Tables for
Volume F
Crystallography of biological macromolecules
Edited by E. Arnold, D. M. Himmel and M. G. Rossmann

International Tables for Crystallography (2012). Vol. F, ch. 4.3, pp. 135-136   | 1 | 2 |

Section 4.3.11. Conclusions

Z. S. Derewendaa*

aDepartment of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, VA 22908–0736, USA
Correspondence e-mail:

4.3.11. Conclusions

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Protein engineering has become a routine tool that is used to generate crystallizable macromolecules and their complexes. While some approaches may only apply to very specific targets, a number of strategies offer general applicability. Among these, gene-construct optimization or surface-entropy reduction are quickly gaining popularity as methods of choice. However, it should be stressed that none of the methods described here offer a guarantee that the target protein can be coerced to crystallize. To maximize the chances of success, one must frequently attack the problem on multiple fronts based on an understanding of the chemical and physical properties of a specific protein. This is particularly true of technically difficult targets such as membrane proteins. A classic example illustrating this principle is the study of the HIV gp120 envelope glycoprotein (Kwong et al., 1998[link], 1999[link]). The con­struct that was ultimately used in successful crystallization screens had deletions of 52 and 19 residues from the N- and C-­termini and two flexible loops replaced by Gly-Ala-Gly linkages; additionally, the protein was 90% deglycosylated compared with the wild type. Moreover, this engineered gp120 was only crystallized in the form of a ternary complex with the CD4 receptor and an Fab fragment from a neutralizing antibody. In the recent case of the ATP-gated P2X4 ion channel, a crystallizable variant was obtained after a series of N- and C-­terminal deletions were screened to identify the smallest functional unit and the introduction of three mutations (C51F/N78K/N187R) to eliminate both aggregation arising from oxidation and N-glycosylation (Kawate et al., 2009[link]).

The rapidly expanding database of macromolecular structures greatly enhances our understanding of the physical chemistry of proteins, ultimately enhancing our ability to predict the behaviour of a protein in solution from its sequence. It is therefore increasingly possible to rely on such theoretical predictions in lieu of tedious experimental screens. A number of online tools have been developed for this purpose. The propensity of a protein target to crystallize can be evaluated using the XtalPred server ( ), which offers insights into potential sources of problems arising from sequence features (Slabinski et al., 2007[link]). Automated design of optimally truncated con­structs for structural analysis has been made possible by the ProteinCCD meta-server ( ), which uses the cDNA sequence of the target (Mooij et al., 2009[link]). This server collects information about secondary structure, disorder, putative coiled coils, transmembrane segments, domains and domain linkers, and suggests constructs so that the user can interactively choose suitable options and obtain sequences of oligonucleotides needed for appropriate PCR amplification (Mooij et al., 2009[link]). For proteins recalcitrant to crystallization in their wild-type form, surface mutations enhancing crystallizability can be designed using the surface-entropy reduction server ( ; Goldschmidt et al., 2007[link]).

As the focus of macromolecular crystallography shifts from the principles of protein architecture to increasingly complex biological questions, the approach to crystallization is also undergoing dramatic evolution. As we gain better understanding of the microscopic nature of protein crystallization, we will be able to develop rational protein-engineering strategies that systematically and significantly improve the success rate of crystallization.


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