Novel mutations in malonyl-CoA-acyl carrier protein transacylase provoke autosomal recessive optic neuropathy.

Inherited optic neuropathies are rare eye diseases of optic nerve dysfunction that present in various genetic forms. Previously, mutation in three genes encoding mitochondrial proteins has been implicated in autosomal recessive forms of optic atrophy that involve progressive degeneration of optic nerve and retinal ganglion cells (RGC). Using whole exome analysis, a novel double homozygous mutation p.L81R and pR212W in malonyl CoA-acyl carrier protein transacylase (MCAT), a mitochondrial protein involved in fatty acid biosynthesis, has now been identified as responsible for an autosomal recessive optic neuropathy from a Chinese consanguineous family. MCAT is expressed in RGC that are rich in mitochondria. The disease variants lead to structurally unstable MCAT protein with significantly reduced intracellular expression. RGC-specific knockdown of Mcat in mice, lead to an attenuated retinal neurofiber layer, that resembles the phenotype of optic neuropathy. These results indicated that MCAT plays an essential role in mitochondrial function and maintenance of RGC axons, while novel MCAT p.L81R and p.R212W mutations can lead to optic neuropathy.

Fragment-based drug discovery using cryo-EM.

Recent advances in electron cryo-microscopy (cryo-EM) structure determination have pushed the resolutions obtainable by the method into the range widely considered to be of utility for drug discovery. Here, we review the use of cryo-EM in fragment-based drug discovery (FBDD) based on in-house method development. We demonstrate not only that cryo-EM can reveal details of the molecular interactions between fragments and a protein, but also that the current reproducibility, quality, and throughput are compatible with FBDD. We exemplify this using the test system ß-galactosidase (Bgal) and the oncology target pyruvate kinase 2 (PKM2).

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.

Insights into Hunter syndrome from the structure of iduronate-2-sulfatase.

Hunter syndrome is a rare but devastating childhood disease caused by mutations in the IDS gene encoding iduronate-2-sulfatase, a crucial enzyme in the lysosomal degradation pathway of dermatan sulfate and heparan sulfate. These complex glycosaminoglycans have important roles in cell adhesion, growth, proliferation and repair, and their degradation and recycling in the lysosome is essential for cellular maintenance. A variety of disease-causing mutations have been identified throughout the IDS gene. However, understanding the molecular basis of the disease has been impaired by the lack of structural data. Here, we present the crystal structure of human IDS with a covalently bound sulfate ion in the active site. This structure provides essential insight into multiple mechanisms by which pathogenic mutations interfere with enzyme function, and a compelling explanation for severe Hunter syndrome phenotypes. Understanding the structural consequences of disease-associated mutations will facilitate the identification of patients that may benefit from specific tailored therapies.

Can I solve my structure by SAD phasing? Anomalous signal in SAD phasing.

A key challenge in the SAD phasing method is solving a structure when the anomalous signal-to-noise ratio is low. A simple theoretical framework for describing measurements of anomalous differences and the resulting useful anomalous correlation and anomalous signal in a SAD experiment is presented. Here, the useful anomalous correlation is defined as the correlation of anomalous differences with ideal anomalous differences from the anomalous substructure. The useful anomalous correlation reflects the accuracy of the data and the absence of minor sites. The useful anomalous correlation also reflects the information available for estimating crystallographic phases once the substructure has been determined. In contrast, the anomalous signal (the peak height in a model-phased anomalous difference Fourier at the coordinates of atoms in the anomalous substructure) reflects the information available about each site in the substructure and is related to the ability to find the substructure. A theoretical analysis shows that the expected value of the anomalous signal is the product of the useful anomalous correlation, the square root of the ratio of the number of unique reflections in the data set to the number of sites in the substructure, and a function that decreases with increasing values of the atomic displacement factor for the atoms in the substructure. This means that the ability to find the substructure in a SAD experiment is increased by high data quality and by a high ratio of reflections to sites in the substructure, and is decreased by high atomic displacement factors for the substructure.

Can I solve my structure by SAD phasing? Planning an experiment, scaling data and evaluating the useful anomalous correlation and anomalous signal.

A key challenge in the SAD phasing method is solving a structure when the anomalous signal-to-noise ratio is low. Here, algorithms and tools for evaluating and optimizing the useful anomalous correlation and the anomalous signal in a SAD experiment are described. A simple theoretical framework [Terwilliger et al. (2016), Acta Cryst. D72, 346-358] is used to develop methods for planning a SAD experiment, scaling SAD data sets and estimating the useful anomalous correlation and anomalous signal in a SAD data set. The phenix.plan_sad_experiment tool uses a database of solved and unsolved SAD data sets and the expected characteristics of a SAD data set to estimate the probability that the anomalous substructure will be found in the SAD experiment and the expected map quality that would be obtained if the substructure were found. The phenix.scale_and_merge tool scales unmerged SAD data from one or more crystals using local scaling and optimizes the anomalous signal by identifying the systematic differences among data sets, and the phenix.anomalous_signal tool estimates the useful anomalous correlation and anomalous signal after collecting SAD data and estimates the probability that the data set can be solved and the likely figure of merit of phasing.

Local error estimates dramatically improve the utility of homology models for solving crystal structures by molecular replacement.

Predicted structures submitted for CASP10 have been evaluated as molecular replacement models against the corresponding sets of structure factor amplitudes. It has been found that the log-likelihood gain score computed for each prediction correlates well with common structure quality indicators but is more sensitive when the accuracy of the models is high. In addition, it was observed that using coordinate error estimates submitted by predictors to weight the model can improve its utility in molecular replacement dramatically, and several groups have been identified who reliably provide accurate error estimates that could be used to extend the application of molecular replacement for low-homology cases.

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.

Crystal structure of the RNA-guided immune surveillance Cascade complex in Escherichia coli.

Clustered regularly interspaced short palindromic repeats (CRISPR) together with CRISPR-associated (Cas) proteins form the CRISPR/Cas system to defend against foreign nucleic acids of bacterial and archaeal origin. In the I-E subtype CRISPR/Cas system, eleven subunits from five Cas proteins (CasA1B2C6D1E1) assemble along a CRISPR RNA (crRNA) to form the Cascade complex. Here we report on the 3.05 Å crystal structure of the 405-kilodalton Escherichia coli Cascade complex that provides molecular details beyond those available from earlier lower-resolution cryo-electron microscopy structures. The bound 61-nucleotide crRNA spans the entire 11-protein subunit-containing complex, where it interacts with all six CasC subunits (named CasC1-6), with its 5' and 3' terminal repeats anchored by CasD and CasE, respectively. The crRNA spacer region is positioned along a continuous groove on the concave surface generated by the aligned CasC1-6 subunits. The five long ß-hairpins that project from individual CasC2-6 subunits extend across the crRNA, with each ß-hairpin inserting into the gap between the last stacked base and its adjacent splayed counterpart, and positioned within the groove of the preceding CasC subunit. Therefore, instead of continuously stacking, the crRNA spacer region is divided into five equal fragments, with each fragment containing five stacked bases flanked by one flipped-out base. Each of those crRNA spacer fragments interacts with CasC in a similar fashion. Furthermore, our structure explains why the seed sequence, with its outward-directed bases, has a critical role in target DNA recognition. In conclusion, our structure of the Cascade complex provides novel molecular details of protein-protein and protein-RNA alignments and interactions required for generation of a complex mediating RNA-guided immune surveillance.

Automating crystallographic structure solution and refinement of protein-ligand complexes.

High-throughput drug-discovery and mechanistic studies often require the determination of multiple related crystal structures that only differ in the bound ligands, point mutations in the protein sequence and minor conformational changes. If performed manually, solution and refinement requires extensive repetition of the same tasks for each structure. To accelerate this process and minimize manual effort, a pipeline encompassing all stages of ligand building and refinement, starting from integrated and scaled diffraction intensities, has been implemented in Phenix. The resulting system is able to successfully solve and refine large collections of structures in parallel without extensive user intervention prior to the final stages of model completion and validation.

Improved estimates of coordinate error for molecular replacement.

The estimate of the root-mean-square deviation (r.m.s.d.) in coordinates between the model and the target is an essential parameter for calibrating likelihood functions for molecular replacement (MR). Good estimates of the r.m.s.d. lead to good estimates of the variance term in the likelihood functions, which increases signal to noise and hence success rates in the MR search. Phaser has hitherto used an estimate of the r.m.s.d. that only depends on the sequence identity between the model and target and which was not optimized for the MR likelihood functions. Variance-refinement functionality was added to Phaser to enable determination of the effective r.m.s.d. that optimized the log-likelihood gain (LLG) for a correct MR solution. Variance refinement was subsequently performed on a database of over 21,000 MR problems that sampled a range of sequence identities, protein sizes and protein fold classes. Success was monitored using the translation-function Z-score (TFZ), where a TFZ of 8 or over for the top peak was found to be a reliable indicator that MR had succeeded for these cases with one molecule in the asymmetric unit. Good estimates of the r.m.s.d. are correlated with the sequence identity and the protein size. A new estimate of the r.m.s.d. that uses these two parameters in a function optimized to fit the mean of the refined variance is implemented in Phaser and improves MR outcomes. Perturbing the initial estimate of the r.m.s.d. from the mean of the distribution in steps of standard deviations of the distribution further increases MR success rates.

Phaser.MRage: automated molecular replacement.

Phaser.MRage is a molecular-replacement automation framework that implements a full model-generation workflow and provides several layers of model exploration to the user. It is designed to handle a large number of models and can distribute calculations efficiently onto parallel hardware. In addition, phaser.MRage can identify correct solutions and use this information to accelerate the search. Firstly, it can quickly score all alternative models of a component once a correct solution has been found. Secondly, it can perform extensive analysis of identified solutions to find protein assemblies and can employ assembled models for subsequent searches. Thirdly, it is able to use a priori assembly information (derived from, for example, homologues) to speculatively place and score molecules, thereby customizing the search procedure to a certain class of protein molecule (for example, antibodies) and incorporating additional biological information into molecular replacement.

Graphical tools for macromolecular crystallography in PHENIX.

A new Python-based graphical user interface for the PHENIX suite of crystallography software is described. This interface unifies the command-line programs and their graphical displays, simplifying the development of new interfaces and avoiding duplication of function. With careful design, graphical interfaces can be displayed automatically, instead of being manually constructed. The resulting package is easily maintained and extended as new programs are added or modified.

phenix.mr_rosetta: molecular replacement and model rebuilding with Phenix and Rosetta.

The combination of algorithms from the structure-modeling field with those of crystallographic structure determination can broaden the range of templates that are useful for structure determination by the method of molecular replacement. Automated tools in phenix.mr_rosetta simplify the application of these combined approaches by integrating Phenix crystallographic algorithms and Rosetta structure-modeling algorithms and by systematically generating and evaluating models with a combination of these methods. The phenix.mr_rosetta algorithms can be used to automatically determine challenging structures. The approaches used in phenix.mr_rosetta are described along with examples that show roles that structure-modeling can play in molecular replacement.

The Phenix software for automated determination of macromolecular structures.

X-ray crystallography is a critical tool in the study of biological systems. It is able to provide information that has been a prerequisite to understanding the fundamentals of life. It is also a method that is central to the development of new therapeutics for human disease. Significant time and effort are required to determine and optimize many macromolecular structures because of the need for manual interpretation of complex numerical data, often using many different software packages, and the repeated use of interactive three-dimensional graphics. The Phenix software package has been developed to provide a comprehensive system for macromolecular crystallographic structure solution with an emphasis on automation. This has required the development of new algorithms that minimize or eliminate subjective input in favor of built-in expert-systems knowledge, the automation of procedures that are traditionally performed by hand, and the development of a computational framework that allows a tight integration between the algorithms. The application of automated methods is particularly appropriate in the field of structural proteomics, where high throughput is desired. Features in Phenix for the automation of experimental phasing with subsequent model building, molecular replacement, structure refinement and validation are described and examples given of running Phenix from both the command line and graphical user interface.

Improvement of molecular-replacement models with Sculptor.

In molecular replacement, the quality of models can be improved by transferring information contained in sequence alignment to the template structure. A family of algorithms has been developed that make use of the sequence-similarity score calculated from residue-substitution scores smoothed over nearby residues to delete or downweight parts of the model that are unreliable. These algorithms have been implemented in the program Sculptor, together with well established methods that are in common use for model improvement. An analysis of the new algorithms has been performed by studying the effect of algorithm parameters on the quality of models. Benchmarking against existing techniques shows that models from Sculptor compare favourably, especially if the alignment is unreliable. Carrying out multiple trials using alternative models created from the same structure but using different algorithm parameters can significantly improve the success rate.

PHENIX: a comprehensive Python-based system for macromolecular structure solution.

Macromolecular X-ray crystallography is routinely applied to understand biological processes at a molecular level. However, significant time and effort are still required to solve and complete many of these structures because of the need for manual interpretation of complex numerical data using many software packages and the repeated use of interactive three-dimensional graphics. PHENIX has been developed to provide a comprehensive system for macromolecular crystallographic structure solution with an emphasis on the automation of all procedures. This has relied on the development of algorithms that minimize or eliminate subjective input, the development of algorithms that automate procedures that are traditionally performed by hand and, finally, the development of a framework that allows a tight integration between the algorithms.

Structural basis for different specificities of acyltransferases associated with the human cytosolic and mitochondrial fatty acid synthases.

Animals employ two systems for the de novo biosynthesis of fatty acids: a megasynthase complex in the cytosol (type I) that produces mainly palmitate, and an ensemble of freestanding enzymes in the mitochondria (type II) that produces mainly octanoyl moieties. The acyltransferases responsible for initiation of fatty acid biosynthesis in the two compartments are distinguished by their different substrate specificities: the type I enzyme transfers both the acetyl primer and the malonyl chain extender, whereas the type II enzyme is responsible for translocation of only the malonyl substrate. Crystal structures for the type I and II enzymes, supported by in silico substrate docking studies and mutagenesis experiments that alter their respective specificities, reveal that, although the two enzymes adopt a similar overall fold, subtle differences at their catalytic centers account for their different specificities.

Structure of the pseudokinase VRK3 reveals a degraded catalytic site, a highly conserved kinase fold, and a putative regulatory binding site.

About 10% of all protein kinases are predicted to be enzymatically inactive pseudokinases, but the structural details of kinase inactivation have remained unclear. We present the first structure of a pseudokinase, VRK3, and that of its closest active relative, VRK2. Profound changes to the active site region underlie the loss of catalytic activity, and VRK3 cannot bind ATP because of residue substitutions in the binding pocket. However, VRK3 still shares striking structural similarity with VRK2, and appears to be locked in a pseudoactive conformation. VRK3 also conserves residue interactions that are surprising in the absence of enzymatic function; these appear to play important architectural roles required for the residual functions of VRK3. Remarkably, VRK3 has an "inverted" pattern of sequence conservation: although the active site is poorly conserved, portions of the molecular surface show very high conservation, suggesting that they form key interactions that explain the evolutionary retention of VRK3.

Mechanism and substrate recognition of human holo ACP synthase.

Mammals utilize a single phosphopantetheinyl transferase for the posttranslational modification of at least three different apoproteins: the carrier protein components of cytosolic and mitochondrial fatty acid synthases and the aminoadipate semialdehyde reductase involved in lysine degradation. We determined the crystal structure of the human phosphopantetheinyl transferase, a eukaryotic phosphopantetheinyl transferase characterized, complexed with CoA and Mg(2+), and in ternary complex with CoA and ACP. The involvement of key residues in ligand binding and catalysis was confirmed by mutagenesis and kinetic analysis. Human phosphopantetheinyl transferase exhibits an alpha/beta fold and 2-fold pseudosymmetry similar to the Sfp phosphopantetheinyl transferase from Bacillus subtilis. Although the bound ACP exhibits a typical four-helix structure, its binding is unusual in that it is facilitated predominantly by hydrophobic interactions. A detailed mechanism is proposed describing the substrate binding and catalytic process.