At 278 K, large differences appear for carboxyl O atoms and amine nitrogens in the main chain, and also cysteines, phenylalanines and the polar side-chains asparagines and threonines. At 100 K, damage was concentrated mainly on cysteines, methionines, aspartates, glutamates and main-chain carboxyl O atoms. The only residues where a distinct alternate conformation could be clearly attributed to radiation damage were some of the cysteines in disulfide bridges in HEWL and thaumatin at 100 K. Negative electron density around the sulfur sites suggested that the cysteines also sustained damage at room temperature, but alternative conformations were not found by qFit (Fig. 2).
Residues implicated in enzymatic activity of CypA (F113, M61, S99 and the catalytic residue R55) showed only minor electron density changes as a function of absorbed dose (see Fig. 3), suggesting that radiation damage is not responsible for the appearance of distinct conformations.
We next used a measure of disorder in multiconformer models, the complement of the B-order parameter (1 − S2), to track the effect of radiation damage on in each temperature regime (Fig. 4). Interestingly, this metric suggests a clear correlation between absorbed dose and at cryogenic temperature, but not at room temperature (Fig. 4). A linear fit of 1 − S2, averaged over all residues, against dose indicates a highly significant increase in disorder at 100 K from lowest to highest radiation dose: around 20% for thaumatin (p < 0.005) and around 35% for CypA (p < 10−6) between the first and last dataset in the series. The total increase for HEWL is not significant (p = 0.256), although similar to that of thaumatin. At 278 K, the disorder increases by only 2% and 3%, for HEWL and CypA, respectively, and is not statistically significant (p = 0.740 and 0.846, respectively). The increase of 8% for thaumatin (p = 0.009) is statistically significant, but 2.5 times smaller than at 278 K. Surprisingly, the value at low dose for 1 − S2 for thaumatin was higher at 100 K than at 278 K. At low dose, the data collected at 100 K also had a higher average B-factor (about 26 Å2 for the lowest dose dataset) than the data at 278 K (19 Å2), which is uncommon, but thaumatin cryo-structures in the Protein Data Bank (PDB) exhibit a wide range of values from 7.6 Å2 (PDB ID 4c3c) to 23.6 Å2 (PDB ID 3v88), indicating that the high value at 100 K could be due to sample-to-sample variation.
Fig. 5 shows 1 − S2 for the CypA side chains F113, M61, S99 and R55 at 278 K. None of these residues shows a statistically significant relationship between dose and disorder. The electron density maps do not show many changes as the dose increases, except for an overall reduction in the density level, as shown in Fig. 3, consistent with the global radiation damage and loss of resolution.
4. Discussion
Automated software for modelling multiple conformers in low-level electron density has enabled detailed, unbiased analysis of the conformational ensemble of biological molecules, especially for data collected at room temperature. Here, the conformational ensembles of three proteins subjected to increasing doses of radiation were examined for signs of damage at 100 K and 278 K. We found that crystal structures respond differently to increasing dose at these temperatures. At both temperatures the conformational heterogeneity (in terms of the number of alternative conformations) of the crystal structures is at most minimally affected by dose. However, cryogenic crystals respond to dose with elevated conformational dynamics encoded by the multi-conformer B-factors, these two facts together suggest that the dominant effects of radiation damage at cryogenic temperatures can be modelled by B-factors (Warkentin & Thorne, 2010).
up to DWDs close to 10 MGy, exceeding the disorder values measured for the room-temperature structures. Because this type of is based on alternative conformations andBy contrast, the order parameters of room-temperature crystals were generally unaffected by the much lower dose accumulated over the time of the experiment. The sequential radiation damage model of protein decay in X-rays at room temperature (Sygusch & Allaire, 1988; Southworth-Davies et al., 2007) predicts that crystalline samples go through a partially disordered phase that contributes to diffraction to high angle before becoming totally disordered. While this model predicts a significant increase in disorder during the our analysis has not found clear evidence of this process. This discrepancy may be due to the difference between the ordered and partially disordered fractions being too subtle to be modelled using our approaches. Indeed, the conformational changes may be too subtle to detect in the electron density with existing tools, such as qFit or Ringer (Lang et al., 2014). Alternatively, the dose used in our study may not be high enough to detect the intermediate state; nevertheless, it was sufficient to determine high-resolution room-temperature structures. Our findings are also consistent with a fast transition from ordered to totally disordered structure, with only the more ordered fraction contributing to the electron density.
We confirmed that, despite the faster decay of crystals at room temperature, many sites where damage is concentrated at 100 K do not appear affected to the same extent at room temperature. Although the comparison between datasets shows evidence of specific radiation damage, the progression is not the same in the two temperature regimes: the most notable effects at 100 K (decarboxylation of acidic side chains and reduction of disulfide bridges) are less prominent at 278 K. This difference could explain the results of Roedig et al. (2016), who found no visible specific damage at room temperature for doses up to 0.5 MGy, which is of the same order of magnitude as the doses used at 278 K in this study. The difference in response by specific sites to radiation between the two temperature regimes could be an effect of the much smaller dose received by the crystals at room temperature being deposited over a larger number of susceptible sites: the crystal is already destroyed by the time some changes would be clearly detectable. However, the amount of damage to a specific site may be different at different dose rates. If this is the case, data collection at high dose rates to outrun radiation damage at room temperature (Owen et al., 2012) might counter-intuitively result in more extensive specific damage affecting the structure. Also, at temperatures slightly above the where more radical species are mobile but the crystal will tolerate a larger dose (Warkentin et al., 2013), the damage to specific sites over the course of the experiment could be more visible. Structures at these intermediate temperatures are likely to be similar to the ones at room temperature, making this intermediate temperature regime interesting for future experiments to examine the temperature-dependent effects of radiation damage.
5. Conclusions
Our results signify that there is no relationship between specific radiation damage at side chains and large shifts in their conformations at 278 and 100 K, except for the case of broken disulfide bridges at 100 K. Only weak correlations were found between disorder and dose at 278 K over typical doses used for experiments at room temperature. Therefore, it seems unlikely that radiation damage is responsible for the alternate conformations responsible for biological activity in, for example, CypA. These findings were consistent for the three proteins studied, suggesting that conformational dynamics at room temperature is generally unaffected by radiation damage, if the experiment is carefully designed. However, at sufficiently high dose, radiation damage could mask minor conformers due to overall loss of electron density. Moreover, although specific damage to key residues was not detected here, it cannot be ruled out in the general case. As long as experiments at X-ray free-electron laser sources are not commonplace, careful monitoring of experiments based on the detection of subtle conformational changes will be a necessity.
The approach used here, using multiple crystals to collect increasingly damaged data with multi-conformer qFit models as readout, can be useful to monitor trends and effects of radiation damage on experiments at different temperatures and conditions. Although the analysis methods we used are limited to samples that diffract to high resolution and well ordered areas of the protein, any consistent findings could be of general use.
Supporting information
Supplementary tables listing https://doi.org/10.1107/S1600577516017343/gm5050sup1.pdf
and difference map DOI:Acknowledgements
The authors thank Shawn Kann for helping collect and process some of the datasets used in the experiment. JSF is supported by NIH GM110580 and NSF STC-1231306. DAK is supported by a fellowship from the A. P. Giannini Foundation. Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, is supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences under Contract No. DE-AC02-76SF00515. The SSRL Structural Molecular Biology Program is supported by the DOE Office of Biological and Environmental Research, and by the National Institutes of Health, National Institute of General Medical Sciences (including P41GM103393). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of NIGMS or NIH.
References
Afonine, P. V., Grosse-Kunstleve, R. W., Echols, N., Headd, J. J., Moriarty, N. W., Mustyakimov, M., Terwilliger, T. C., Urzhumtsev, A., Zwart, P. H. & Adams, P. D. (2012). Acta Cryst. D68, 352–367. Web of Science CrossRef CAS IUCr Journals Google Scholar
Axford, D., Owen, R. L., Aishima, J., Foadi, J., Morgan, A. W., Robinson, J. I., Nettleship, J. E., Owens, R. J., Moraes, I., Fry, E. E., Grimes, J. M., Harlos, K., Kotecha, A., Ren, J., Sutton, G., Walter, T. S., Stuart, D. I. & Evans, G. (2012). Acta Cryst. D68, 592–600. Web of Science CrossRef CAS IUCr Journals Google Scholar
Bedem, H. van den, Bhabha, G., Yang, K., Wright, P. E. & Fraser, J. S. (2013). Nat. Methods, 10, 896–902. Web of Science PubMed Google Scholar
Bedem, H. van den, Dhanik, A., Latombe, J.-C. & Deacon, A. M. (2009). Acta Cryst. D65, 1107–1117. Web of Science CrossRef IUCr Journals Google Scholar
Bhabha, G., Biel, J. & Fraser, T. (2015). Acc. Chem. Res. 48, 423–430. CrossRef CAS Google Scholar
Bourgeois, D. & Royant, A. (2005). Curr. Opin. Struct. Biol. 15, 538–547. Web of Science CrossRef PubMed CAS Google Scholar
Boutet, S., Lomb, L., Williams, G. J., Barends, T. R. M., Aquila, A., Doak, R. B., Weierstall, U., DePonte, D. P., Steinbrener, J., Shoeman, R. L., Messerschmidt, M., Barty, A., White, T. A., Kassemeyer, S., Kirian, R. A., Seibert, M. M., Montanez, P. A., Kenney, C., Herbst, R., Hart, P., Pines, J., Haller, G., Gruner, S. M., Philipp, H. T., Tate, M. W., Hromalik, M., Koerner, L. J., van Bakel, N., Morse, J., Ghonsalves, W., Arnlund, D., Bogan, M. J., Caleman, C., Fromme, R., Hampton, C. Y., Hunter, M. S., Johansson, L. C., Katona, G., Kupitz, C., Liang, M., Martin, A. V., Nass, K., Redecke, L., Stellato, F., Timneanu, N., Wang, D., Zatsepin, N. A., Schafer, D., Defever, J., Neutze, R., Fromme, P., Spence, J. C. H., Chapman, H. N. & Schlichting, I. (2012). Science, 337, 362–364. Web of Science CrossRef CAS PubMed Google Scholar
Brodersen, D. E., Clemons, W. M., Carter, A. P., Wimberly, B. T. & Ramakrishnan, V. (2003). Acta Cryst. D59, 2044–2050. Web of Science CrossRef CAS IUCr Journals Google Scholar
Burmeister, W. P. (2000). Acta Cryst. D56, 328–341. Web of Science CrossRef CAS IUCr Journals Google Scholar
Chapman, H. N., Caleman, C. & Timneanu, N. (2014). Philos. Trans. R. Soc. B, 369, 20130313. Web of Science CrossRef Google Scholar
Chapman, H. N., Fromme, P., Barty, A., White, T. A., Kirian, R. A., Aquila, A., Hunter, M. S., Schulz, J., DePonte, D. P., Weierstall, U., Doak, R. B., Maia, F. R. N. C., Martin, A. V., Schlichting, I., Lomb, L., Coppola, N., Shoeman, R. L., Epp, S. W., Hartmann, R., Rolles, D., Rudenko, A., Foucar, L., Kimmel, N., Weidenspointner, G., Holl, P., Liang, M., Barthelmess, M., Caleman, C., Boutet, S., Bogan, M. J., Krzywinski, J., Bostedt, C., Bajt, S., Gumprecht, L., Rudek, B., Erk, B., Schmidt, C., Hömke, A., Reich, C., Pietschner, D., Strüder, L., Hauser, G., Gorke, H., Ullrich, J., Herrmann, S., Schaller, G., Schopper, F., Soltau, H., Kühnel, K., Messerschmidt, M., Bozek, J. D., Hau-Riege, S. P., Frank, M., Hampton, C. Y., Sierra, R. G., Starodub, D., Williams, G. J., Hajdu, J., Timneanu, N., Seibert, M. M., Andreasson, J., Rocker, A., Jönsson, O., Svenda, M., Stern, S., Nass, K., Andritschke, R., Schröter, C., Krasniqi, F., Bott, M., Schmidt, K. E., Wang, X., Grotjohann, I., Holton, J. M., Barends, T. R. M., Neutze, R., Marchesini, S., Fromme, R., Schorb, S., Rupp, D., Adolph, M., Gorkhover, T., Andersson, I., Hirsemann, H., Potdevin, G., Graafsma, H., Nilsson, B. & Spence, J. C. H. (2011). Nature (London), 470, 73–77. Web of Science CrossRef CAS PubMed Google Scholar
Colletier, J.-P., Bourgeois, D., Sanson, B., Fournier, D., Sussman, J. L., Silman, I. & Weik, M. (2008). Proc. Natl Acad. Sci. USA, 105, 11742–11747. Web of Science CrossRef PubMed CAS Google Scholar
Cosier, J. & Glazer, A. M. (1986). J. Appl. Cryst. 19, 105–107. CrossRef CAS Web of Science IUCr Journals Google Scholar
Davis, I. W., Arendall, W. B., Richardson, D. D. & Richardson, J. S. (2006). Structure, 14, 265–274. CrossRef CAS Google Scholar
Deacon, A., Gleichmann, T., Kalb (Gilboa), A. J., Price, H., Raftery, J., Bradbrook, G., Yariv, J. & Helliwell, J. R. (1997). Faraday Trans. 93, 4305–4312. Google Scholar
Dunlop, K. V., Irvin, R. T. & Hazes, B. (2005). Acta Cryst. D61, 80–87. Web of Science CrossRef CAS IUCr Journals Google Scholar
Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. (2010). Acta Cryst. D66, 486–501. Web of Science CrossRef CAS IUCr Journals Google Scholar
Evans, P. (2006). Acta Cryst. D62, 72–82. Web of Science CrossRef CAS IUCr Journals Google Scholar
Evans, P. R. (2011). Acta Cryst. D67, 282–292. Web of Science CrossRef CAS IUCr Journals Google Scholar
Fenwick, R. B., van den Bedem, H., Fraser, J. S. & Wright, P. E. (2014). Proc. Natl Acad. Sci. USA, 111, 445–454. CrossRef Google Scholar
Fioravanti, E., Vellieux, F. M. D., Amara, P., Madern, D. & Weik, M. (2007). J. Synchrotron Rad. 14, 84–91. Web of Science CrossRef CAS IUCr Journals Google Scholar
Fischer, M., Shoichet, B. K. & Fraser, J. S. (2015). ChemBioChem, 16, 1560–1564. Web of Science CrossRef CAS PubMed Google Scholar
Fraser, J. S., Clarkson, M. W., Degnan, S. C., Erion, R., Kern, D. & Alber, T. (2009). Nature (London), 462, 669–673. Web of Science CrossRef PubMed CAS Google Scholar
Fraser, J. S., van den Bedem, H., Samelson, A. J., Lang, P. T., Holton, J. M., Echols, N. & Alber, T. (2011). Proc. Natl Acad. Sci. USA, 108, 16247–16252. Web of Science CrossRef CAS PubMed Google Scholar
Frauenfelder, H., Petsko, G. A. & Tsernoglou, D. (1979). Nature (London), 280, 558–563. CrossRef CAS PubMed Web of Science Google Scholar
Garman, E. (1999). Acta Cryst. D55, 1641–1653. Web of Science CrossRef CAS IUCr Journals Google Scholar
Garman, E. F. & Schneider, T. R. (1997). J. Appl. Cryst. 30, 211–237. CrossRef Web of Science IUCr Journals Google Scholar
Gilbert, R. J. C., Grimes, J. M. & Stuart, D. I. (2003). Adv. Protein Chem. 64, 37–91. CrossRef PubMed CAS Google Scholar
González, A., Moorhead, P., McPhillips, S. E., Song, J., Sharp, K., Taylor, J. R., Adams, P. D., Sauter, N. K. & Soltis, S. M. (2008). J. Appl. Cryst. 41, 176–184. Web of Science CrossRef IUCr Journals Google Scholar
Haas, D. J. & Rossmann, M. G. (1970). Acta Cryst. B26, 998–1004. CrossRef CAS IUCr Journals Web of Science Google Scholar
Hope, H. (1988). Acta Cryst. B44, 22–26. CrossRef CAS Web of Science IUCr Journals Google Scholar
Juers, D. H. & Weik, M. (2011). J. Synchrotron Rad. 18, 329–337. Web of Science CrossRef CAS IUCr Journals Google Scholar
Kabsch, W. (1976). Acta Cryst. A32, 922–923. CrossRef IUCr Journals Web of Science Google Scholar
Kabsch, W. (2010). Acta Cryst. D66, 125–132. Web of Science CrossRef CAS IUCr Journals Google Scholar
Keedy, D. A., Fraser, J. S. & van den Bedem, H. (2015b). PLoS Comput. Biol. 11, e1004507. CrossRef Google Scholar
Keedy, D. A., Kenner, L. R., Warkentin, M., Woldeyes, R. A., Hopkins, J. B., Thompson, M. C., Brewster, A. S., Van Benschoten, A. H., Baxter, E. L., Uervirojnangkoorn, M., McPhillips, S. E., Song, J., Alonso-Mori, R., Holton, J. M., Weis, W. I., Brunger, A. T., Soltis, S. M., Lemke, H., Gonzalez, A., Sauter, N. K., Cohen, A. E., van den Bedem, H., Thorne, R. E. & Fraser, J. S. (2015a). eLife, e07574. Google Scholar
Keedy, D. A., van den Bedem, H., Sivak, D. A., Petsko, G. A., Ringe, D., Wilson, M. A. & Fraser, J. S. (2014). Structure, 22, 899–910. Web of Science CrossRef CAS PubMed Google Scholar
Kmetko, J., Warkentin, M., Englich, U. & Thorne, R. E. (2011). Acta Cryst. D67, 881–893. Web of Science CrossRef CAS IUCr Journals Google Scholar
Lang, P. T., Holton, J. M., Fraser, J. S. & Alber, T. (2014). Proc. Natl Acad. Sci. USA, 111, 237–242. Web of Science CrossRef CAS PubMed Google Scholar
Leal, R. M. F., Bourenkov, G., Russi, S. & Popov, A. N. (2013). J. Synchrotron Rad. 20, 14–22. Web of Science CrossRef CAS IUCr Journals Google Scholar
McPhillips, T. M., McPhillips, S. E., Chiu, H.-J., Cohen, A. E., Deacon, A. M., Ellis, P. J., Garman, E., Gonzalez, A., Sauter, N. K., Phizackerley, R. P., Soltis, S. M. & Kuhn, P. (2002). J. Synchrotron Rad. 9, 401–406. Web of Science CrossRef CAS IUCr Journals Google Scholar
Murray, J. W., Garman, E. F. & Ravelli, R. B. G. (2004). J. Appl. Cryst. 37, 513–522. Web of Science CrossRef CAS IUCr Journals Google Scholar
Murshudov, G. N., Vagin, A. A. & Dodson, E. J. (1997). Acta Cryst. D53, 240–255. CrossRef CAS Web of Science IUCr Journals Google Scholar
Nanao, M. H., Sheldrick, G. M. & Ravelli, R. B. G. (2005). Acta Cryst. D61, 1227–1237. Web of Science CrossRef CAS IUCr Journals Google Scholar
Nave, C. & Garman, E. F. (2005). J. Synchrotron Rad. 12, 257–260. Web of Science CrossRef CAS IUCr Journals Google Scholar
Neutze, R., Wouts, R., van der Spoel, D., Weckert, E. & Hajdu, J. (2000). Nature (London), 406, 752–757. Web of Science CrossRef PubMed CAS Google Scholar
Owen, R. L., Axford, D., Nettleship, J. E., Owens, R. J., Robinson, J. I., Morgan, A. W., Doré, A. S., Lebon, G., Tate, C. G., Fry, E. E., Ren, J., Stuart, D. I. & Evans, G. (2012). Acta Cryst. D68, 810–818. Web of Science CrossRef CAS IUCr Journals Google Scholar
Owen, R. L., Rudino-Pinera, E. & Garman, E. F. (2006). Proc. Natl Acad. Sci. USA, 103, 4912–4917. Web of Science CrossRef PubMed CAS Google Scholar
Paithankar, K. S. & Garman, E. F. (2010). Acta Cryst. D66, 381–388. Web of Science CrossRef CAS IUCr Journals Google Scholar
Pflugrath, J. W. (2004). Methods, 34, 415–423. Web of Science CrossRef PubMed CAS Google Scholar
Ravelli, R. B. G. & Garman, E. (2006). Curr. Opin. Struct. Biol. 16, 624–629. Web of Science CrossRef PubMed CAS Google Scholar
Ravelli, R. B. G. & McSweeney, S. (2000). Structure, 8, 315–328. Web of Science CrossRef PubMed CAS Google Scholar
Rodgers, D. W. (1997). Methods Enzymol. 276, 183–203. CrossRef CAS Web of Science Google Scholar
Roedig, P., Duman, R., Sanchez-Weatherby, J., Vartiainen, I., Burkhardt, A., Warmer, M., David, C., Wagner, A. & Meents, A. (2016). J. Appl. Cryst. 49, 968–975. Web of Science CrossRef CAS IUCr Journals Google Scholar
Rossmann, M. G. (1999). J. Synchrotron Rad. 6, 816–821. Web of Science CrossRef IUCr Journals Google Scholar
Saikrishnan, K., Kalapala, S. K., Varshney, U. & Vijayan, M. (2005). J. Mol. Biol. 345, 29–38. Web of Science CrossRef PubMed CAS Google Scholar
Scheidig, A. J., Burmester, C. & Goody, R. S. (1999). Structure, 7, 1311–1324. Web of Science CrossRef PubMed CAS Google Scholar
Schmidt, M., Achterhold, K., Prusakov, V. & Parak, F. G. (2009). Eur. Biophys. J. 38, 687–700. Web of Science CrossRef PubMed CAS Google Scholar
Soltis, S. M., Cohen, A. E., Deacon, A., Eriksson, T., González, A., McPhillips, S., Chui, H., Dunten, P., Hollenbeck, M., Mathews, I., Miller, M., Moorhead, P., Phizackerley, R. P., Smith, C., Song, J., van dem Bedem, H., Ellis, P., Kuhn, P., McPhillips, T., Sauter, N., Sharp, K., Tsyba, I. & Wolf, G. (2008). Acta Cryst. D64, 1210–1221. Web of Science CrossRef IUCr Journals Google Scholar
Southworth-Davies, R. J., Medina, M. A., Carmichael, I. & Garman, E. F. (2007). Structure, 15, 1531–1541. Web of Science CrossRef PubMed CAS Google Scholar
Stellato, F., Oberthür, D., Liang, M., Bean, R., Gati, C., Yefanov, O., Barty, A., Burkhardt, A., Fischer, P., Galli, L., Kirian, R. A., Meyer, J., Panneerselvam, S., Yoon, C. H., Chervinskii, F., Speller, E., White, T. A., Betzel, C., Meents, A. & Chapman, H. N. (2014). IUCrJ, 1, 204–212. Web of Science CrossRef CAS PubMed IUCr Journals Google Scholar
Sygusch, J. & Allaire, M. (1988). Acta Cryst. A44, 443–448. CrossRef CAS Web of Science IUCr Journals Google Scholar
Teng, T.-Y. & Moffat, K. (1998). J. Appl. Cryst. 31, 252–257. Web of Science CrossRef CAS IUCr Journals Google Scholar
Tilton, R. F. Jr, Dewan, J. C. & Petsko, G. A. (1992). Biochemistry, 31, 2469–2481. CrossRef PubMed CAS Web of Science Google Scholar
Warkentin, M., Badeau, R., Hopkins, J. B. & Thorne, R. E. (2012). Acta Cryst. D68, 1108–1117. Web of Science CrossRef IUCr Journals Google Scholar
Warkentin, M., Hopkins, J. B., Badeau, R., Mulichak, A. M., Keefe, L. J. & Thorne, R. E. (2013). J. Synchrotron Rad. 20, 7–13. Web of Science CrossRef CAS IUCr Journals Google Scholar
Warkentin, M. & Thorne, R. E. (2010). Acta Cryst. D66, 1092–1100. Web of Science CrossRef IUCr Journals Google Scholar
Weik, M. & Colletier, J.-P. (2010). Acta Cryst. D66, 437–446. Web of Science CrossRef CAS IUCr Journals Google Scholar
Weik, M., Ravelli, R. B. G., Kryger, G., McSweeney, S., Raves, M. L., Harel, M., Gros, P., Silman, I., Kroon, J. & Sussman, J. L. (2000). Proc. Natl Acad. Sci. USA, 97, 623–628. Web of Science CrossRef PubMed CAS Google Scholar
Winn, M. D., Ballard, C. C., Cowtan, K. D., Dodson, E. J., Emsley, P., Evans, P. R., Keegan, R. M., Krissinel, E. B., Leslie, A. G. W., McCoy, A., McNicholas, S. J., Murshudov, G. N., Pannu, N. S., Potterton, E. A., Powell, H. R., Read, R. J., Vagin, A. & Wilson, K. S. (2011). Acta Cryst. D67, 235–242. Web of Science CrossRef CAS IUCr Journals Google Scholar
Woldeyes, R. A., Sivak, D. A. & Fraser, J. S. (2014). Curr. Opin. Struct. Biol. 28, 56–62. Web of Science CrossRef CAS PubMed Google Scholar
Zeldin, O. B., Brockhauser, S., Bremridge, J., Holton, J. M. & Garman, E. F. (2013a). Proc. Natl Acad. Sci. USA, 110, 20551–20556. Web of Science CrossRef CAS PubMed Google Scholar
Zeldin, O. B., Gerstel, M. & Garman, E. F. (2013b). J. Appl. Cryst. 46, 1225–1230. Web of Science CrossRef CAS IUCr Journals Google Scholar
This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.