Validation tools: can they indicate the information content of macromolecular crystal structures?

Dodson, E.J.; Davies, G.J.; Lamzin, Victor S.; Murshudov, GN; Wilson, K. S.

doi:10.1016/s0969-2126(98)00070-7

Cited by 15 publications

(8 citation statements)

References 21 publications

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“…Engh & Huber (1991) provided a dictionary of target distances and their standard deviations for CÐC, CÐO and CÐN distances and angles, but the inclusion of metal±ligand geometrical information at that stage was not practicable. A third area of possible usefulness is in the validation of protein structures, a project which has been undertaken by the EU Validation Network (EU Validation Network, 1998;Dodson et al, 1998). Validation of any particular structure determination should include checking of the reported geometry against accepted means and ranges for each type of bond, angle etc.…”

Section: Introductionmentioning

confidence: 99%

The geometry of metal–ligand interactions relevant to proteins

Harding

1999

Acta Crystallogr D Biol Crystallogr

232

209

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Geometrical data which could be of relevance in the structure determination, structure re®nement, assessment or understanding of metalloproteins have been extracted from the Cambridge Structural Database (CSD). The CSD contains crystallographic data from`small-molecule' structures determined by X-ray or neutron diffraction to an accuracy much better than that of most current protein structure determinations. The structures selected have a crystallographic R factor 0.065 and contain Ca, Mg, Mn, Fe, Cu or Zn interacting with ligands which are analogues of the amino-acid side chains commonly found in proteins; they include carboxylate groups, alcohols, phenolates, thiolates, imidazole groups and also water molecules. For each pair, the mean metal±donor-atom distance, the sample standard deviation and the range of observed values are tabulated, using $4500 observations in all. Where practicable, subsets with different coordination numbers and/or oxidation states are given. Also included are inter-bond angles at the ligand donor atom, the orientation of carboxylate and imidazole groups with respect to the metal± donor-atom bond and some other aspects of ligand geometry. Thus, for example, target distances and their standard deviations could be easily looked up for the validation of a metalloprotein structure or for use in restrained re®nement with low-resolution data.

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Section: Introductionmentioning

confidence: 99%

The geometry of metal–ligand interactions relevant to proteins

Harding

1999

Acta Crystallogr D Biol Crystallogr

232

209

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“…An analysis of 13 atomicresolution structures shows a broad distribution. 4 In this article, we will present a detailed analysis of 22 atomicresolution protein structures with an examination of the -angle distribution dependence on secondary structure. The increased rigidity of the peptide bond due to hydrogen bonding is also demonstrated by the shortening of the C-N bond and lengthening of the Cv0 bond in hydrogen-bonded crystals of amide molecules compared to isolated electronic structure calculations.…”

Section: Introductionmentioning

confidence: 99%

The nonplanarity of the peptide group: Molecular dynamics simulations with a polarizable two-state model for the peptide bond

Rick

Cachau

2000

The Journal of Chemical Physics

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The general properties of the peptide bond can be described from a linear combination of two states: a single bond neutral form and a double bond zwitterionic form. However, environmental effects can shift the balance of the linear combination. This would cause the rigidity of torsional rotations of the peptide bond to be environmentally dependent and, in fact, an analysis of protein structures in the protein data bank reveals a different degree of nonplanarity for different secondary structure elements. A potential is presented in which the peptide bond is treated as a linear combination of two states; the coefficients of the two states are updated as the simulation progresses using an extended Lagrangian formalism. The model is applied to the helix/coil transition of polyalanine. Fluctuations in the planarity of the peptide dihedral angle are found to increase the rate constant for the coil to helix transition by a factor of two.

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“…The Protein Data Bank (http://www.rcsb.org/pdb/) provides submission tools for model validation and is an outstanding example of a common format for model coordinates. A number of issues remain to be resolved, especially regarding the validation targets 37,38 .…”

Section: Validationmentioning

confidence: 99%