The FUSION protein crystallization screen
The success and speed of atomic structure determination of biological macromolecules by X-ray crystallography depends critically on the availability of diffraction-quality crystals. However, the process of screening crystallization conditions often consumes large amounts of sample and time. An innovative protein crystallization screen formulation called FUSION has been developed to help with the production of useful crystals. The concept behind the formulation of FUSION was to combine the most efficient components from the three MORPHEUS screens into a single screen using a systematic approach. The resulting formulation integrates 96 unique combinations of crystallization additives. Most of these additives are small molecules and ions frequently found in crystal structures of the Protein Data Bank (PDB), where they bind proteins and complexes. The efficiency of FUSION is demonstrated by obtaining high yields of diffraction-quality crystals for seven different test proteins. In the process, two crystal forms not currently in the PDB for the proteins α-amylase and avidin were discovered.
HEPES-Na: 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid, sodium salt.
LiNaK: MORPHEUS mix of chemicals containing lithium sulfate, sodium sulfate and potassium sulfate.
(MRC) LMB: Medical Research Council Laboratory of Molecular Biology.
MES: 2-(N-morpholino)ethanesulfonic acid.
MOPS: 3-(N-morpholino)propanesulfonic acid.
NDSB: non-detergent sulfobetaine.
NPS: MORPHEUS mix of chemicals containing sodium nitrate, di-sodium hydrogen phosphate and ammonium sulfate.
PEG: polyethylene glycol.
PEG MME: polyethylene glycol monomethyl ether.
Progress in protein X-ray crystallography during the past decade has been mainly driven by instrument and software developments at synchrotrons, enabling high-throughput data collection and processing. In addition, femtosecond time-resolved serial crystallography with X-ray free-electron lasers (XFELs) now provides access to structural dynamics on femtosecond timescales (Nass et al., 2020). However, the initial yield of diffraction-quality crystals obtained with novel samples is rate limiting. The underlying problem is that each protein sample has specific characteristics. Notably, each protein has a different surface landscape, while every crystal structure is the result of a number of intermolecular interactions that need to occur using the available (although often deformable) surfaces. Most of these interactions are weak, water-mediated or hydrophobic interactions that can easily lead to irreversible aggregation. In fact, crystallization mostly occurs at high levels of saturation, where most samples tend to aggregate randomly rather than assembling into a highly ordered crystal (Chayen et al., 2010). Given the large number of parameters controlling protein crystallization, it is not currently possible to predict the right conditions to crystallize a novel sample. Instead, a multitude of variables associated with the experiment must be investigated empirically and often simultaneously (Dessau & Modis, 2011).
The reagents employed in a given crystallization screen can alter many of these variables. These reagents are categorized into three main groups of crystallization components, namely precipitants to reduce solubility, buffers to control pH and additives. Additives are employed for various reasons, for example to facilitate de novo structure determination by experimental phasing (McCoy & Read, 2010). Most reagents, however, have characteristics that have the potential to alter crystallization in several ways. For example, HEPES-like reagents are not only buffers; they can also alter protein stability, either by affecting the surfactant properties of the solution (Vasconcelos et al., 1996; Lin & Timasheff, 1996) or by binding to proteins directly (Newman, 2004). As a result, a positive impact of a reagent on macromolecular crystallization can rarely be explained rationally, even after the structure has been solved.
A systematic and complete factorial approach to crystallization screen formulation that combines the vast numbers of suitable reagents would contain billions of conditions (Abrahams & Newman, 2021). However, given the scarcity of most macromolecular samples, the number of conditions trialled must be radically reduced to a realistic level. Therefore, formulation strategies have been designed that cover a relatively large theoretical chemical space while minimizing the number of conditions. A number of screens have been published, and many also commercialized, that are typically made of 96 conditions, a format that is highly amenable to automation. A commonly employed strategy is the `incomplete factorial' sampling of components, where reagents and their combinations are omitted randomly (Carter & Carter, 1979; Rupp, 2003) or systematically (Gorrec et al., 2011). Another popular strategy is termed `sparse matrix', which integrates previously successful crystallization conditions that have been selected empirically against a number of samples (Jancarik & Kim, 1991), and can be optimized to avoid redundancies (Newman, 2004; Parker & Newstead, 2012; Gorrec, 2016).
An alternative strategy is to add mixes of crystallization additives in each condition to enlarge the sampled chemical space (McPherson & Cudney, 2006). Newman (2004) demonstrated that buffer molecules observed as ordered ligands in crystal structures deposited in the PDB could form useful mixes for crystallization screens. Later, an extensive search for small ligands that were found with relatively high numbers of occurrences in the PDB (molecular weight cut-off of 250 Da) was the basis for the original MORPHEUS screen formulation (Gorrec, 2009). To formulate MORPHEUS, 34 additive reagents were grouped into eight additive mixes according to their chemical nature to increase the coverage of the theoretical chemical space while minimizing cross reactions. In addition, their concentrations were maximized to take into account the expected low-affinity interactions with proteins (Danley, 2006). Some of the selected PDB-derived ligands were buffers, meaning they could be employed to form three buffer systems. Four highly efficient mixes of precipitants were optimized to provide cryoprotection upon flash freezing of the resulting crystals in liquid nitrogen, taking advantage of the fact that some precipitants are also cryoprotectants, such as glycerol and ethylene glycol (Tyree et al., 2018). Finally, the MORPHEUS formulation was simplified by combining the stock solutions of the three main screen components in fixed ratios for all conditions. The resulting sampling of the three main components formed a systematic 3D grid screen with 96 conditions.
Following the success of the original MORPHEUS screen, two derivative screens were designed in a similar way. MORPHEUS II integrated mixes of ligands that were less frequently found as small ligands in the PDB (Gorrec, 2015), a strategy based on the fact that the corresponding reagents were under-utilized for initial crystallization screening (Gorrec, 2013). For MORPHEUS III, the main criterion for selecting the crystallization additives was their drug-like properties, rather than their small size and the number of occurrences in the PDB (Gorrec & Zinzalla, 2018; Sammak et al., 2019).
Here, we present the latest implementation of the MORPHEUS formulation principles, named FUSION. FUSION essentially combines the most efficient components from the three MORPHEUS screens into a single 96-condition screen. For this, a systematic approach to formulate an incomplete factorial screen was taken. We tested FUSION with seven soluble proteins available commercially and obtained a large number of diffraction-quality crystals, demonstrating its efficiency. X-ray diffraction data collection on the largest crystals from the efficiency testing resulted in 12 unique crystal forms, including unreported crystal forms for the proteins α-amylase and avidin.
Of the 16 additive mixes from MORPHEUS (Gorrec, 2009) and MORPHEUS II (Gorrec, 2015), 14 were integrated into FUSION. To complement the pool of additive mixes, three mixes from the more recent MORPHEUS III screen (Gorrec & Zinzalla, 2018) and two new additive mixes were incorporated. The two new mixes are
(i) cryo-polyols prepared with the four cryoprotectants already used in MORPHEUS II and an additional polyol reagent (meso-erythritol);
(ii) NDSBs made of five non-detergent sulfobetaines (including NDSB 195 and NDSB 256 which were already used in MORPHEUS II).
As a result, the FUSION sampling of additives is made up of 19 different additive mixes (their preparation requires 81 unique reagents overall). The 19 additive mixes were split into two sets. Set 1 is composed of 12 mixes prepared mostly with reagents that could be categorized as salts (Table 1). The corresponding PDB ligands are monoatomic or simple polyatomic ions of mineral or organic nature, such as divalent metal cations, halides, carboxylic acids etc. (see Table S1 in the supporting information). Set 2 is mostly composed of small organic compounds with one or more hydroxyl groups as their main functional group (alcohols, polyols, monosaccharides and ethylene glycols) and also surfactants (cholic acid derivatives and NDSBs) (Table 2). The PDB ligands that gave rise to this other set of additives are listed in Table S2. The two different sets of additive mixes were combined systematically according to a sampling scheme (Fig. 1).
The 12 mixes forming set 1 were sampled horizontally across the 12 columns of the standard 96-well plate layout and labelled 1–12. The seven mixes from set 2 were sampled vertically across seven of the eight rows (i.e. rows A–G) and labelled a–g. The bottom row H is an exception where, instead, the concentration of each mix from set 1 was doubled.
Four precipitant mixes and three buffer systems from the original MORPHEUS screen (listed in Table 3) are used here to form the `backbone' of the FUSION formulation. However, the distribution of these two components is arranged differently across the 96-well plate layout in the FUSION screen, as shown in Fig. 2.
Before being mixed with the other components, the buffers were titrated to their required pH values (6.5, 7.5 and 8.5) using an IFSET solid-state pH probe (Gorrec, 2009). Each precipitant mix contains a precipitant that is also a cryoprotectant, namely polyethylene glycol monomethyl ether 500, ethylene glycol, glycerol or MPD. Their respective final concentrations in the screen (Table 4) are high enough to vitrify the resulting conditions in a cryo-loop during flash freezing in liquid nitrogen. Note that the small precipitants/cryoprotectants and the buffers employed here have frequently been reported as ordered ligands in crystal structures deposited in the PDB (Gorrec, 2009), namely ethylene glycol, glycerol and MPD (PDB residue identifiers EDO, GOL and MPD/MRD, respectively) and the buffers bicine, HEPES, imidazole, MES, MOPS and TRIS (PDB residue identifiers BCN, EPE, IMD, MES, MPO and TRS/TAM, respectively).
Conditions were prepared by combining the stock solutions according to the following ratios: 0.5 mix of precipitants + 0.1 mix of additives from set 1 + 0.1 mix of additives from set 2 + 0.1 titrated buffer system + 0.2 water. Deviating from this recipe, 15 conditions were prepared with only one additive mix and the ratios became 0.5 mix of precipitants + 0.2 mix of additives from set 1 or 2 + 0.1 titrated buffer system + 0.2 water. This doubles the concentration of a single additive mix in the final solutions in the 12 conditions H1–H12, as described earlier (Fig. 1). The same applies to the conditions B9, E9 and G9, where the mix `oxometallates' had to be removed as it was causing precipitation.
The incomplete factorial backbone formed with the precipitant mixes and titrated buffer systems (Fig. 2) was added first, in 96 test tubes, followed by water. The additive mixes from set 1 (Table 1) were then added to the tubes, and finally the additive mixes from set 2 (Table 2). Vortex mixing was applied after each addition. The stability of the conditions was assessed regularly over a three-month period by checking the turbidity and pH at 293 and 277 K. The pH of the conditions (IFSET solid-state pH probe) was tested in the tubes at 293 K and also after three months at 277 K. The final pH values of all conditions are listed in Table 4.
Seven proteins were employed to test the efficiency of the FUSION formulation as an initial screen. All were purchased from Sigma (Table S3). Five proteins were provided as lyophilized powders. After solubilization in water, the lyophilized proteins were left to hydrate for 24 h at 277 K. Insulin and catalase were used as provided (saline/aqueous solutions).
The screen preparation in the test tubes was aliquotted into MRC 96-well crystallization plates (SWISSCI), with the reservoirs containing 85 µl (Gorrec & Löwe, 2018). Vapour-diffusion sitting-drop experiments (Table 5) were prepared on a Mosquito nanolitre liquid handler (STP Labtech) at 293 K. Equal volumes of protein and reservoir solutions were dispensed (500 nl + 500 nl) with a final mixing step: the `advanced transfer options' on the controlling software were set as follows: four `mix cycles', 400 nl `mix volume', 0.5 mm `mix move'. Plates were immediately sealed with three-inch wide Crystal Clear sealing tape (Hampton Research), stored at 291 K and assessed regularly over three weeks using a Leica M205C stereomicroscope.
Crystals were screened for X-ray diffraction with an X-ray diffractometer system comprising an FR-E+ SuperBright rotating anode (Rigaku) and a MAR-DTB image-plate detector. Typically, two images were taken at 0 and 90°, with 1° rotation during 2–20 min exposures. Diffraction patterns were indexed using iMOSFLM (Battye et al., 2011; Powell, 2021). Diffraction data sets for relatively large crystals (100–500 µm) were collected on beamline I04 (Diamond, Harwell) at 100 K and processed with DIALS (Winter et al., 2018) (Table 6). The resulting structures were solved by molecular replacement with PHASER (McCoy et al., 2007). Interactive atomic model building was performed with COOT (Emsley et al., 2010), refinement with REFMAC5 (Mushudov et al., 1997) and PHENIX (Liebschner et al., 2019), and geometric model validation with MOLPROBITY (Chen et al., 2010).
The final formulation of the 96-condition FUSION screen is shown in Table 4. FUSION can simply be regarded as an evolution of the MORPHEUS formulation and sampling concept. One major difference is the number of additives in FUSION: there are 96 combinations of additives in FUSION, compared with eight in MORPHEUS. Another major difference is that an incomplete factorial approach to formulation was taken because a 3D grid screen against the four precipitant mixes and three buffer systems would have required 96 × 4 × 3 = 1152 conditions. To formulate an incomplete factorial screen with only 96 conditions, the components were sampled systematically, as shown in Figs. 1 and 2.
There were practical considerations driving the formulation work. First, although they contain a relatively large number of reagents, the conditions had to be stable, a problem accentuated by the final conditions being fairly saturated. Second, the formulation had to be highly efficient in producing diffracting crystals of a variety of test proteins. Third, the screen had to be practical and cost-efficient. According to this last consideration, the concept of fixed ratios of components was kept, while expensive additive mixes whose usefulness was questionable were excluded.
The MORPHEUS II mix `amino acids II' was not investigated because it has been cited only once (Wang et al., 2018) and is expensive to make. Similarly, some mixes from MORPHEUS III, namely `dipeptides', `nucleosides', `phytochemicals' and `antibiotics' were not often requested by our users at the LMB for optimization purposes. Although it is not entirely clear what the underlying reason for this was, they were not investigated to formulate FUSION.
Splitting the additive mixes into two different sets reduced the number of possible cross reactions, but some combinations of mixes were still prone to instability. The `lanthanides' mix from MORPHEUS II, despite producing some exclusive crystal hits (De Munck et al., 2021; Modenutti et al., 2021), had to be excluded during preliminary tests because it led to precipitation or flocculation when combined with other mixes.
The counterions from set 1 of additive mixes such as sodium, potassium and others (Table 1) can alter the physico-chemical properties of proteins in solution (Boström et al., 2011; Medda et al., 2012; Salis & Ninham, 2014; McPherson, 2001). Additionally, they can facilitate crystallization through the mediation of contact sites, especially with divalent metal cations (Camara-Artigas et al., 2016; Hegde et al., 2017). The additives from set 2 (Table 2) are more likely to alter protein–water interactions (Timasheff, 2002) than be part of the crystal structure. For example, some polyols and monosaccharides are well known for their stabilizing effects on proteins (Ajito et al., 2018).
In some cases, crystal structure determination reveals the additives as bound and ordered ligands and enables researchers to understand how the additives help to form or stabilize a crystal structure (De Yoreo & Vekilov, 2003). For example, the crystal structure of C-phycocyanin was mediated by tetracaine from the MORPHEUS III mix `anaesthetic alkaloids' (PDB code 6yqg, resolution 1.45 Å; Sarrou et al., 2021). However, this is not a very common scenario, and in many instances the positive impact of additives cannot be explained. For example, the heteromeric complex needed for the initiation of TRIM21 RING-anchored ubiquitin chain elongation crystallized in a MORPHEUS II condition formulated with 1,2,6-hexanetriol as cryoprotectant and the additive mix `LiNaK' (PDB code 7bbd, resolution 2.20 Å; Kiss et al., 2021), but no extra densities could be attributed to any of these molecules or atoms. In another example, a condition from MORPHEUS II integrating 1,5-pentanediol as cryoprotectant and the additive mix `polyamines' enabled the crystallization of the complex of RagA/C heterodimer that binds to mTORC1 (PDB codes 6s6a and 6s6d, resolution 2.50–2.63 Å; Anandapadamanaban et al., 2019). In both cases the electron-density maps did not reveal why the crystallization additives were essential.
Although the PDB ligands in the newly formulated mixes are not especially common in the PDB (Table S2), the two new additive mixes made of cryoprotecting polyols and NDSBs (Table 2) are potentially very useful. The cryo-polyol additives can tune the effects of the main cryoprotectants found in the precipitant mixes (Table 3). Cryoprotection parameters such as differential contraction between crystals and mother liquor (Alcorn & Juers, 2010) and cooling rates on vitrification (Berejnov et al., 2006) significantly affect the quality of the resulting X-ray diffraction data. Finally, non-detergent sulfobetaines are widely employed to solubilize proteins (Goldberg et al., 1996), which could be essential to obtain crystals from samples that precipitate readily in crystallization conditions.
Table 5 shows the number of experiments (i.e. sitting droplets) counted as crystallization hits during the crystallization efficiency tests with FUSION. Some droplets contained crystals large enough to be mounted directly for data collection. Other droplets were over-nucleated with many small crystals and would be a reasonable basis for optimization experiments (McPherson & Cudney, 2014; Jones et al., 2019). Salt crystals occurred rarely during the tests and then always in conditions containing the mixes `divalent cations I' and `anaesthetic alkaloids'.
Large single crystals (in duplicates where possible) were harvested from three different FUSION conditions for each test sample. Table 6 shows the 12 unique crystal forms found out of the 21 non-redundant crystals tested. The diffraction resolutions shown in Table 6 are comparable to those previously reported in the PDB for the same proteins. Importantly, different crystal forms were obtained for three proteins: catalase, concanavalin A and insulin. We found unreported crystal forms for α-amylase and avidin, which have been deposited in the PDB (PDB codes 7p4w and 7p4z, respectively).
None of the additives from the FUSION conditions could be located confidently in any of the electron-density maps obtained. There are a multitude of possible underlying reasons for this. Perhaps the resolution is too low to show small ordered additives, especially when the binding sites are unknown (Deller & Rupp, 2015). Or maybe the nature of the intermolecular contacts holding a protein crystal structure is too dynamic (Dimova & Devedjiev, 2018). In fact, the positive impact of FUSION additives on the yield and variety of crystals obtained was most likely acting elsewhere. Crystallization additives alter the water network surrounding a protein (Qiao et al., 2019) and can play transient and subtle roles in the early stages of crystal nucleation (Van Driessche et al., 2018). It should also be considered that additives tune the main experimental parameters such as surface tension, osmolarity and others (Tauchert et al., 2016). Finally, they can be useful indirectly. For example, detergent-like additives such as cholic acid derivatives (Table 2) are potentially beneficial to crystal growth by segregating impurities (McPherson et al., 1986).
The formulation and preparation of the FUSION screen has been presented. The efficiency of this new screen has been demonstrated by producing hits for test samples in multiple conditions and even crystal forms that had not been reported previously for the corresponding well known proteins. No electron densities for any of the additives from the FUSION conditions were observed in the resulting structures. However, on the basis of our past experience with novel screen formulations and their initial testing, we suggest that FUSION will probably produce useful hits for many other samples.
The supporting information contains the following additional tables:
Table S1. PDB-derived ligands from set 1 of FUSION mixes of additives (mixes 1–12).
Table S2. PDB-derived ligands from set 2 of FUSION mixes of additives (mixes a–g).
Table S3. Details of the seven commercially available test proteins.
Table S4. Crystallographic data summary table.
This work was supported by the Medical Research Council, as part of United Kingdom Research and Innovation. FUSION is sold by Molecular Dimensions Ltd (https://www.moleculardimensions.com) as `MORPHEUS FUSION' under an exclusive licence from the MRC and the medical research charity LifeArc (https://www.lifearc.org).
We thank Jan Löwe for critical reading of the manuscript, and Fusinita van den Ent, Olga Perisic, Paul Hart, Tom Pratt, Ben Sutcliffe and Jo Westmoreland (all MRC LMB), Rachel Kramer Green (RCSB PDB), François-Xavier Robert (LifeArc), and Claire Naylor, Simon Tanley and Claire Seddon (Molecular Dimensions) for technical support.
Abrahams, G. & Newman, J. (2021). Acta Cryst. D77, 1437–1450. Web of Science CrossRef IUCr Journals Google Scholar
Ajito, S., Iwase, H., Takata, S. & Hirai, M. (2018). J. Phys. Chem. B, 122, 8685–8697. Web of Science CrossRef CAS PubMed Google Scholar
Alcorn, T. & Juers, D. H. (2010). Acta Cryst. D66, 366–373. Web of Science CrossRef CAS IUCr Journals Google Scholar
Anandapadamanaban, M., Masson, G. R., Perisic, O., Berndt, A., Kaufman, J., Johnson, C. M., Santhanam, B., Rogala, K. B., Sabatini, D. M. & Williams, R. L. (2019). Science, 366, 203–210. Web of Science CrossRef CAS PubMed Google Scholar
Battye, T. G. G., Kontogiannis, L., Johnson, O., Powell, H. R. & Leslie, A. G. W. (2011). Acta Cryst. D67, 271–281. Web of Science CrossRef CAS IUCr Journals Google Scholar
Berejnov, V., Husseini, N. S., Alsaied, O. A. & Thorne, R. E. (2006). J. Appl. Cryst. 39, 244–251. Web of Science CrossRef CAS IUCr Journals Google Scholar
Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., Shindyalow, I. N. & Bourne, P. E. (2000). Nucleic Acids Res. 28, 235–242. Web of Science CrossRef PubMed CAS Google Scholar
Boström, M., Parsons, D. F., Salis, A., Ninham, B. W. & Monduzzi, M. (2011). Langmuir, 27, 9504–9511. Web of Science PubMed Google Scholar
Camara-Artigas, A., Plaza-Garrido, M., Martinez-Rodriguez, S. & Bacarizo, J. (2016). Acta Cryst. F72, 29–35. Web of Science CrossRef IUCr Journals Google Scholar
Carter, C. W. & Carter, C. W. (1979). J. Biol. Chem. 254, 12219–12223. CrossRef CAS PubMed Web of Science Google Scholar
Chayen, N. E., Helliwell, J. R. & Snell, E. H. (2010). Macromolecular Crystallization and Crystal Perfection, International Union of Crystallography Monographs on Crystallography, Vol. 24. Oxford University Press. Google Scholar
Chen, V. B., Arendall, W. B., Headd, J. J., Keedy, D. A., Immormino, R. M., Kapral, G. J., Murray, L. W., Richardson, J. S. & Richardson, D. C. (2010). Acta Cryst. D66, 12–21. Web of Science CrossRef CAS IUCr Journals Google Scholar
Danley, D. E. (2006). Acta Cryst. D62, 569–575. Web of Science CrossRef CAS IUCr Journals Google Scholar
Deller, M. C. & Rupp, B. (2015). J. Comput. Aided Mol. Des. 29, 817–836. Web of Science CrossRef CAS PubMed Google Scholar
De Munck, S., Provost, M., Kurikawa, M., Omori, I., Mukohyama, J., Felix, J., Bloch, Y., Abdel-Wahab, O., Bazan, J. F., Yoshimi, A. & Savvides, S. N. (2021). Nature, 600, 143–147. Web of Science CrossRef CAS PubMed Google Scholar
Dessau, M. A. & Modis, Y. (2011). J. Vis. Exp. 47, e2285. Google Scholar
De Yoreo, J. J. & Vekilov, P. (2003). Biomineralization, 54, 57–93. CrossRef CAS Google Scholar
Dimova, M. & Devedjiev, Y. D. (2018). IUCrJ, 5, 130–140. Web of Science CrossRef CAS PubMed IUCr Journals Google Scholar
Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. (2010). Acta Cryst. D66, 486–501. Web of Science CrossRef IUCr Journals Google Scholar
Goldberg, M. E., Expert-Bezançon, N., Vuillard, L. & Rabilloud, T. (1996). Fold. Des. 1, 21–27. CrossRef CAS PubMed Web of Science Google Scholar
Gorrec, F. (2009). J. Appl. Cryst. 42, 1035–1042. Web of Science CrossRef CAS IUCr Journals Google Scholar
Gorrec, F. (2013). J. Appl. Cryst. 46, 795–797. Web of Science CrossRef CAS IUCr Journals Google Scholar
Gorrec, F. (2015). Acta Cryst. F71, 831–837. Web of Science CrossRef IUCr Journals Google Scholar
Gorrec, F. (2016). Drug Discov. Today, 21, 819–825. Web of Science CrossRef CAS PubMed Google Scholar
Gorrec, F. & Löwe, J. (2018). J. Vis. Exp. 2018, 55790. Google Scholar
Gorrec, F., Palmer, C. M., Lebon, G. & Warne, T. (2011). Acta Cryst. D67, 463–470. Web of Science CrossRef CAS IUCr Journals Google Scholar
Gorrec, F. & Zinzalla, G. (2018). IUCr Newsletter, Vol. 26, Number 1. https://www.iucr.org/news/newsletter/volume-26/number-1/the-morpheus-iii-crystallization-screen-at-the-frontier-of-drug-discovery. Google Scholar
Hegde, R. P., Pavithra, G. C., Dey, D., Almo, S. C., Ramakumar, S. & Ramagopal, U. A. (2017). Protein Sci. 26, 1704–1713. Web of Science CrossRef CAS PubMed Google Scholar
Jancarik, J. & Kim, S.-H. (1991). J. Appl. Cryst. 24, 409–411. CrossRef CAS Web of Science IUCr Journals Google Scholar
Jones, H. G., Wrapp, D., Gilman, M. S. A., Battles, M. B., Wang, N., Sacerdote, S., Chuang, G.-Y., Kwong, P. D. & McLellan, J. S. (2019). Acta Cryst. F75, 123–131. Web of Science CrossRef IUCr Journals Google Scholar
Kiss, L., Clift, D., Renner, N., Neuhaus, D. & James, L. C. (2021). Nat. Commun. 12, 1220. Web of Science CrossRef PubMed Google Scholar
Liebschner, D., Afonine, P. V., Baker, M. L., Bunkóczi, G., Chen, V. B., Croll, T. I., Hintze, B., Hung, L.-W., Jain, S., McCoy, A. J., Moriarty, N. W., Oeffner, R. D., Poon, B. K., Prisant, M. G., Read, R. J., Richardson, J. S., Richardson, D. C., Sammito, M. D., Sobolev, O. V., Stockwell, D. H., Terwilliger, T. C., Urzhumtsev, A. G., Videau, L. L., Williams, C. J. & Adams, P. D. (2019). Acta Cryst. D75, 861–877. Web of Science CrossRef IUCr Journals Google Scholar
Lin, T. Y. & Timasheff, S. N. (1996). Protein Sci. 5, 372–381. 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. & Read, R. J. (2010). Acta Cryst. D66, 458–469. Web of Science CrossRef CAS IUCr Journals Google Scholar
McPherson, A. (2001). Protein Sci. 10, 418–422. Web of Science CrossRef PubMed CAS Google Scholar
McPherson, A. & Cudney, B. (2006). J. Struct. Biol. 156, 387–406. Web of Science CrossRef PubMed CAS Google Scholar
McPherson, A. & Cudney, B. (2014). Acta Cryst. F70, 1445–1467. Web of Science CrossRef IUCr Journals Google Scholar
McPherson, A., Koszelak, S., Axelrod, H., Day, J., Robinson, L., McGrath, M., Williams, R. & Cascio, D. (1986). J. Cryst. Growth, 76, 547–553. CrossRef CAS Web of Science Google Scholar
Medda, L., Salis, A. & Magner, E. (2012). Phys. Chem. Chem. Phys. 14, 2875–2883. Web of Science CrossRef CAS PubMed Google Scholar
Modenutti, C. P., Blanco Capurro, J. I., Ibba, R., Alonzi, D. S., Song, M. N., Vasiljević, S., Kumar, A., Chandran, A. V., Tax, G., Marti, L., Hill, J. C., Lia, A., Hensen, M., Waksman, T., Rushton, J., Rubichi, S., Santino, A., Martí, M. A., Zitzmann, N. & Roversi, P. (2021). Structure, 29, 357–370.e9. Web of Science CrossRef CAS PubMed 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
Nass, K., Gorel, A., Abdullah, M. M., Martin, A., Kloos, M., Marinelli, A., Aquila, A., Barends, T. R. M., Decker, F. J., Bruce Doak, R., Foucar, L., Hartmann, E., Hilpert, M., Hunter, M. S., Jurek, Z., Koglin, J. E., Kozlov, A., Lutman, A. A., Kovacs, G. N., Roome, C. M., Shoeman, R. L., Santra, R., Quiney, H. M., Ziaja, B., Boutet, S. & Schlichting, I. (2020). Nat. Commun. 11, 1814. Web of Science CrossRef PubMed Google Scholar
Newman, J. (2004). Acta Cryst. D60, 610–612. Web of Science CrossRef CAS IUCr Journals Google Scholar
Parker, J. L. & Newstead, S. (2012). Protein Sci. 21, 1358–1365. Web of Science CrossRef CAS PubMed Google Scholar
Powell, H. R. (2021). Biochemist, 43, 46–50. CrossRef Google Scholar
Qiao, B., Jiménez-Ángeles, F., Nguyen, D. & Olvera de la Cruz, M. (2019). Proc. Natl Acad. Sci. USA, 116, 19274–19281. Web of Science CrossRef CAS PubMed Google Scholar
Rupp, B. (2003). J. Struct. Biol. 142, 162–169. Web of Science CrossRef PubMed CAS Google Scholar
Salis, A. & Ninham, B. W. (2014). Chem. Soc. Rev. 43, 7358–7377. Web of Science CrossRef CAS PubMed Google Scholar
Sammak, S., Hamdani, N., Gorrec, F., Allen, M. D., Freund, M. V., Bycroft, M. & Zinzalla, G. (2019). Biochemistry, 58, 3144–3154. Web of Science CrossRef CAS PubMed Google Scholar
Sarrou, I., Feiler, C. G., Falke, S., Peard, N., Yefanov, O. & Chapman, H. (2021). Acta Cryst. D77, 224–236. Web of Science CrossRef IUCr Journals Google Scholar
Tauchert, M. J., Hémonnot, C., Neumann, P., Köster, S., Ficner, R. & Dickmanns, A. (2016). Acta Cryst. D72, 705–717. Web of Science CrossRef IUCr Journals Google Scholar
Timasheff, S. N. (2002). Proc. Natl Acad. Sci. USA, 99, 9721–9726. Web of Science CrossRef PubMed CAS Google Scholar
Tyree, T. J., Dan, R. & Thorne, R. E. (2018). Acta Cryst. D74, 471–479. Web of Science CrossRef IUCr Journals Google Scholar
Van Driessche, A. E. S., Van Gerven, N., Bomans, P. H. H., Joosten, R. R. M., Friedrich, H., Gil-Carton, D., Sommerdijk, N. A. J. M. & Sleutel, M. (2018). Nature, 556, 89–94. Web of Science CrossRef CAS PubMed Google Scholar
Vasconcelos, M. T., Azenha, M. A. & Lage, O. M. (1996). Anal. Biochem. 241, 248–253. CrossRef CAS PubMed Web of Science Google Scholar
Wang, L., Parnell, A., Williams, C., Bakar, N. A., Challand, M. R., van der Kamp, M. W., Simpson, T. J., Race, P. R., Crump, M. P. & Willis, C. L. (2018). Nat. Catal. 1, 968–976. Web of Science CrossRef CAS Google Scholar
Winter, G., Waterman, D. G., Parkhurst, J. M., Brewster, A. S., Gildea, R. J., Gerstel, M., Fuentes-Montero, L., Vollmar, M., Michels-Clark, T., Young, I. D., Sauter, N. K. & Evans, G. (2018). Acta Cryst. D74, 85–97. Web of Science CrossRef IUCr Journals Google Scholar
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