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.

Crystal structures of multidrug efflux transporters from Burkholderia pseudomallei suggest details of transport mechanism.

BpeB and BpeF are multidrug efflux transporters from Burkholderia pseudomallei that enable multidrug resistance. Here, we report the crystal structures of BpeB and BpeF at 2.94 Å and 3.0 Å resolution, respectively. BpeB was found as an asymmetric trimer, consistent with the widely-accepted functional rotation mechanism for this type of transporter. One of the monomers has a distinct structure that we interpret as an intermediate along this functional cycle. Additionally, a detergent molecule bound in a previously undescribed binding site provides insights into substrate translocation through the pathway. BpeF shares structural similarities with the crystal structure of OqxB from Klebsiella pneumoniae, where both are symmetric trimers composed of three "binding"-state monomers. The structures of BpeB and BpeF further our understanding of the functional mechanisms of transporters belonging to the HAE1-RND superfamily.

Improved AlphaFold modeling with implicit experimental information.

Machine-learning prediction algorithms such as AlphaFold and RoseTTAFold can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy. We hypothesized that by implicitly including new experimental information such as a density map, a greater portion of a model could be predicted accurately, and that this might synergistically improve parts of the model that were not fully addressed by either machine learning or experiment alone. An iterative procedure was developed in which AlphaFold models are automatically rebuilt on the basis of experimental density maps and the rebuilt models are used as templates in new AlphaFold predictions. We show that including experimental information improves prediction beyond the improvement obtained with simple rebuilding guided by the experimental data. This procedure for AlphaFold modeling with density has been incorporated into an automated procedure for interpretation of crystallographic and electron cryo-microscopy maps.

Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge.

This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of current metrics used for model evaluation, particularly Fit-to-Map metrics, with focus on near-atomic resolution. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, including three forming a resolution series (1.8 to 3.1 Å). The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual experiments and structure data archives such as the Protein Data Bank. We recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed cryo-EM map density.

Improvement of cryo-EM maps by density modification.

A density-modification procedure for improving maps from single-particle electron cryogenic microscopy (cryo-EM) is presented. The theoretical basis of the method is identical to that of maximum-likelihood density modification, previously used to improve maps from macromolecular X-ray crystallography. Key differences from applications in crystallography are that the errors in Fourier coefficients are largely in the phases in crystallography but in both phases and amplitudes in cryo-EM, and that half-maps with independent errors are available in cryo-EM. These differences lead to a distinct approach for combination of information from starting maps with information obtained in the density-modification process. The density-modification procedure was applied to a set of 104 datasets and improved map-model correlation and increased the visibility of details in many of the maps. The procedure requires two unmasked half-maps and a sequence file or other source of information on the volume of the macromolecule that has been imaged.

Bottom-up structural proteomics: cryoEM of protein complexes enriched from the cellular milieu.

X-ray crystallography often requires non-native constructs involving mutations or truncations, and is challenged by membrane proteins and large multicomponent complexes. We present here a bottom-up endogenous structural proteomics approach whereby near-atomic-resolution cryo electron microscopy (cryoEM) maps are reconstructed ab initio from unidentified protein complexes enriched directly from the endogenous cellular milieu, followed by identification and atomic modeling of the proteins. The proteins in each complex are identified using cryoID, a program we developed to identify proteins in ab initio cryoEM maps. As a proof of principle, we applied this approach to the malaria-causing parasite Plasmodium falciparum, an organism that has resisted conventional structural-biology approaches, to obtain atomic models of multiple protein complexes implicated in intraerythrocytic survival of the parasite. Our approach is broadly applicable for determining structures of undiscovered protein complexes enriched directly from endogenous sources.

A fully automatic method yielding initial models from high-resolution cryo-electron microscopy maps.

We report a fully automated procedure for the optimization and interpretation of reconstructions from cryo-electron microscopy (cryo-EM) data, available in Phenix as phenix.map_to_model. We applied our approach to 476 datasets with resolution of 4.5 Å or better, including reconstructions of 47 ribosomes and 32 other protein-RNA complexes. The median fraction of residues in the deposited structures reproduced automatically was 71% for reconstructions determined at resolutions of 3 Å or better and 47% for those at resolutions worse than 3 Å.

Map segmentation, automated model-building and their application to the Cryo-EM Model Challenge.

A recently-developed method for identifying a compact, contiguous region representing the unique part of a density map was applied to 218 Cryo-EM maps with resolutions of 4.5 Šor better. The key elements of the segmentation procedure are (1) identification of all regions of density above a threshold and (2) choice of a unique set of these regions, taking symmetry into consideration, that maximize connectivity and compactness. This segmentation approach was then combined with tools for automated map sharpening and model-building to generate models for the 12 maps in the 2016 Cryo-EM Model Challenge in a fully automated manner. The resulting models have completeness from 24% to 82% and RMS distances from reference interpretations of 0.6 Å-2.1 Å.

Macromolecular X-ray structure determination using weak, single-wavelength anomalous data.

We describe a likelihood-based method for determining the substructure of anomalously scattering atoms in macromolecular crystals that allows successful structure determination by single-wavelength anomalous diffraction (SAD) X-ray analysis with weak anomalous signal. With the use of partial models and electron density maps in searches for anomalously scattering atoms, testing of alternative values of parameters and parallelized automated model-building, this method has the potential to extend the applicability of the SAD method in challenging cases.

Structural and Biophysical Characterization of the Mycobacterium tuberculosis Protein Rv0577, a Protein Associated with Neutral Red Staining of Virulent Tuberculosis Strains and Homologue of the Streptomyces coelicolor Protein KbpA.

Mycobacterium tuberculosis protein Rv0577 is a prominent antigen in tuberculosis patients, the component responsible for neutral red staining of virulent strains of M. tuberculosis, a putative component in a methylglyoxal detoxification pathway, and an agonist of toll-like receptor 2. It also has an amino acid sequence that is 36% identical to that of Streptomyces coelicolor AfsK-binding protein A (KbpA), a component in the complex secondary metabolite pathways in the Streptomyces genus. To gain insight into the biological function of Rv0577 and the family of KpbA kinase regulators, the crystal structure for Rv0577 was determined to a resolution of 1.75 Å, binding properties with neutral red and deoxyadenosine were surveyed, backbone dynamics were measured, and thermal stability was assayed by circular dichroism spectroscopy. The protein is composed of four approximate repeats with a ßαßßß topology arranged radially in consecutive pairs to form two continuous eight-strand ß-sheets capped on both ends with an α-helix. The two ß-sheets intersect in the center at roughly a right angle and form two asymmetric deep "saddles" that may serve to bind ligands. Nuclear magnetic resonance chemical shift perturbation experiments show that neutral red and deoxyadenosine bind to Rv0577. Binding to deoxyadenosine is weaker with an estimated dissociation constants of 4.1 ± 0.3 mM for saddle 1. Heteronuclear steady-state {1H}-15N nuclear Overhauser effect, T1, and T2 values were generally uniform throughout the sequence with only a few modest pockets of differences. Circular dichroism spectroscopy characterization of the thermal stability of Rv0577 indicated irreversible unfolding upon heating with an estimated melting temperature of 56 °C.

Improved molecular replacement by density- and energy-guided protein structure optimization.

Molecular replacement procedures, which search for placements of a starting model within the crystallographic unit cell that best account for the measured diffraction amplitudes, followed by automatic chain tracing methods, have allowed the rapid solution of large numbers of protein crystal structures. Despite extensive work, molecular replacement or the subsequent rebuilding usually fail with more divergent starting models based on remote homologues with less than 30% sequence identity. Here we show that this limitation can be substantially reduced by combining algorithms for protein structure modelling with those developed for crystallographic structure determination. An approach integrating Rosetta structure modelling with Autobuild chain tracing yielded high-resolution structures for 8 of 13 X-ray diffraction data sets that could not be solved in the laboratories of expert crystallographers and that remained unsolved after application of an extensive array of alternative approaches. We estimate that the new method should allow rapid structure determination without experimental phase information for over half the cases where current methods fail, given diffraction data sets of better than 3.2 Å resolution, four or fewer copies in the asymmetric unit, and the availability of structures of homologous proteins with >20% sequence identity.

Conformational dynamics of a crystalline protein from microsecond-scale molecular dynamics simulations and diffuse X-ray scattering.

X-ray diffraction from protein crystals includes both sharply peaked Bragg reflections and diffuse intensity between the peaks. The information in Bragg scattering is limited to what is available in the mean electron density. The diffuse scattering arises from correlations in the electron density variations and therefore contains information about collective motions in proteins. Previous studies using molecular-dynamics (MD) simulations to model diffuse scattering have been hindered by insufficient sampling of the conformational ensemble. To overcome this issue, we have performed a 1.1-µs MD simulation of crystalline staphylococcal nuclease, providing 100-fold more sampling than previous studies. This simulation enables reproducible calculations of the diffuse intensity and predicts functionally important motions, including transitions among at least eight metastable states with different active-site geometries. The total diffuse intensity calculated using the MD model is highly correlated with the experimental data. In particular, there is excellent agreement for the isotropic component of the diffuse intensity, and substantial but weaker agreement for the anisotropic component. Decomposition of the MD model into protein and solvent components indicates that protein-solvent interactions contribute substantially to the overall diffuse intensity. We conclude that diffuse scattering can be used to validate predictions from MD simulations and can provide information to improve MD models of protein motions.

Improved low-resolution crystallographic refinement with Phenix and Rosetta.

Refinement of macromolecular structures against low-resolution crystallographic data is limited by the ability of current methods to converge on a structure with realistic geometry. We developed a low-resolution crystallographic refinement method that combines the Rosetta sampling methodology and energy function with reciprocal-space X-ray refinement in Phenix. On a set of difficult low-resolution cases, the method yielded improved model geometry and lower free R factors than alternate refinement methods.

Crystal structure of Bacillus subtilis GabR, an autorepressor and transcriptional activator of gabT.

Bacillus subtilis GabR is a transcription factor that regulates gamma-aminobutyric acid (GABA) metabolism. GabR is a member of the understudied MocR/GabR subfamily of the GntR family of transcription regulators. A typical MocR/GabR-type regulator is a chimeric protein containing a short N-terminal helix-turn-helix DNA-binding domain and a long C-terminal pyridoxal 5'-phosphate (PLP)-binding putative aminotransferase domain. In the presence of PLP and GABA, GabR activates the gabTD operon, which allows the bacterium to use GABA as nitrogen and carbon sources. GabR binds to its own promoter and represses gabR transcription in the absence of GABA. Here, we report two crystal structures of full-length GabR from B. subtilis: a 2.7-Å structure of GabR with PLP bound and the 2.55-Å apo structure of GabR without PLP. The quaternary structure of GabR is a head-to-tail domain-swap homodimer. Each monomer comprises two domains: an N-terminal winged-helix DNA-binding domain and a C-terminal PLP-binding type I aminotransferase-like domain. The winged-helix domain contains putative DNA-binding residues conserved in other GntR-type regulators. Together with sedimentation velocity and fluorescence polarization assays, the crystal structure of GabR provides insights into DNA binding by GabR at the gabR and gabT promoters. The absence of GabR-mediated aminotransferase activity in the presence of GABA and PLP, and the presence of an active site configuration that is incompatible with stabilization of the GABA external aldimine suggest that a GabR aminotransferase-like activity involving GABA and PLP is not essential to its primary function as a transcription regulator.

FEM: feature-enhanced map.

A method is presented that modifies a 2mFobs - DFmodel σA-weighted map such that the resulting map can strengthen a weak signal, if present, and can reduce model bias and noise. The method consists of first randomizing the starting map and filling in missing reflections using multiple methods. This is followed by restricting the map to regions with convincing density and the application of sharpening. The final map is then created by combining a series of histogram-equalized intermediate maps. In the test cases shown, the maps produced in this way are found to have increased interpretability and decreased model bias compared with the starting 2mFobs - DFmodel σA-weighted map.

Predicting X-ray diffuse scattering from translation-libration-screw structural ensembles.

Identifying the intramolecular motions of proteins and nucleic acids is a major challenge in macromolecular X-ray crystallography. Because Bragg diffraction describes the average positional distribution of crystalline atoms with imperfect precision, the resulting electron density can be compatible with multiple models of motion. Diffuse X-ray scattering can reduce this degeneracy by reporting on correlated atomic displacements. Although recent technological advances are increasing the potential to accurately measure diffuse scattering, computational modeling and validation tools are still needed to quantify the agreement between experimental data and different parameterizations of crystalline disorder. A new tool, phenix.diffuse, addresses this need by employing Guinier's equation to calculate diffuse scattering from Protein Data Bank (PDB)-formatted structural ensembles. As an example case, phenix.diffuse is applied to translation-libration-screw (TLS) refinement, which models rigid-body displacement for segments of the macromolecule. To enable the calculation of diffuse scattering from TLS-refined structures, phenix.tls_as_xyz builds multi-model PDB files that sample the underlying T, L and S tensors. In the glycerophosphodiesterase GpdQ, alternative TLS-group partitioning and different motional correlations between groups yield markedly dissimilar diffuse scattering maps with distinct implications for molecular mechanism and allostery. These methods demonstrate how, in principle, X-ray diffuse scattering could extend macromolecular structural refinement, validation and analysis.

Protein Crystallography from the Perspective of Technology Developments.

Early on, crystallography was a domain of mineralogy and mathematics and dealt mostly with symmetry properties and imaginary crystal lattices. This changed when Wilhelm Conrad Röntgen discovered X-rays in 1895, and in 1912 Max von Laue and his associates discovered X-ray irradiated salt crystals would produce diffraction patterns that could reveal the internal atomic periodicity of the crystals. In the same year the father-and-son team, Henry and Lawrence Bragg successfully solved the first crystal structure of sodium chloride and the era of modern crystallography began. Protein crystallography (PX) started some 20 years later with the pioneering work of British crystallographers. In the past 50-60 years, the achievements of modern crystallography and particularly those in protein crystallography have been due to breakthroughs in theoretical and technical advancements such as phasing and direct methods; to more powerful X-ray sources such as synchrotron radiation (SR); to more sensitive and efficient X-ray detectors; to ever faster computers and to improvements in software. The exponential development of protein crystallography has been accelerated by the invention and applications of recombinant DNA technology that can yield nearly any protein of interest in large amounts and with relative ease. Novel methods, informatics platforms, and technologies for automation and high-throughput have allowed the development of large-scale, high efficiency macromolecular crystallography efforts in the field of structural genomics (SG). Very recently, the X-ray free-electron laser (XFEL) sources and its applications in protein crystallography have shown great potential for revolutionizing the whole field again in the near future.

Archiving raw crystallographic data.

This article describes some of the activities of the IUCr Diffraction Data Deposition Working Group and introduces a collection of articles discussing the archiving of diffraction images.

Continuous mutual improvement of macromolecular structure models in the PDB and of X-ray crystallographic software: the dual role of deposited experimental data.

Accurate crystal structures of macromolecules are of high importance in the biological and biomedical fields. Models of crystal structures in the Protein Data Bank (PDB) are in general of very high quality as deposited. However, methods for obtaining the best model of a macromolecular structure from a given set of experimental X-ray data continue to progress at a rapid pace, making it possible to improve most PDB entries after their deposition by re-analyzing the original deposited data with more recent software. This possibility represents a very significant departure from the situation that prevailed when the PDB was created, when it was envisioned as a cumulative repository of static contents. A radical paradigm shift for the PDB is therefore proposed, away from the static archive model towards a much more dynamic body of continuously improving results in symbiosis with continuously improving methods and software. These simultaneous improvements in methods and final results are made possible by the current deposition of processed crystallographic data (structure-factor amplitudes) and will be supported further by the deposition of raw data (diffraction images). It is argued that it is both desirable and feasible to carry out small-scale and large-scale efforts to make this paradigm shift a reality. Small-scale efforts would focus on optimizing structures that are of interest to specific investigators. Large-scale efforts would undertake a systematic re-optimization of all of the structures in the PDB, or alternatively the redetermination of groups of structures that are either related to or focused on specific questions. All of the resulting structures should be made generally available, along with the precursor entries, with various views of the structures being made available depending on the types of questions that users are interested in answering.

Metrics for comparison of crystallographic maps.

Numerical comparison of crystallographic contour maps is used extensively in structure solution and model refinement, analysis and validation. However, traditional metrics such as the map correlation coefficient (map CC, real-space CC or RSCC) sometimes contradict the results of visual assessment of the corresponding maps. This article explains such apparent contradictions and suggests new metrics and tools to compare crystallographic contour maps. The key to the new methods is rank scaling of the Fourier syntheses. The new metrics are complementary to the usual map CC and can be more helpful in map comparison, in particular when only some of their aspects, such as regions of high density, are of interest.