PICKScreens, A New Database for the Comparison of Crystallization

Dec 31, 2010 - Published as part of the Crystal Growth & Design virtual special issue on the ... PICKScreens, a database reporting Profile of Identiti...
1 downloads 3 Views 2MB Size
DOI: 10.1021/cg101267n

Published as part of the Crystal Growth & Design virtual special issue on the 13th International Conference on the Crystallization of Biological Macromolecules (ICCBM13).

2011, Vol. 11 488–491

PICKScreens, A New Database for the Comparison of Crystallization Screens for Biological Macromolecules Tanja Hedderich, Marco Marcia,# J€ urgen K€ opke, and Hartmut Michel* Department of Molecular Membrane Biology, Max Planck Institute of Biophysics, Max von Laue Strasse 3, D-60438 Frankfurt am Main, Germany. #Current address: Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA. Received September 27, 2010; Revised Manuscript Received November 29, 2010

ABSTRACT: Extensive screening during crystallization trials is necessary, especially for challenging but interesting targets, that is, large multisubunit complexes or membrane proteins. Producing high amounts of such macromolecules is difficult, so it is important to perform screening efficiently. However, commercial screens are redundant, leading to unnecessary or unwanted sample consumption, and cannot be visually compared, because the manufacturers’ formulations are not formatted uniformly. PICKScreens, a database reporting Profile of Identities among Crystallization Kit Screens, will help crystallographers “pick” screens in a more rational manner, minimizing sample consumption and hopefully enhancing their success rate. It is available at https://registration.cc.biophys.mpg.de/fam-core/.

1. Introduction X-ray crystallography is the method of choice to study the structures of biological macromolecules, and to date more than 85% of the structures deposited on the Protein Data Bank (PDB) have been obtained with this technique. In order to produce three-dimensional crystals suitable for X-ray diffraction and structure solution, extensive screening is often necessary, and a wide range of screens is now available on the market offering a rich choice to crystallographers. Moreover, advanced high-throughput platforms allow the automatized setup of crystallization trials in nanoliter scale.1 However, the production of high amounts of a pure, homogeneous and stable form of the desired targets is often a limitation, especially when dealing with challenging samples, such as large multisubunit complexes or membrane proteins.2,3 Consequently, there is a need to rationalize the choice of the crystallization screens, in order to minimize target consumption. In particular, it is certainly desirable to sample a wide, well-distributed range of the crystallization space in initial trials. Nonetheless, it is a matter of fact that the commercial crystallization screens are redundant,4 and identical solutions are present among screens often unbeknownst to the experimenters, because the formulations listed by the manufacturers follow very different formats (Figure 1). This lack of homogeneity hampers an easy visual comparison of the screen formulations and may lead to unnecessary or unwanted repetitions in the crystallization experiment. In this article, we describe PICKScreens, a database that reports the Profile of Identities among Crystallization Kit *Corresponding author. E-mail: Hartmut.Michel@mpibp-frankfurt. mpg.de. Telephone: 0049-(0)69-63031000. Fax: 0049-(0)69-63031002. pubs.acs.org/crystal

Published on Web 12/31/2010

Screens and which is therefore suited to help researchers plan their crystallization trials with more awareness and hopefully with higher success rates. 2. Experimental Section The formulations of 87 commercially available screens were downloaded from their producers’ web pages and formatted according to the following guidelines. They are Microsoft Office Excel worksheets composed of five columns, titled “Buffer”, “Salt 1”, “Salt 2”, “Precipitant 1”, and “Precipitant 2”, respectively. Since virtually all crystallization solutions are composed of a buffering agent, one or two salts, and/or one or two other precipitating agents, the chosen formatting scheme was sufficient to represent all considered crystallization screens. In a few (2.5%) solutions, more than five components were present and were therefore listed in alphabetical order in the “Salt 2” or the “Precipitant 2” columns, which only in such cases exceptionally contained more than one chemical compound in the same table cell. The chemical names, concentrations, and pH values of each compound were also formatted uniformly, as exemplified in Figure 1. A comprehensive table containing all compounds and their precise name as used by our database is reported at https://registration. cc.biophys.mpg.de/fam-core/. Any screen formatted in the described way can be used in PICKScreens, independently of the number of solutions that compose it. The formatted screens can then be imported into and compared by the database PICKScreens. PICKScreens is based on Microsoft Office Access and works therefore on Windows platforms. It performs a single-click query, whereby the screens are compared solution by solution, each one corresponding to a single line in the input formulation tables. The components listed in the columns “Salt 1” and “Salt 2” are considered equivalent, and so do those listed in the columns “Precipitant 1” and “Precipitant 2”. The outputs of the query are a cross-table showing the number of identical solutions for each pair of the imported screens, and the list of such identical solutions. Screens that are unique, not showing any pairwise identities with any other screen, are not reported in the output table. r 2010 American Chemical Society

Article

Crystal Growth & Design, Vol. 11, No. 2, 2011

489

Figure 1. Identical solutions are present across crystallization screens. Here, seven conditions are listed (lines A-G) in the format provided online by different manufacturers (A = HR Cryo 46; B = EB Wizard III 35; C = MDL JCSGþ E11; D = Q JCSG 53; E = Q JCSGþ 59; F = SA Cryo 46; G = Q Cryos 67). The formulations appear very different from one another. However, after formatting them uniformly according to the standards adopted in PICKScreens, it becomes evident that they are all identical and all correspond to the formulation listed in the bottom line.

3. Results We have formatted and analyzed all commonly used commercial screens for macromolecular crystallization, counting 87 screens (7230 solutions) provided by six companies [Qiagen (Q), Emerald Biosystems (EB), Sigma Aldrich (SA), Jena Bioscience (JB), Hampton Research (HR) and Molecular Dimensions Limited (MDL)]. The following observations can be made. First, 10 screens are absolutely unique (“SA RNA”, “SA Low Ionic Strength”, “EB Ozma 8 and 10”, “EB Precipitant Synergy Expanded 33”, “EB Precipitant Synergy Expanded 67”, “HR Nucleic Acid Mini”, “HR PEG/Ion HT” “JB Pentaerythritol”, “MDL

Morpheus” and “MDL PGA”). Second, although the majority of the screens show less than 10% pairwise identities, other screens share a very high number of identical solutions. In particular, 19 pairs of screens in 96-well format possess more than 70% identities, 11 pairs more than 80% identities, and 5 pairs more than 90% identities (the latter pairs are “HR Crystal Screen HT” and “Q Classics Suite”, “HR Crystal Screen HT” and “SA Automated”, “HR Crystal Screen HT” and “MDL Structure Screen 1-2 HT”, “Q MbClass II Suite” and “MDL MemStart&MemSys”, and “Q Protein Complex Suite” and “MDL ProPlex HT”). Finally, an interesting example is the analysis of overlaps in the subset of screens

490

Crystal Growth & Design, Vol. 11, No. 2, 2011

Hedderich et al.

Table 1. Cross-Table Obtained by PICKScreens Showing the Comparison of Screens Dedicated to Membrane Protein Crystallizationa

a The numbers in the table cells indicate the number of pairwise identities between the corresponding screens. NB: “Q Cubic Phase II” is not listed because it is unique and does not show any identity with any of the other screens.

dedicated to the crystallization of membrane proteins, a class of macromolecules difficult and expensive to produce in crystallizable form5 and for which therefore well-planned crystallization is particularly desirable. Only 1 of the 11 membrane protein crystallization screens is absolutely unique (“Q Cubic Phase Screen II”), while the pair “MDL MemStart&MemSys” and “Q MbClass II Suite” shows the highest redundancy with as much as 93 out of 96 identical solutions (Table 1). 4. Discussion The PICKScreens database allows the easy visualization of identical solutions in crystallization screens. It is a simple, three-step tool, which consists of (i) importing the desired uniformly formatted screens, (ii) starting a single-click query, and (iii) reading the output tables (Figure 2). Therefore, it supports an efficient and quick planning of crystallization experiments for two main reasons. On one hand, it helps avoid unwanted redundancy in initial crystallization trials, enhancing the probability of obtaining crystals even if the sample amount is limited. On the other hand, it allows recognizing nominally identical solutions produced by different manufacturers, which may also be worth testing if high amounts of sample are available, because they may influence the crystallization process differently, despite being apparently repetitive.4 Additionally, the PICKScreens database also offers other advantages. First, it can perform single- and multiple-compound searches across all imported screens, thereby allowing the quick identification of similar but not identical solutions. Such search helps evaluate the reproducibility of crystallization results and plan the design of optimization screens for promising hits, because it enables one to respectively choose or avoid favorable or unfavorable crystallization agents. Second,

Figure 2. PICKScreens reports Profiles of Identities among Crystallization Kit Screens in three easy steps. Desired crystallization screens are (1) imported into the database and (2) compared through one single-click query. The results can be readily visualized and exported as Microsoft Excel Worksheets or PDF Documents (3). The figure specifically shows the search for duplicates of HR Cryo condition 46 across all of the 87 commercial crystallization screens analyzed in our report (see Figure 1).

Article

the database can also be used to assess whether new screens coming on the market or being developed individually in the laboratory are unique or redundant. Toward this purpose, PICKScreens is available for download at the URL https:// registration.cc.biophys.mpg.de/fam-core/ and will be updated when new crystallization screens are available on the market. In conclusion, we hope that PICKScreens can serve as a valuable tool to rationalize the choice of crystallization screens, minimize sample consumption, and maximize the success rate of crystallization trials. Acknowledgment. We thank Georg Klepp for his thorough support in developing the PICKScreens database and Paolo Lastrico for help in preparing the figures. The work has been supported by the Deutsche Forschungsgemeinschaft (SFB 472), the Fonds der Chemischen Industrie, the Max Planck Gesellschaft, the Cluster of Excellence “Macromolecular Complexes”, Frankfurt am Main, Germany, by the ESFRI INSTRUCT program of the European Union and the BMBF (Core Center G), and the International Max Planck Research School on Structure and Function of Biological Membranes, Frankfurt am Main, Germany.

Crystal Growth & Design, Vol. 11, No. 2, 2011

491

Abbreviations PICKScreens Profile of Identities among Crystallization Kit Screens PDB Protein Data Bank 3-D three-dimensional HT high throughput Q Qiagen EB Emerald Biosystems SA Sigma Aldrich HR Hampton Research JB Jena Bioscience MDL Molecular Dimensions Limited

References (1) Kambach, C. Curr. Protein Pept. Sci. 2007, 8, 205–217. (2) Michel, H. International Tables for Crystallography 2006, F, 94–99. (3) Auerbach-Nevo, T.; Zarivach, R.; Peretz, M.; Yonath, A. Acta Crystallogr. D Biol. Crystallogr. 2005, 61, 713–719. (4) Wooh, J. W.; Kidd, R. D.; Martin, J. L.; Kobe, B. Acta Crystallogr. D Biol. Crystallogr. 2003, 59, 769–772. (5) Newby, Z. E.; O’Connell, J. D., 3rd; Gruswitz, F.; Hays, F. A.; Harries, W. E.; Harwood, I. M.; Ho, J. D.; Lee, J. K.; Savage, D. F.; Miercke, L. J.; Stroud, R. M. Nat. Protoc. 2009, 4, 619–637.