Protein hydration observed by X-ray diffraction. Solvation properties of penicillopepsin and neuraminidase crystal structures.

By Jiansheng Jiang, A. Brunger. 1994

Solvation in macromolecular crystal structures was studied by analyzing X-ray diffraction data of two proteins, penicillopepsin and neuraminidase. The quality of several solvent models was assessed by complete cross-validation in order to prevent overfitting the diffraction data. Radial solvent distribution functions were computed from electron density maps using phases obtained from multiple isomorphous replacement and from the protein's atomic model combined with the best solvent model. Distribution functions were computed around hydrophilic and hydrophobic groups on the protein's surface. Averaging of the distribution functions was performed in order to reduce the influence of noise. The first solvation shell is characterized by a peak in the average distribution functions. At 1.8 A resolution, polar groups show a sharp peak while non-polar groups show a broad one. The distinction between hydrophobic and hydrophilic solvation sites is lost when using lower resolution (2.8 A) diffraction data. Higher-order solvation shells are not observed in the average distribution functions. We hope that site-specific radial distribution functions obtained from high-quality diffraction data will produce a picture of macromolecular solvation consistent with available experimental data and computational results.

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Citations in the corpus

Towards automated crystallographic structure refinement with phenix.refine (2012, background): “D68, 352–367 Jiang & Brünger, 1994), s2 = htG*h, where G* is the reciprocalspace metric tensor, and Fmask are structure factors calculated from a solvent mask (a binary function with zero values in the protein region and non-zeros values in the solvent region).”
Considerations for the refinement of low-resolution crystal structures. (2006, unknown): “D62, 923–932 high resolution (Jiang & Brünger, 1994).”
New tools for the analysis and validation of cryo-EM maps and atomic models (2018, methodology): “CCmask only uses map values inside a mask calculated around the macromolecule as described by Jiang & Brunger (1994).”
Version 1.2 of the Crystallography and NMR system (2007, background): “For refinements at medium to high resolution (up to around 3 A resolution), R probe = R shrink = 1 is the optimum choic”
Checking your imagination: applications of the free R value. (1996, methodology): “Complete cross-validation [ 26 ] was used to compute sA (black bar) whereas averaging over individual error estimates for different test sets was used to compute Luzzati’s cross-validated error estimate (cross-hatched bar).”
Automatic multiple-zone rigid-body refinement with a large convergence radius (2009, unknown): “It has been shown that a bulk-solvent correction of the lowresolution data is very important to achieve optimal refinement results (Jiang & Brünger, 1994; Kostrewa, 1997; Badger, 1997).”
Metrics for comparison of crystallographic maps (2014, methodology): “…less than 0.18 and 0.22, respectively, showing that the structure factors Fmodel exp(i’model) calculated from the atomic model including the correction from the bulk solvent [Jiang & Brünger (1994), with the improvements described by Afonine et al. (2013)], reproduce the experimental data well.”
Bulk-solvent and overall scaling revisited: faster calculations, improved results (2013, methodology): “…modify (7) by adding the constant kanisotropic ¼ 1þ stV0sþ ðstV1sÞs2: ð9Þ The bulk-solvent scale factor is traditionally defined as kmask ¼ ksol expð Bsols2=4Þ; ð10Þ where ksol and Bsol are the flat bulk-solvent model parameters (Phillips, 1980; Jiang & Brünger, 1994; Fokine & Urzhumtsev, 2002b).”
Polder maps: improving OMIT maps by excluding bulk solvent (2017, background): “This model assumes a constant solvent density (typically 0.2–0.6 e Å 3) anywhere in the unit-cell volume that is not occupied by the current atomic model (Jiang & Brünger, 1994).”
Crystal structures (2004, unknown): “The second bulk-solvent model is derived similarly to that described by Jiang & Brünger (1994).”
Averaged kick maps: less noise, more signal…and probably less bias (2009, methodology): “…correction models have been developed in order to be able to include all reflections in the map calculation rather than applying a low-resolution truncation (Moews & Kretsinger, 1975; Phillips, 1980; Jiang & Brünger, 1994; Tronrud, 1997; Badger, 1997; Urzhumtsev, 2000; Fokine & Urzhumtsev, 2002).”