Evaluation of models determined by neutron diffraction and proposed improvements to their validation and deposition
aMolecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA, bDepartment of Physics and International Centre for Quantum and Molecular Structures, Shanghai University, Shanghai 200444, People's Republic of China, cNeutron Science Directorate, Oak Ridge National Laboratory, PO Box 2008, Oak Ridge, TN 37831, USA, and dDepartment of Bioengineering, University of California, Berkeley, CA 94720, USA
*Correspondence e-mail: email@example.com
The Protein Data Bank (PDB) contains a growing number of models that have been determined using neutron diffraction or a hybrid method that combines X-ray and neutron diffraction. The advantage of neutron diffraction experiments is that the positions of all atoms can be determined, including H atoms, which are hardly detectable by X-ray diffraction. This allows the determination of protonation states and the assignment of H atoms to water molecules. Because neutrons are scattered differently by hydrogen and its isotope deuterium, neutron diffraction in combination with H/D exchange can provide information on accessibility, dynamics and chemical lability. In this study, the deposited data, models and model-to-data fit for all PDB entries that used neutron diffraction as the source of experimental data have been analysed. In many cases, the reported Rwork and Rfree values were not reproducible. In such cases, the model and data files were analysed to identify the reasons for this mismatch. The issues responsible for the discrepancies are summarized and explained. The analysis unveiled limitations to the annotation, deposition and validation of models and data, and a lack of community-wide accepted standards for the description of neutron models and data, as well as deficiencies in current model refinement tools. Most of the issues identified concern the handling of H atoms. Since the primary use of neutron macromolecular crystallography is to locate and directly visualize H atoms, it is important to address these issues, so that the deposited neutron models allow the retrieval of the maximum amount of information with the smallest effort of manual intervention. A path forward to improving the annotation, validation and deposition of neutron models and hybrid X-ray and neutron models is suggested.
Keywords: model validation; neutron crystallography; PDB data mining; H/D exchange; Phenix.
The predominant method to determine the three-dimensional structure of macromolecules is X-ray crystallography (Fig. 1), which is based on the interaction between X-rays and the electrons of the atoms constituting the crystal. Neutron diffraction is a complementary technique that relies on the interaction of neutrons with atomic nuclei. The neutron scattering cross-section, which determines the probability of a neutron being scattered by a nucleus, varies by element (or isotope) in a nonlinear fashion, as opposed to X-rays, where the scattering increases with the number of electrons. This is why neutron diffraction complements X-ray diffraction by enabling the location of very light atoms or ions such as hydrogen or protons in protein structures. As the knowledge of H-atom positions is important for determining the protonation states and reaction pathways of proteins (Engler et al., 2003; Weber et al., 2013; Haupt et al., 2014; Casadei et al., 2014; Howard et al., 2016), neutron diffraction is able to provide valuable information for the understanding of catalytic mechanisms and ligand binding (Yamaguchi et al., 2009; Bryan et al., 2013; Knihtila et al., 2015).
However, neutron diffraction may be challenging in practice for the following reasons.
When computational tools are developed, it is desirable to exercise the new algorithms using all available data and models (see, for example, Afonine et al., 2009; Weichenberger et al., 2015). This ensures that the new developments work not only on the developer's favourite examples but are also robust enough to work generally, which is the key for automated software development. New tools for joint XN refinement are being developed in the framework of the PHENIX software suite (Adams et al., 2010). To test the algorithms, all neutron models and diffraction data available as of 8 September 2017 in the Protein Data Bank (PDB; Berman et al., 1977, 2000) were analyzed. An approach for the early detection of issues that could cause problems is to use the deposited data and model to calculate Rwork and Rfree, and compare the obtained values with the published values. A mismatch may be indicative of various issues, ranging from trivial typos to incomplete or incorrect annotations in the deposited data. We find a surprising number of models that show large differences (reaching up to 30%) between the reported and recomputed R factors. These models and data were inspected in order to determine the origin of the differences. This study summarizes the lessons learned from the data-mining effort.
2. Materials and methods
2.1. Collecting the data from the PDB
All computations were performed with PHENIX tools (Adams et al., 2010). Models determined by neutron diffraction were identified using the `experimental method' search option on the PDB website. The model PDB and data files were obtained with the phenix.fetch_pdb tool. Information relevant to recomputing R factors using the same conditions as were used for refinement of the final structure by the depositors were automatically extracted from the PDB file header: minimum and maximum resolution limits and σ cutoff as well as the twin law, if present. Furthermore, crystallographic R factors (Rwork and Rfree), the deposition year and the program used for refinement were obtained from the PDB file header.
2.2. Diffraction data labels for joint XN data sets
In the case of models determined by joint XN refinement, the corresponding data file should contain at least two data arrays: one for the neutron data and one for the X-ray data. It is therefore important to know which data array corresponds to which experiment. In the data CIF file the item _diffrn.details can be used to describe the details of the diffraction measurement, such as `first data set reflections X-ray diffraction' and `second data set reflections neutron diffraction'. We note that annotations could not be parsed automatically. The keyword or sentence was not consistently the same and in several instances only one data array had an annotation while the other did not. However, a practical way to determine which data array corresponds to which experiment is to compute Rwork using X-ray and neutron scattering factors for both data arrays; the wrong set of scattering factors leads to higher R factors.
2.3. Model files
2.3.1. Assessment of hydrogenation state
We define the hydrogenation state as a model feature describing how the experimentalists chose to model H-atom sites (using H, D or H and D). The presence of H and D atoms in the PDB file was used to sort models into four different categories.
Case (i) is worthy of further consideration. Even if a protein is expressed from organisms cultured in deuterated reagents and crystallization is performed in deuterated solutions, there is a chance that the sample will have been exposed to ambient hydrogenated moisture at some stage. It is therefore unlikely that all H atoms (100%) are replaced by D atoms (an all-D refinement protocol might nevertheless be chosen, for example to increase the data-to-parameter ratio). Also, it may happen that some D atoms back-exchange to hydrogen if hydrogenated reagents are used in one of the protein crystal-production steps (such as purification; Haupt et al., 2014; Yee et al., 2017). Some models therefore contain a majority of D atoms and very few H atoms. To prevent the misinterpretation of such a model as containing both H and D, which means that H atoms are at all exchangeable sites, a cutoff was applied. If more than 90% of atoms are of one type (H or D) this type is assigned. We chose 90% because it represents a compromise between a strict separation of perdeuterated versus hydrogenated and the experimental reality that even perdeuterated crystals can contain some H atoms.
Furthermore, for each model we determined the total number of H or D atoms and the number of H atoms, D atoms and exchanged sites in protein (or RNA/DNA) residues. Here, an exchanged site is not counted twice as belonging to the H and D atoms as well; for example, an H atom is either H, D or exchanged. A site was identified as being exchanged if both H and D were used to model it. The number of H or D atoms in other molecular species was also determined, including water molecules and ligands. Finally, the percentage of H/D-exchange sites per protein H and D atom was analysed.
2.3.2. Properties of H and/or D atoms
In addition to counting H and D atoms (§2.3.1), we also looked at (i) models containing H or D atoms with occupancies smaller than zero; (ii) models with incomplete XH3 groups (`propeller groups'), i.e. if one H or D atom was missing; (iii) the use of standard X—H and X—D bond-length constraints; and (iv) the coordinates and atomic displacement parameters (ADPs) of corresponding H and D atoms in exchanged sites.
2.3.3. Generation of H and/or D atoms
If the deposited model did not contain H or D atoms according to the published information, they were generated using phenix.ready_set. If both H and D atoms were added at exchangeable sites, the occupancy ratio was set to 50:50. These curated models were used to test hypotheses about particular issues. The reported values in Tables 1, 2 and 3 are based on original models (unless curation was necessary to be able to process the file; for example, a few models contained corrupt atom names).
2.4. Model-to-data fit: computation of R factors
To assess the model-to-data fit, Rwork and Rfree were computed using resolutions and σ cutoffs as reported in the PDB header or the literature. X-ray (Maslen et al., 1992; Waasmaier & Kirfel, 1995; Grosse-Kunstleve et al., 2004) and neutron (Sears, 1992) scattering tables were used as appropriate.
3. Results and discussion
3.1. Overview of neutron models deposited to date
As of 8 September 2017, the number of neutron diffraction models deposited in the PDB was 122. Fig. 3 shows the cumulative number of neutron models per year. The first model in the database was determined in 1984 and corresponds to the structure of a bovine pancreatic trypsin inhibitor determined by joint XN refinement (PDB entry 5PTi; Wlodawer et al., 1984). However, several structural reports predate the establishment of the PDB, such as a model of myoglobin (Schoenborn, 1969), or were not deposited in the PDB, such as a model of crambin (Teeter & Kossiakoff, 1984).
It can be noted that no models were deposited between 1990 and 1998 owing to the unavailability of macromolecular neutron crystallography facilities in the early 1990s. The reactors at the Institut Laue–Langevin (ILL) in Grenoble and the High Flux Beam Reactor (HFBR) at Brookhaven were unavailable from 1990 to 1995 and from 1989 to 1991, respectively (Chen & Unkefer, 2017). Also, some neutron structures were not deposited in the PDB, such as a model of concanavalin A (Habash et al., 1997). Several factors have changed this situation and have recently increased the rate of model deposition. New and advanced neutron sources have begun operation, including the SNS in the USA, the FRM-2 reactor in Germany and J-PARC in Japan. Additional macromolecular neutron crystallography beamlines have been built, including LADI (Cipriani et al., 1997) in France; PCS (Langan et al., 2004), MaNDi (Coates et al., 2015) and IMAGINE (Meilleur et al., 2013) in the USA; BioDiff (Ostermann & Schrader, 2015) in Germany; and iBIX (Kurihara, Tanaka, Muslih et al., 2004) in Japan. New methods and technologies have been developed, such as the development of the neutron image-plate detector (Niimura et al., 1994) and the development of new types of macromolecular neutron crystallography beamlines based on the use of powerful time-of-flight techniques at spallation sources (Langan et al., 2004). The rate of structure deposition will increase further with several next-generation advanced neutron sources that are under construction or commissioning, including the ESS in Sweden (https://europeanspallationsource.se) and the CSNS in China (https://english.ihep.cas.cn/csns/).
The total number of deposited structures has grown since the 1980s, but the number of depositions per year is low compared with X-ray crystallography and has varied between three and 22 during the past decade. Among the 122 deposited structures, 55 were determined using neutron data alone (coral in Fig. 3) and 67 were obtained from joint XN refinement (blue in Fig. 3). Most of the recently deposited structures were refined using the joint XN refinement method. The development of robust refinement algorithms for joint XN refinement has enabled the increased use of macromolecular neutron crystallography and has provided more complete (including all atoms) and more accurate structures.
Fig. 4 shows the resolution of the neutron diffraction data sets as a function of deposition year. Interestingly, the average resolution has not improved in a period of more than 35 years, with the majority of data sets having resolutions of between 1.5 and 2.5 Å. The mean data resolution for all 122 deposited models is 1.99 Å. The highest resolution was reported for PDB entry 4AR3 (Cuypers et al., 2013), which has neutron data extending to 1.05 Å resolution. This is related to the primary reason that researchers conduct neutron crystallography studies of biological macromolecules. Neutron crystallography is not used to determine the structures of biological macromolecules; that is best performed using X-ray crystallography. Rather, neutron crystallography addresses critical science questions that require the direct location and visualization of functionally important H atoms or protons. Using neutron crystallography, H atoms can be located at resolutions of 2.5 Å or less, i.e. the resolution of almost all deposited neutron structures. An exception is PDB entry 3VXF, which was determined with neutron data collected to 2.75 Å resolution (Yamada et al., 2013).
The earlier models were refined with PROLSQ (Hendrickson & Konnert, 1979) and some models determined with neutron data alone were refined using X-PLOR (Brunger, 1992) or SHELX (Gruene et al., 2014; Sheldrick, 2015). We note that the neutron community is increasingly using programs tailored to handle neutron data, such as PHENIX (Afonine et al., 2010) and nCNS (Adams et al., 2009), which can be used for joint XN refinement (Table 3).
3.2. Data files
Six data sets from neutron diffraction experiments in the PDB do not have diffraction data at all (PDB entries 2XQZ, 1GKT, 1io5, 1LZN, 1NTP and 6RSA). Three joint XN data sets have only X-ray data (PDB entries 4CVJ, 3KYX and 5JPR), while in six cases only neutron data are available (PDB entries 3QF6, 4Q49, 3KKX, 5DPN, 3iNS and 5A93).2 In these cases it is possible to refine models against the neutron data alone, but the joint refinement cannot be reproduced. The absence of the X-ray data is largely a result of limitations in earlier PDB deposition processes. It is important that experimental data should be deposited and made available. Of the 122 models determined via neutron or joint XN refinement, nine do not have neutron data, which is more than 7%.
3.2.2. Type of diffraction data
When multiple data arrays associated with a PDB entry are available, it is important to be able to identify whether an array corresponds to X-ray or neutron data. Only 27 of the 67 joint data sets had an annotation in the CIF file, whereas a majority of 40 models did not have any specification. These annotations cannot be processed automatically as they are inconsistent or incomplete in many cases. For example, in some instances there was an annotation for only one array while the other array had none. By comparing R factors using X-ray and neutron scattering factors for both data arrays, their type could be identified. However, this may be complicated if this is convoluted with the issue of incorrect H/D assignment (see §3.3.2).
3.2.3. Incomplete or missing cross-validation (Rfree) sets
The Rfree flags in 24 data sets do not match the available data. This means that at least one reflection in the data file did not have an Rfree flag assigning it to the test set or the working set. If Rfree flags are present, PHENIX tools require a data file to have these flags for every reflection.
3.2.4. Wrong data annotations
It is important to know whether diffraction data are intensities or amplitudes. For example, the neutron data array for PDB entry 2iNQ is indicated as structure-factor amplitudes in the CIF file. The recomputed Rwork and Rfree are 26.6 and 30.6%, respectively. If the data array is treated as intensities, Rwork and Rfree are 20.9 and 25.0%, respectively, which are much closer to the published values of 18.2 and 23.3%. This is likely to be owing to incorrect annotation during deposition or conversion.
3.3. Model files
3.3.1. Information in the PDB file header
The information in the PDB file header can be incomplete, i.e. the values necessary to perform the refinement under the same conditions, such as the resolution limit or the σ cutoff, have not been included. Furthermore, there are cases where the information is different in the header and in the concomitant paper. For example, the header of PDB entry 1WQ2 reports 22.9 and 28.9% for Rwork and Rfree, respectively, while the paper indicates values of 28.2 and 30.1% (Chatake, Mizuno et al., 2003). The latter are similar to the recomputed R factors (28.5 and 31.1% for Rwork and Rfree, respectively).
The H (or D) atoms and the presence of exchanged sites with both H and D are most likely to be the largest source of confusion in model files (discussed below).
3.3.2. Availability of H/D atoms
3.3.3. Modeling of partially exchanged sites
Atomic models of partially deuterated crystals contain sites with both H and D atoms sharing the same location. This situation arises if only a fraction of a particular H atom of all of the molecules in the crystal was replaced by a D atom. At least three approaches for the simultaneous modeling of an H and D atom at the same location were found in models deposited in the PDB. Fig. 5 shows the PDB format for an amide H atom for the three modeling options. The PDB format lines describe the same information, i.e. an H atom with occupancy 0.77 and a D atom with occupancy 0.23 at the same location. The lines look rather different for the different methods and they are explained below.
3.3.4. Hydrogenation state
Fig. 6 shows a histogram of the hydrogenation state, as determined by the procedure described in §2.3.1. Most models (88) contain significant amounts of both H and D atoms, with a majority of H atoms. It is likely that these models correspond to crystals of hydrogenated protein soaked in D2O. 19 models contain predominantly D atoms (among H and D) and are likely to originate from crystals of perdeuterated protein containing deuterated solvent. Ten models contain significant amounts of both H and D atoms, with a majority of D atoms. In most of these cases the proteins were expressed in a deuterated medium that contained D2O but with hydrogenated glycerol, which leads to mixed H/D occupancy at every nonexchangeable C—H site (PDB entries 4JEC, 5E5J, 5E5K and 5T8H), hydrogen labeling (PDB entry 3KYY; Gardberg et al., 2010) or selective protonation or deuteration (Fisher et al., 2014; PDB entry 4NY6). Five models are in the fourth category and contain mainly H atoms (among H and D), such as PDB entries 5D97 (a hydrogenated crystal) and 1NTP (contains a small number of exchanged H atoms).
As the hydrogenation state is difficult to assess algorithmically, we suggest that the PDB or mmCIF file should contain a specific keyword identifying the protonation state. For example: `protonation: H' (or `D' or `H and D' in the other cases).
Table 1 shows a more detailed breakdown of the H- and D-atom count, sorted according to the hydrogenation state of the model, for protein residues, water molecules and other entities (such as ligands). The percentage of H/D sites represents how many of the total H sites in a protein are modeled with both an H and a D atom. A large number of models containing both H and D atoms do not have shared sites, i.e. a site is either occupied by an H atom or a D atom. Most notably, of the 88 models that contain more H than D atoms, 23 do not have any shared sites. It is not possible to determine algorithmically whether this choice was made on purpose (for example to decrease the number of refinable parameters by avoiding H/D-occupancy refinement) or whether the complementary atom is assumed to be accounted for but is not physically present in the file [such as for method (ii) described in §3.3.3].
For models containing shared sites, the ratio of exchanged sites and all modeled protein H atoms in the model in question varies between 4 and 23%. Notable exceptions are models 4JEC, 5E5J, 5E5K and 5T8H, where the ratio of exchanged H/D is 83, 78, 75 and 69%, respectively. As mentioned above, the samples for these models were prepared in a special manner and are expected to contain H and D atoms at the majority of sites (exchangeable and not exchangeable).
The table also lists the number of water molecules modeled with no, one or two D atoms. In 52 of the 122 models all water molecules were modeled as D2O molecules. However, it was reported that only a fraction of water molecules show a distinguished triangular shape in nuclear scattering length density maps that allows the location of both D atoms (Chatake, Ostermann et al., 2003). Fig. 7 shows the percentage of water molecules modeled as D2O as a function of resolution. Only with the higher resolution data sets is it possible to accurately differentiate between different water species (OD−, D2O and D3O+).
3.3.5. Properties of exchanged sites
As D has a larger mass than H, it is expected that D has a lower ADP. However, the resolution of most macromolecular neutron diffraction data sets is not sufficient to detect this difference. Imposing the same ADPs and coordinates for H and D atoms is therefore a reasonable approximation. The sum of occupancies at H/D sites is constrained to 1. We analysed whether exchanged sites in all models fulfil these criteria.
Out of 81 models with at least one exchanged H/D, 20 have different coordinates (25%), ten have sites with different ADPs and eight and six have the sum of occupancies smaller and larger than one, respectively. The number of mismatches per model can range from one (one coordinate mismatch, PDB entry 3U2J) to 542 (coordinate mismatch and occupancy sum < 1; PDB entry 2DXM).
In some cases, the mismatch comes from model errors, such as in PDB entry 4JEC, where the HG3 atom of proline 1 (chain A) has the wrong atom name, which should be correctly indicated as HG2. It has the same coordinates and ADP as DG2 and the sum of occupancies qDG2 + qHG3(HG2) = 1. DG3, on the other hand, is modeled as being fully occupied. It therefore cannot have an exchanged partner. 364 atoms suffer from mislabeled atom names in this model.
In other models, such as 3FHP, the H and D atoms of the amide N atom are modeled systematically with different coordinates. The distance between the atoms ranges from 0.01 Å (Gly20, chain D) to 0.5 Å (Leu6, chain B).
Model 3HGN has 232 sites with different ADPs (but the same coordinates) for the H and the D atom. The difference can reach up to 11 Å2 (Asn148, chain A). It is possible that the ADPs were refined individually for both atoms (as opposed to being constrained to be equal to each other, as is desirable).
3.3.6. The covalent X—H bond lengths are set to standard X-ray distances
The X—H bond length is different in models derived from X-ray and neutron diffraction data. X-rays interact with electrons, and in the case of the H atom (which has only one valence electron and therefore no core electrons) the electron distribution is shifted along the covalent X—H bond towards atom X. Neutrons interact with the nuclei, which are not affected by deformations of the valence electron density owing to chemical bonds. H-atom nuclear scattering length density peaks are therefore at a different location to electron-density peaks (Fig. 8), and X—H bond lengths thus appear to be shorter in X-ray models than in neutron models. The difference in bond length is 10–20% (Allen, 1986; Allen & Bruno, 2010), requiring that standard neutron distances be used for the refinement of H and D atoms in neutron models. It was mentioned by Gruene et al. (2014) that several neutron models were refined with X-ray X—H bond lengths. Of the 122 neutron models deposited in the PDB, the H (or D) atoms are located at X-ray distances in more than 40 models.
Using shorter (X-ray) instead of longer (neutron) bond lengths may not affect R-factor values greatly and the effect may largely depend on the data resolution (lower impact at lower resolution, greater impact at higher resolution). For example, in PDB entry 2GVE, which contains 4195 H atoms, most of them are placed at standard X-ray distances; the recomputed Rwork and Rfree are 24.7 and 30.0%, respectively. Using standard neutron distances, Rfree decreases to 29.8% while Rwork remains the same. However, to obtain a model that reflects the experimental data correctly, the X—H distances should be according to commonly accepted targets for neutron distances.
4. Summary of the lessons learned from the survey
Table 2 provides a summary of the following parameters for all neutron models: PDB code, deposition year, H/D state, refinement program, high-resolution and σ cutoff, published and recomputed Rwork and Rfree. Table 3 lists the same information for models from joint XN refinement, along with relevant cutoffs and R factors for the X-ray data sets.
To address the differences between models described in §3, we suggest that the following guidelines are adopted during the deposition and validation of neutron models.
5. Development of a validation tool for H atoms
The work described in this report led to the development of a new tool in PHENIX that can comprehensively validate neutron models and data. It is available in PHENIX release 1.13 and later. The following validation tasks are performed.
Neutron models constitute a small fraction of the models deposited in the PDB; however, the information that they provide is unique and of great importance for understanding biological function. At present, X-ray crystallography is the method of choice for determining the structure of biological macromolecules. Neutron crystallography is used only in cases where a critical science question requires the direct localization and visualization of H atoms or protons. The initial goal of surveying neutron models was to verify the suitability of their use in the development and benchmarking of new robust computational tools for neutron crystallography. However, a preliminary assessment of model-to-data fit quality has revealed opportunities to improve the PDB annotation and validation methods and the deposition process itself. Implementation of the suggested improvements will minimize inconsistencies between the deposited neutron models available in the PDB and therefore the possibility of misinterpretation. Most of the issues identified concerned the handling of H and D atoms. The survey led to the development of a new tool in PHENIX that can comprehensively validate H and D atoms in protein models. Since the primary use of macromolecular crystallography is to locate and directly visualize H atoms, it is important to address these issues, so that deposited neutron models allow the retrieval of the maximum amount of information with the smallest effort of manual intervention.
1The scattering length of hydrogen is −3.74 fm and that of carbon is +6.65 fm. The sum of the scattering lengths of two H atoms and one C atom is approximately zero.
2Model 5A93 contains two arrays, but they are identical neutron data arrays.
3See File formats and the PDB (https://www.wwpdb.org/documentation/file-formats-and-the-pdb).
4Question 2.4 at wwPDB validation report FAQs (https://www.wwpdb.org/validation/2016/FAQs): `…no reports are currently created for structures determined by neutron diffraction…'.
PL would like to thank Andrey Kovalevsky and Leighton Coates for helpful discussions.
We gratefully acknowledge the financial support of NIH/NIGMS through grants 5P01GM063210 and 1R01GM071939. Our work was supported in part by the US Department of Energy under Contracts No. DE-AC03-76SF00098 and DE-AC02-05CH11231.
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