CCP4 study weekend
On symmetries of substructures
^{a}Lawrence Berkeley National Laboratory, One Cyclotron Road, BLDG 4R0230, Berkeley, California 947208235, USA
^{*}Correspondence email: rwgrossekunstleve@lbl.gov
This paper accompanies a lecture given at the 2003 CCP4 Study Weekend on experimental phasing. With the audience of the CCP4 Study Weekend in mind, an overview is given of symmetries of substructures and the implications for single
and single anomalous diffraction phasing procedures, as well as difference Fourier analyses. Pointers are also provided to practical tools for working with symmetries.Keywords: substructure symmetries.
1. Introduction
Experimental phasing divides the larger problem of determining a complete macromolecular structure into two steps. Firstly, a e.g. Drenth, 1999).
consisting of heavy atoms or anomalous scatterers is determined and refined. The refined is then used in algebraic or probabilistic phasing procedures to derive estimates of the phases for the full structure. These phases are in turn used to compute electrondensity maps for the purpose of density modification and model building (In this paper, we give an overview of e.g. in a multiple procedure.
symmetries. We distinguish two types, expected symmetry and unexpected symmetry. Expected symmetry encompasses alternative origin choices, hand ambiguity and indexing ambiguities. Expected symmetry has to be considered when substructures are compared or combined in some way,Unexpected symmetry refers to cases where the symmetry of the isolated
is higher than the crystal symmetry. For example, in many noncentrosymmetric space groups a singleatom is centrosymmetric. This may have an impact on single (SIR) or single anomalous diffraction (SAD) experiments, as well as on difference Fourier analyses. Phasing procedures and difference Fourier syntheses will yield maps that exhibit the higher symmetry of the rendering completion, density modification and model building more difficult. We introduce a simple diagnostic test that indicates unexpected symmetry.2. Expected symmetry
Expected symmetry is equivalent to or a ), which is also known as Cheshire symmetry (Hirshfeld, 1968). The concepts of allowed origin shifts or structureseminvariant vectors and moduli (e.g. Giacovazzo, 2001) are also intimately connected with Euclidean normalizers. The exact definition of Euclidean normalizers as given by, for example, Koch & Fischer (1983), is an advanced subject of group theory and a full account is beyond the scope of this paper. Here, we will approach Euclidean normalizers pragmatically by noticing that they are useful for answering the question `How many possibilities are there for transforming a given (sub)structure without changing the corresponding diffraction intensities?'
of the Euclidean of the crystal symmetry (Koch & Fischer, 1983We can distinguish three classes of transformations, corresponding to the three columns listed under `Additional Generators' in Table 15.3.2 of Hahn (1983).
2.1. Translations
A simple example is P1 (No. 1). The only symmetry is the periodicity of the lattice of unit cells. If a given is shifted arbitrarily in space, the complex structure factors change owing to phase shifts, but the intensities are invariant. Fig. 1 illustrates that this is not the case for (for example) P2 (No. 3). An atom placed at the site x, y, z implies another atom at −x, y, −z. If both atoms are shifted together in a general direction and the symmetry is applied again, the result is that we find four atoms in the The overall arrangement of atoms is invariant only for particular shifts (Fig. 1c). These are known as allowed origin shifts, which can alternatively be represented as structureseminvariant vectors and moduli (e.g. Giacovazzo, 2001).
2.2. Inversion through a center
In the absence of e.g. GrosseKunstleve & Adams, 2003a). In most space groups the inversion operation is located at the origin of the standard setting, but there are exceptions (e.g. I4_{1}22; No. 98). Applying the inversion operation is also known as `changing the hand' of a structure.
the inverse image of a given structure gives rise to the same diffraction intensities as the original structure. Somewhat counterintuitively, this is also true for substructures solved using anomalous differences, as these are approximations of the anomalous contributions to the only (2.3. Further generators
These generators describe the possibilities for reindexing a given data set. For some space groups, autoindexing programs may randomly choose between alternative indexing conventions (c.f. `Scenario 5: Reindexing' in the SCALEPACK Manual published by HKL Research Inc.; https://www.hklxray.com/hkl/manual.htm ). For example, in P4 a certain reflection could be indexed as (1, 2, 0) or alternatively (2, 1, 0). This corresponds to the generator y, x, z in Table 15.3.2 of Hahn (1983).
To compare two substructures that were derived from the same data set, it is sufficient to consider the allowed origin shifts and the inversion through a center as given by Table 15.3.2 of Hahn (1983). If it is not a given that the substructures relate to the same data set, the further generators must also be taken into account. This is performed automatically by the Euclidean modelmatching (Emma) module included in the Computational Crystallography Toolbox (GrosseKunstleve & Adams, 2003b). Similar programs are included in the ShakeandBake suite (Smith, 2002) and the SHELX suite (Dall'Antonia et al., 2003).
3. Unexpected symmetry
An electrondensity map obtained through SIR phasing is a superposition of the true electron density and the centrosymmetric counterpart of the true electron density convoluted with the Fourier transform of exp(2iφ_{sub}), where φ_{sub} are the phases of the heavyatom and i is the imaginary number. The Fourier coefficients of this map are given by (Ramachandran & Srinivasan, 1970)
where F represents complex structure factors and F* are the complex conjugates.
An electrondensity map obtained through SAD phasing is a superposition of the true electron density and the negative inverse of the true electron density convoluted with the Fourier transform of exp(2iφ_{sub}) (Ramachandran & Srinivasan, 1970),
The second terms of (1) and (2) are expected to only contribute noise to the general background in the SIR and SAD maps, respectively. However, the case when the has a centrosymmetric configuration in a noncentrosymmetric crystal is special. If the center of inversion of the is (without loss of generality) placed at the origin of the all phases φ_{sub} are either 0 or 180° and exp(2iφ_{sub}) = 1 for either value. Therefore, (1) and (2) reduce to F + F* and F − F*, respectively. The SIR or SAD map will therefore be the superposition of the true electron density with its exact inverse or exact negative inverse, respectively, and interpretation of the map can be significantly more difficult.
Often it is not immediately obvious that a
is centrosymmetric. However, the following algorithm provides a simple means to test for this condition.

Figs. 2, 3, 4 and 5 show selected results of the phaseophrenia algorithm. The sharp peak in Fig. 2 is generated by one or two atoms in any position in P1 or, for example, one atom at x_{1}, y_{1}, 0 and optionally another atom at x_{2}, y_{2}, ½ in P6. As a counterexample, Fig. 3 shows a plot generated by four randomly placed atoms in P3_{1}. The phaseophrenia algorithm can also be used to show that some maps will be more difficult to interpret than others even if the is not centrosymmetric. For example, the plot generated by a randomly placed atom in P3 (Fig. 4) is significantly sharper than a plot generated by a randomly placed atom in P3_{1} (Fig. 5). This reflects the higher symmetry of the singleatom in P3: the symmetry is actually , with a mirror plane passing through the atom.
It is worth noting that substructures with all sites in special positions may also lead to higher symmetries. A systematic treatment can be found in chapter 14 of Hahn (1983) under the title `Lattice Complexes'.
4. Implications for difference Fourier analyses
It is possible to solve small substructures by manual difference Fourier analyses. A certain number of initial sites (often only one) are used to compute phases for the full structure. These phases are combined with isomorphous or anomalous differences ΔF to compute a Fourier map that hopefully shows the missing sites,
If the φ has a symmetry higher than the crystal symmetry, the phases will reflect this higher symmetry. Difference Fourier maps in both the SIR and SAD case are likely to show spurious strong positive peaks. For example, if the is centrosymmetric, the map will show the and the inverse simultaneously. Therefore, it is important to pick only one peak from the difference Fourier map and to repeat the computation of phases with the additional site. If more than one site is picked from the same map they may not all be consistent with one choice of hand and the phasing procedure could fail. The best way to avoid this pitfall is to use automatic procedures for the solution of substructures (e.g. GrosseKunstleve & Adams, 2003a). In our experience, it is highly unlikely that a can be solved manually if all automatic programs available fail to produce the solution.
used to compute the phases5. Conclusions
We have presented a summary of how Euclidean Emma; https://cci.lbl.gov/cctbx/emma.html ) that is freely available as source code and through a web interface. Details of the Emma algorithm will be published elsewhere.
symmetry affects the comparison of substructures found in experimental phasing procedures. Based on this theory, we have implemented a Euclidean modelmatching algorithm (We have also shown how substructures with a symmetry higher than the crystal symmetry may affect the interpretability of SIR and SAD maps. Our simple diagnostic phaseophrenia algorithm is also freely available as source code and through an easytouse web interface. For substructures with a small number of sites (less than five), it can be informative to use the phaseophrenia web service. The general rule is that a SIR or SAD map will be easier to interpret if the phaseophrenia plot is relatively flat because the (negative) inverse of the electron density is smeared out more evenly according to (1) and (2). A sharp plot indicates that a map may be difficult to interpret even if the diffraction data are of high quality.
Acknowledgements
Our work was funded in part by the US Department of Energy under contract No. DEAC0376SF00098 and by NIH/NIGMS under grant No. 1P01GM063210.
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