AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination.

Artificial intelligence-based protein structure prediction methods such as AlphaFold have revolutionized structural biology. The accuracies of these predictions vary, however, and they do not take into account ligands, covalent modifications or other environmental factors. Here, we evaluate how well AlphaFold predictions can be expected to describe the structure of a protein by comparing predictions directly with experimental crystallographic maps. In many cases, AlphaFold predictions matched experimental maps remarkably closely. In other cases, even very high-confidence predictions differed from experimental maps on a global scale through distortion and domain orientation, and on a local scale in backbone and side-chain conformation. We suggest considering AlphaFold predictions as exceptionally useful hypotheses. We further suggest that it is important to consider the confidence in prediction when interpreting AlphaFold predictions and to carry out experimental structure determination to verify structural details, particularly those that involve interactions not included in the prediction.

The first crystal structure of a family 129 glycoside hydrolase from a probiotic bacterium reveals critical residues and metal cofactors.

The α-N-acetylgalactosaminidase from the probiotic bacterium Bifidobacterium bifidum (NagBb) belongs to the glycoside hydrolase family 129 and hydrolyzes the glycosidic bond of Tn-antigen (GalNAcα1-Ser/Thr). NagBb is involved in assimilation of O-glycans on mucin glycoproteins by B. bifidum in the human gastrointestinal tract, but its catalytic mechanism has remained elusive because of a lack of sequence homology around putative catalytic residues and of other structural information. Here we report the X-ray crystal structure of NagBb, representing the first GH129 family structure, solved by the single-wavelength anomalous dispersion method based on sulfur atoms of the native protein. We determined ligand-free, GalNAc, and inhibitor complex forms of NagBb and found that Asp-435 and Glu-478 are located in the catalytic domain at appropriate positions for direct nucleophilic attack at the anomeric carbon and proton donation for the glycosidic bond oxygen, respectively. A highly conserved Asp-330 forms a hydrogen bond with the O4 hydroxyl of GalNAc in the -1 subsite, and Trp-398 provides a stacking platform for the GalNAc pyranose ring. Interestingly, a metal ion, presumably Ca2+, is involved in the recognition of the GalNAc N-acetyl group. Mutations at Asp-435, Glu-478, Asp-330, and Trp-398 and residues involved in metal coordination (including an all-Ala quadruple mutant) significantly reduced the activity, indicating that these residues and the metal ion play important roles in substrate recognition and catalysis. Interestingly, NagBb exhibited some structural similarities to the GH101 endo-α-N-acetylgalactosaminidases, but several critical differences in substrate recognition and reaction mechanism account for the different activities of these two enzymes.

Crystallographic analysis of murine p24γ2 Golgi dynamics domain.

The p24 family proteins form homo- and hetero-oligomeric complexes for efficient transport of cargo proteins from the endoplasmic reticulum to the Golgi apparatus. It consists of four subfamilies (p24α, p24ß, p24γ, and p24δ). p24γ2 plays crucial roles in the selective transport of glycosylphosphatidylinositol-anchored proteins. Here, we determined the crystal structure of mouse p24γ2 Golgi dynamics (GOLD) domain at 2.8 Å resolution by the single anomalous diffraction method using intrinsic sulfur atoms. In spite of low sequence identity among p24 family proteins, p24γ2 GOLD domain assumes a ß-sandwich fold, similar to that of p24ß1 or p24δ1. An additional short α-helix is observed at the C-terminus of the p24γ2 GOLD domain. Intriguingly, p24γ2 GOLD domains crystallize as dimers, and dimer formation seems assisted by the short α-helix. Dimerization modes of GOLD domains are compared among p24 family proteins. Proteins 2017; 85:764-770. © 2016 Wiley Periodicals, Inc.

Radiation decay of thaumatin crystals at three X-ray energies.

Radiation damage is an unavoidable obstacle in X-ray crystallographic data collection for macromolecular structure determination, so it is important to know how much radiation a sample can endure before being degraded beyond an acceptable limit. In the literature, the threshold at which the average intensity of all recorded reflections decreases to a certain fraction of the initial value is called the `dose limit'. The first estimated D50 dose-limit value, at which the average diffracted intensity was reduced to 50%, was 20 MGy and was derived from observing sample decay in electron-diffraction experiments. A later X-ray study carried out at 100 K on ferritin protein crystals arrived at a D50 of 43 MGy, and recommended an intensity reduction of protein reflections to 70%, D70, corresponding to an absorbed dose of 30 MGy, as a more appropriate limit for macromolecular crystallography. In the macromolecular crystallography community, the rate of intensity decay with dose was then assumed to be similar for all protein crystals. A series of diffraction images of cryocooled (100 K) thaumatin crystals at identical small, 2° rotation intervals were recorded at X-ray energies of 6.33 , 12.66 and 19.00 keV. Five crystals were used for each wavelength. The decay in the average diffraction intensity to 70% of the initial value, for data extending to 2.45 Šresolution, was determined to be about 7.5 MGy at 6.33 keV and about 11 MGy at the two higher energies.

Likelihood-based interactive local docking into cryo-EM maps in ChimeraX.

The interpretation of cryo-EM maps often includes the docking of known or predicted structures of the components, which is particularly useful when the map resolution is worse than 4 Å. Although it can be effective to search the entire map to find the best placement of a component, the process can be slow when the maps are large. However, frequently there is a well-founded hypothesis about where particular components are located. In such cases, a local search using a map subvolume will be much faster because the search volume is smaller, and more sensitive because optimizing the search volume for the rotation-search step enhances the signal to noise. A Fourier-space likelihood-based local search approach, based on the previously published em_placement software, has been implemented in the new emplace_local program. Tests confirm that the local search approach enhances the speed and sensitivity of the computations. An interactive graphical interface in the ChimeraX molecular-graphics program provides a convenient way to set up and evaluate docking calculations, particularly in defining the part of the map into which the components should be placed.

On the reproducibility of protein crystal structures: five atomic resolution structures of trypsin.

Structural studies of proteins usually rely on a model obtained from one crystal. By investigating the details of this model, crystallographers seek to obtain insight into the function of the macromolecule. It is therefore important to know which details of a protein structure are reproducible or to what extent they might differ. To address this question, the high-resolution structures of five crystals of bovine trypsin obtained under analogous conditions were compared. Global parameters and structural details were investigated. All of the models were of similar quality and the pairwise merged intensities had large correlation coefficients. The C(α) and backbone atoms of the structures superposed very well. The occupancy of ligands in regions of low thermal motion was reproducible, whereas solvent molecules containing heavier atoms (such as sulfur) or those located on the surface could differ significantly. The coordination lengths of the calcium ion were conserved. A large proportion of the multiple conformations refined to similar occupancies and the residues adopted similar orientations. More than three quarters of the water-molecule sites were conserved within 0.5 Šand more than one third were conserved within 0.1 Å. An investigation of the protonation states of histidine residues and carboxylate moieties was consistent for all of the models. Radiation-damage effects to disulfide bridges were observed for the same residues and to similar extents. Main-chain bond lengths and angles averaged to similar values and were in agreement with the Engh and Huber targets. Other features, such as peptide flips and the double conformation of the inhibitor molecule, were also reproducible in all of the trypsin structures. Therefore, many details are similar in models obtained from different crystals. However, several features of residues or ligands located in flexible parts of the macromolecule may vary significantly, such as side-chain orientations and the occupancies of certain fragments.

In situ ligand restraints from quantum-mechanical methods.

In macromolecular crystallographic structure refinement, ligands present challenges for the generation of geometric restraints due to their large chemical variability, their possible novel nature and their specific interaction with the binding pocket of the protein. Quantum-mechanical approaches are useful for providing accurate ligand geometries, but can be plagued by the number of minima in flexible molecules. In an effort to avoid these issues, the Quantum Mechanical Restraints (QMR) procedure optimizes the ligand geometry in situ, thus accounting for the influence of the macromolecule on the local energy minima of the ligand. The optimized ligand geometry is used to generate target values for geometric restraints during the crystallographic refinement. As demonstrated using a sample of >2330 ligand instances in >1700 protein-ligand models, QMR restraints generally result in lower deviations from the target stereochemistry compared with conventionally generated restraints. In particular, the QMR approach provides accurate torsion restraints for ligands and other entities.

Improved joint X-ray and neutron refinement procedure in Phenix.

Neutron diffraction is one of the three crystallographic techniques (X-ray, neutron and electron diffraction) used to determine the atomic structures of molecules. Its particular strengths derive from the fact that H (and D) atoms are strong neutron scatterers, meaning that their positions, and thus protonation states, can be derived from crystallographic maps. However, because of technical limitations and experimental obstacles, the quality of neutron diffraction data is typically much poorer (completeness, resolution and signal to noise) than that of X-ray diffraction data for the same sample. Further, refinement is more complex as it usually requires additional parameters to describe the H (and D) atoms. The increase in the number of parameters may be mitigated by using the `riding hydrogen' refinement strategy, in which the positions of H atoms without a rotational degree of freedom are inferred from their neighboring heavy atoms. However, this does not address the issues related to poor data quality. Therefore, neutron structure determination often relies on the presence of an X-ray data set for joint X-ray and neutron (XN) refinement. In this approach, the X-ray data serve to compensate for the deficiencies of the neutron diffraction data by refining one model simultaneously against the X-ray and neutron data sets. To be applicable, it is assumed that both data sets are highly isomorphous, and preferably collected from the same crystals and at the same temperature. However, the approach has a number of limitations that are discussed in this work by comparing four separately re-refined neutron models. To address the limitations, a new method for joint XN refinement is introduced that optimizes two different models against the different data sets. This approach is tested using neutron models and data deposited in the Protein Data Bank. The efficacy of refining models with H atoms as riding or as individual atoms is also investigated.

Accelerating crystal structure determination with iterative AlphaFold prediction.

Experimental structure determination can be accelerated with artificial intelligence (AI)-based structure-prediction methods such as AlphaFold. Here, an automatic procedure requiring only sequence information and crystallographic data is presented that uses AlphaFold predictions to produce an electron-density map and a structural model. Iterating through cycles of structure prediction is a key element of this procedure: a predicted model rebuilt in one cycle is used as a template for prediction in the next cycle. This procedure was applied to X-ray data for 215 structures released by the Protein Data Bank in a recent six-month period. In 87% of cases our procedure yielded a model with at least 50% of Cα atoms matching those in the deposited models within 2 Å. Predictions from the iterative template-guided prediction procedure were more accurate than those obtained without templates. It is concluded that AlphaFold predictions obtained based on sequence information alone are usually accurate enough to solve the crystallographic phase problem with molecular replacement, and a general strategy for macromolecular structure determination that includes AI-based prediction both as a starting point and as a method of model optimization is suggested.

How good can our beamlines be?

The accuracy of X-ray diffraction data depends on the properties of the crystalline sample and on the performance of the data-collection facility (synchrotron beamline elements, goniostat, detector etc.). However, it is difficult to evaluate the level of performance of the experimental setup from the quality of data sets collected in rotation mode, as various crystal properties such as mosaicity, non-uniformity and radiation damage affect the measured intensities. A multiple-image experiment, in which several analogous diffraction frames are recorded consecutively at the same crystal orientation, allows minimization of the influence of the sample properties. A series of 100 diffraction images of a thaumatin crystal were measured on the SBC beamline 19BM at the APS (Argonne National Laboratory). The obtained data were analyzed in the context of the performance of the data-collection facility. An objective way to estimate the uncertainties of individual reflections was achieved by analyzing the behavior of reflection intensities in the series of analogous diffraction images. The multiple-image experiment is found to be a simple and adequate method to decompose the random errors from the systematic errors in the data, which helps in judging the performance of a data-collection facility. In particular, displaying the intensity as a function of the frame number allows evaluation of the stability of the beam, the beamline elements and the detector with minimal influence of the crystal properties. Such an experiment permits evaluation of the highest possible data quality potentially achievable at the particular beamline.

Dimeric structure of the N-terminal domain of PriB protein from Thermoanaerobacter tengcongensis solved ab initio.

PriB is one of the components of the bacterial primosome, which catalyzes the reactivation of stalled replication forks at sites of DNA damage. The N-terminal domain of the PriB protein from the thermophilic bacterium Thermoanaerobacter tengcongensis (TtePriB) was expressed and its crystal structure was solved at the atomic resolution of 1.09 Šby direct methods. The protein chain, which encompasses the first 104 residues of the full 220-residue protein, adopts the characteristic oligonucleotide/oligosaccharide-binding (OB) structure consisting of a five-stranded ß-barrel filled with hydrophobic residues and equipped with four loops extending from the barrel. In the crystal two protomers dimerize, forming a six-stranded antiparallel ß-sheet. The structure of the N-terminal OB domain of T. tengcongensis shows significant differences compared with mesophile PriBs. While in all other known structures of PriB a dimer is formed by two identical OB domains in separate chains, TtePriB contains two consecutive OB domains in one chain. However, sequence comparison of both the N-terminal and the C-terminal domains of TtePriB suggests that they have analogous structures and that the natural protein possesses a structure similar to a dimer of two N-terminal domains.

Structural insights and ab initio sequencing within the DING proteins family.

DING proteins constitute an intriguing family of phosphate-binding proteins that was identified in a wide range of organisms, from prokaryotes and archae to eukaryotes. Despite their seemingly ubiquitous occurrence in eukaryotes, their encoding genes are missing from sequenced genomes. Such a lack has considerably hampered functional studies. In humans, these proteins have been related to several diseases, like atherosclerosis, kidney stones, inflammation processes and HIV inhibition. The human phosphate binding protein is a human representative of the DING family that was serendipitously discovered from human plasma. An original approach was developed to determine ab initio the complete and exact sequence of this 38 kDa protein by utilizing mass spectrometry and X-ray data in tandem. Taking advantage of this first complete eukaryotic DING sequence, a immunohistochemistry study was undertaken to check the presence of DING proteins in various mice tissues, revealing that these proteins are widely expressed. Finally, the structure of a bacterial representative from Pseudomonas fluorescens was solved at sub-angstrom resolution, allowing the molecular mechanism of the phosphate binding in these high-affinity proteins to be elucidated.

Topological analysis of hydrogen bonds and weak interactions in protein helices via transferred experimental charge density parameters.

Helices represent the most abundant secondary structure motif in proteins and are often involved in various functional roles. They are stabilized by a network of hydrogen bonds between main chain carbonyl and amide groups. Several surveys scrutinized these hydrogen bonds, mostly based on the geometry of the interaction. Alternatively, the topological analysis of the electron density provides a powerful technique to investigate hydrogen bonds. For the first time, transferred experimental charge density parameters (ELMAM database) were used to carry out a topological analysis of the electron density in protein helices. New parameters for the description of the hydrogen bond geometry are proposed. Bonding contacts between the amide N and carbonyl O atoms (N···O) of helices, poorly addressed in the literature so far, were characterized from topological, geometrical, and local energetic analyses. Particularly, a geometrical criterion allowing for the discrimination between hydrogen bonds and N···O contacts is proposed.

CERES: a cryo-EM re-refinement system for continuous improvement of deposited models.

The field of electron cryomicroscopy (cryo-EM) has advanced quickly in recent years as the result of numerous technological and methodological developments. This has led to an increase in the number of atomic structures determined using this method. Recently, several tools for the analysis of cryo-EM data and models have been developed within the Phenix software package, such as phenix.real_space_refine for the refinement of atomic models against real-space maps. Also, new validation metrics have been developed for low-resolution cryo-EM models. To understand the quality of deposited cryo-EM structures and how they might be improved, models deposited in the Protein Data Bank that have map resolutions of better than 5 Šwere automatically re-refined using current versions of Phenix tools. The results are available on a publicly accessible web page (https://cci.lbl.gov/ceres). The implementation of a Cryo-EM Re-refinement System (CERES) for the improvement of models deposited in the wwPDB, and the results of the re-refinements, are described. Based on these results, contents are proposed for a `cryo-EM Table 1', which summarizes experimental details and validation metrics in a similar way to `Table 1' in crystallography. The consistent use of robust metrics for the evaluation of cryo-EM models and data should accompany every structure deposition and be reported in scientific publications.

Arginine off-kilter: guanidinium is not as planar as restraints denote.

Crystallographic refinement of macromolecular structures relies on stereochemical restraints to mitigate the typically poor data-to-parameter ratio. For proteins, each amino acid has a unique set of geometry restraints which represent stereochemical information such as bond lengths, valence angles, torsion angles, dihedrals and planes. It has been shown that the geometry in refined structures can differ significantly from that present in libraries; for example, it was recently reported that the guanidinium moiety in arginine is not symmetric. In this work, the asymmetry of the Nϵ-Cζ-Nη1 and Nϵ-Cζ-Nη2 valence angles in the guanidinium moiety is confirmed. In addition, it was found that the Cδ atom can deviate significantly (more than 20°) from the guanidinium plane. This requires the relaxation of the planar restraint for the Cδ atom, as it otherwise causes the other atoms in the group to compensate by distorting the guanidinium core plane. A new set of restraints for the arginine side chain have therefore been formulated, and are available in the software package Phenix, that take into account the asymmetry of the group and the planar deviation of the Cδ atom. This is an example of the need to regularly revisit the geometric restraint libraries used in macromolecular refinement so that they reflect the best knowledge of the structural chemistry of their components available at the time.

Implementation of the riding hydrogen model in CCTBX to support the next generation of X-ray and neutron joint refinement in Phenix.

A fundamental prerequisite for implementing new procedures of atomic model refinement against neutron diffraction data is the efficient handling of hydrogen atoms. The riding hydrogen model, which constrains hydrogen atom parameters to those of the non-hydrogen atoms, is a plausible parameterization for refinements. This work describes the implementation of the riding hydrogen model in the Computational Crystallography Toolbox and in Phenix. Riding hydrogen atoms can be found in several different configurations that are characterized by specific geometries. For each configuration, the hydrogen atom parameterization and the expressions for the gradients of refinement target function with respect to non-hydrogen parameters are described.

What are the current limits on determination of protonation state using neutron macromolecular crystallography?

The rate of deposition of models determined by neutron diffraction, or a hybrid approach that combines X-ray and neutron diffraction, has increased in recent years. The benefit of neutron diffraction is that hydrogen atom (H) positions are detectable, allowing for the determination of protonation state and water molecule orientation. This study analyses all neutron models deposited in the Protein Data Bank to date, focusing on protonation state and properties of H (or deuterium, D) atoms as well as the details of water molecules. In particular, clashes and hydrogen bonds involving H or D atoms are investigated. As water molecules are typically the least reproducible part of a structural model, their positions in neutron models were compared to those in homologous high-resolution X-ray structures. For models determined by joint refinement against X-ray and neutron data, the water structure comparison was also carried out for models re-refined against the X-ray data alone. The homologues have generally fewer conserved water molecules where X-ray only was used and the positions of equivalent waters vary more than in the case of the hybrid X-ray model. As neutron diffraction data are generally less complete than X-ray data, the influence of neutron data completeness on nuclear density maps was also analyzed. We observe and discuss systematic map quality deterioration as result of data incompleteness.

Elucidation of the phosphate binding mode of DING proteins revealed by subangstrom X-ray crystallography.

PfluDING is a bacterial protein isolated from Pseudomonas fluorescens that belongs to the DING protein family, which is ubiquitous in eukaryotes and extends to prokaryotes. DING proteins and PfluDING have very similar topologies to phosphate Solute Binding Proteins (SBPs). The three-dimensional structure of PfluDING was obtained at subangstrom resolution (0.88 and 0.98 A) at two different pH's (4.5 and 8.5), allowing us to discuss the hydrogen bond network that sequesters the phosphate ion in the binding site. From this high resolution data, we experimentally elucidated the molecular basis of phosphate binding in phosphate SBPs. The phosphate ion is tightly bound to the protein via 12 hydrogen bonds between phosphate oxygen atoms and OH and NH groups of the protein. The proton on one oxygen atom of the phosphate dianion forms a 2.5 A low barrier hydrogen bond with an aspartate, with the energy released by forming this strong bond ensuring the specificity for the dianion even at pH 4.5. In particular, contrary to previous theories on phosphate SBPs, accurate electrostatic potential calculations show that the binding cleft is positively charged. PfluDING structures reveal that only dibasic phosphate binds to the protein at both acidic and basic phosphate, suggesting that the protein binding site environment stabilizes the HPO(4)(2-) form of phosphate.

Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix.

Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks.

Evaluation of models determined by neutron diffraction and proposed improvements to their validation and deposition.

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.