Methyl transfer in psilocybin biosynthesis

Psilocybin, the natural hallucinogen produced by Psilocybe ("magic") mushrooms, holds great promise for the treatment of depression and several other mental health conditions. The final step in the psilocybin biosynthetic pathway, dimethylation of the tryptophan-derived intermediate norbaeocystin, is catalysed by PsiM. Here we present atomic resolution (0.9 Å) crystal structures of PsiM trapped at various stages of its reaction cycle, providing detailed insight into the SAM-dependent methylation mechanism. Structural and phylogenetic analyses suggest that PsiM derives from epitranscriptomic N6-methyladenosine writers of the METTL16 family, which is further supported by the observation that bound substrates physicochemically mimic RNA. Inherent limitations of the ancestral monomethyltransferase scaffold hamper the efficiency of psilocybin assembly and leave PsiM incapable of catalysing trimethylation to aeruginascin. The results of our study will support bioengineering efforts aiming to create novel variants of psilocybin with improved therapeutic properties.

Toll-Like Receptor 3 Mediates Aortic Stenosis Through a Conserved Mechanism of Calcification

BACKGROUND

Calcific aortic valve disease (CAVD) is characterized by a phenotypic switch of valvular interstitial cells to bone-forming cells. Toll-like receptors (TLRs) are evolutionarily conserved pattern recognition receptors at the interface between innate immunity and tissue repair. Type I interferons (IFNs) are not only crucial for an adequate antiviral response but also implicated in bone formation. We hypothesized that the accumulation of endogenous TLR3 ligands in the valvular leaflets may promote the generation of osteoblast-like cells through enhanced type I IFN signaling.

METHODS

Human valvular interstitial cells isolated from aortic valves were challenged with mechanical strain or synthetic TLR3 agonists and analyzed for bone formation, gene expression profiles, and IFN signaling pathways. Different inhibitors were used to delineate the engaged signaling pathways. Moreover, we screened a variety of potential lipids and proteoglycans known to accumulate in CAVD lesions as potential TLR3 ligands. Ligand-receptor interactions were characterized by in silico modeling and verified through immunoprecipitation experiments. Biglycan (Bgn), Tlr3, and IFN-α/β receptor alpha chain (Ifnar1)-deficient mice and a specific zebrafish model were used to study the implication of the byglycan (BGN)-TLR3-IFN axis in both CAVD and bone formation in vivo. Two large-scale cohorts (GERA [Genetic Epidemiology Research on Adult Health and Aging], n=55 192 with 3469 aortic stenosis cases; UK Biobank, n=257 231 with 2213 aortic stenosis cases) were examined for genetic variation at genes implicated in BGN-TLR3-IFN signaling associating with CAVD in humans.

RESULTS

Here, we identify TLR3 as a central molecular regulator of calcification in valvular interstitial cells and unravel BGN as a new endogenous agonist of TLR3. Posttranslational BGN maturation by xylosyltransferase 1 (XYLT1) is required for TLR3 activation. Moreover, BGN induces the transdifferentiation of valvular interstitial cells into bone-forming osteoblasts through the TLR3-dependent induction of type I IFNs. It is intriguing that Bgn^-/-, Tlr3^-/-, and Ifnar1^-/- mice are protected against CAVD and display impaired bone formation. Meta-analysis of 2 large-scale cohorts with >300 000 individuals reveals that genetic variation at loci relevant to the XYLT1-BGN-TLR3-interferon-α/β receptor alpha chain (IFNAR) 1 pathway is associated with CAVD in humans.

CONCLUSIONS

This study identifies the BGN-TLR3-IFNAR1 axis as an evolutionarily conserved pathway governing calcification of the aortic valve and reveals a potential therapeutic target to prevent CAVD.

SARS-CoV-2 3CLpro mutations selected in a VSV-based system confer resistance to nirmatrelvir, ensitrelvir, and GC376

Protease inhibitors are among the most powerful antiviral drugs. Nirmatrelvir is the first protease inhibitor specifically developed against the SARS-CoV-2 protease 3CLpro that has been licensed for clinical use. To identify mutations that confer resistance to this protease inhibitor, we engineered a chimeric vesicular stomatitis virus (VSV) that expressed a polyprotein composed of the VSV glycoprotein (G), the SARS-CoV-2 3CLpro, and the VSV polymerase (L). Viral replication was thus dependent on the autocatalytic processing of this precursor protein by 3CLpro and release of the functional viral proteins G and L, and replication of this chimeric VSV was effectively inhibited by nirmatrelvir. Using this system, we applied nirmatrelvir to select for resistance mutations. Resistance was confirmed by retesting nirmatrelvir against the selected mutations in additional VSV-based systems, in an independently developed cellular system, in a biochemical assay, and in a recombinant SARS-CoV-2 system. We demonstrate that some mutants are cross-resistant to ensitrelvir and GC376, whereas others are less resistant to these compounds. Furthermore, we found that most of these resistance mutations already existed in SARS-CoV-2 sequences that have been deposited in the NCBI and GISAID databases, indicating that these mutations were present in circulating SARS-CoV-2 strains.

Characterization of the Gateway Decarboxylase for Psilocybin Biosynthesis

The l-tryptophan decarboxylase PsiD catalyzes the initial step of the metabolic cascade to psilocybin, the major indoleethylamine natural product of the "magic" mushrooms and a candidate drug against major depressive disorder. Unlike numerous pyridoxal phosphate (PLP)-dependent decarboxylases for natural product biosyntheses, PsiD is PLP-independent and resembles type II phosphatidylserine decarboxylases. Here, we report on the in vitro biochemical characterization of Psilocybe cubensis PsiD along with in silico modeling of the PsiD structure. A non-canonical serine protease triad for autocatalytic cleavage of the pro-protein was predicted and experimentally verified by site-directed mutagenesis.

The structure of neurofibromin isoform 2 reveals different functional states

The autosomal dominant monogenetic disease neurofibromatosis type 1 (NF1) affects approximately one in 3,000 individuals and is caused by mutations in the NF1 tumour suppressor gene, leading to dysfunction in the protein neurofibromin (Nf1)^1,2. As a GTPase-activating protein, a key function of Nf1 is repression of the Ras oncogene signalling cascade. We determined the human Nf1 dimer structure at an overall resolution of 3.3 Å. The cryo-electron microscopy structure reveals domain organization and structural details of the Nf1 exon 23a splicing³ isoform 2 in a closed, self-inhibited, Zn-stabilized state and an open state. In the closed conformation, HEAT/ARM core domains shield the GTPase-activating protein-related domain (GRD) so that Ras binding is sterically inhibited. In a distinctly different, open conformation of one protomer, a large-scale movement of the GRD occurs, which is necessary to access Ras, whereas Sec14-PH reorients to allow interaction with the cellular membrane⁴. Zn incubation of Nf1 leads to reduced Ras-GAP activity with both protomers in the self-inhibited, closed conformation stabilized by a Zn binding site between the N-HEAT/ARM domain and the GRD–Sec14-PH linker. The transition between closed, self-inhibited states of Nf1 and open states provides guidance for targeted studies deciphering the complex molecular mechanism behind the widespread neurofibromatosis syndrome and Nf1 dysfunction in carcinogenesis.

Cryo-EM structure of Nf1 protein is reported, revealing closed and open conformations that regulate interaction with Ras oncogene, setting the stage for understanding the mechanistic action of Nf1 and how disease mutations lead to dysfunction.

Rapid response to emerging biomedical challenges and threats

As part of the global mobilization to combat the present pandemic, almost 100 000 COVID-19-related papers have been published and nearly a thousand models of macromolecules encoded by SARS-CoV-2 have been deposited in the Protein Data Bank within less than a year. The avalanche of new structural data has given rise to multiple resources dedicated to assessing the correctness and quality of structural data and models. Here, an approach to evaluate the massive amounts of such data using the resource https://covid19.bioreproducibility.org is described, which offers a template that could be used in large-scale initiatives undertaken in response to future biomedical crises. Broader use of the described methodology could considerably curtail information noise and significantly improve the reproducibility of biomedical research.

Correcting cis-trans-transgressions in macromolecular structure models

Many macromolecular X-ray and cryo-EM structure models deposited in the PDB contain biologically relevant small molecule ligands with unsaturated fatty acid acyl chains, whose cis-trans stereochemistry is incorrect. The molecules are either not properly defined in their stereochemical restraint files, or the proper stereochemistry is neglected during model building. Often, the same molecules appear in deposited models in both isomeric configurations, one of which is almost always incorrect, and the use of the same moiety (HET) identifier and restraint files in model refinement is wrong. We present case studies of frequently occurring molecules and a compilation of identified cases of C-C=C-C cis-trans geometry in the deposited structure models. Full listings of cis/trans torsion angles are provided for models with commonly occurring molecules to assist identification and correction of cis-trans errors and prevent inadvertent use of incorrect models. Caveats for users, advice for modellers and suggestions for remediation efforts with a simple but effective restraint file modification are provided.

Crystallographic models of SARS-CoV-2 3CLpro: in-depth assessment of structure quality and validation

The appearance at the end of 2019 of the new SARS-CoV-2 coronavirus led to an unprecedented response by the structural biology community, resulting in the rapid determination of many hundreds of structures of proteins encoded by the virus. As part of an effort to analyze and, if necessary, remediate these structures as deposited in the Protein Data Bank (PDB), this work presents a detailed analysis of 81 crystal structures of the main protease 3CLpro, an important target for the design of drugs against COVID-19. The structures of the unliganded enzyme and its complexes with a number of inhibitors were determined by multiple research groups using different experimental approaches and conditions; the resulting structures span 13 different polymorphs representing seven space groups. The structures of the enzyme itself, all determined by molecular replacement, are highly similar, with the exception of one polymorph with a different inter-domain orientation. However, a number of complexes with bound inhibitors were found to pose significant problems. Some of these could be traced to faulty definitions of geometrical restraints for ligands and to the general problem of a lack of such information in the PDB depositions. Several problems with ligand definition in the PDB itself were also noted. In several cases extensive corrections to the models were necessary to adhere to the evidence of the electron-density maps. Taken together, this analysis of a large number of structures of a single, medically important protein, all determined within less than a year using modern experimental tools, should be useful in future studies of other systems of high interest to the biomedical community.

Covid-19.bioreproducibility.org: A web resource for SARS-CoV-2-related structural models

The COVID-19 pandemic has triggered numerous scientific activities aimed at understanding the SARS-CoV-2 virus and ultimately developing treatments. Structural biologists have already determined hundreds of experimental X-ray, cryo-EM, and NMR structures of proteins and nucleic acids related to this coronavirus, and this number is still growing. To help biomedical researchers, who may not necessarily be experts in structural biology, navigate through the flood of structural models, we have created an online resource, covid19.bioreproducibility.org, that aggregates expert-verified information about SARS-CoV-2-related macromolecular models. In this article, we describe this web resource along with the suite of tools and methodologies used for assessing the structures presented therein.

Strategy for Deployment of Integrated Healthy Aging Regions Based Upon an Evidence-Based Regional Ecosystem-The Styria Model

In 2013, the European Commission founded the platform European Innovation Partnership on Active and Healthy Aging as a communication and innovation network in this domain. The goal of the current study was the development of an integrated regional ecosystem for active and healthy aging for the region of Styria via a step-by-step co-creation process. A mixed model approach was used to establish an ecosystem for active and healthy aging, which includes macro-, meso- and micro-level stakeholders in the province of Styria, Austria. Based on the results, eight recommendations for the deployment of a healthy aging region were developed. The visibility and accessibility of healthy aging products and services were evaluated as key factors for innovation in active and healthy aging in the region. Health professionals were identified as major drivers of innovation related to active and healthy aging in Styria. The study presented in this article assessed the capacities for healthy aging in the Styria region and identified the need to improve communication pathways between all levels of the public health system and market.

Ligand-centered assessment of SARS-CoV-2 drug target models in the Protein Data Bank

A bright spot in the SARS‐CoV‐2 (CoV‐2) coronavirus pandemic has been the immediate mobilization of the biomedical community, working to develop treatments and vaccines for COVID‐19. Rational drug design against emerging threats depends on well‐established methodology, mainly utilizing X‐ray crystallography, to provide accurate structure models of the macromolecular drug targets and of their complexes with candidates for drug development. In the current crisis, the structural biological community has responded by presenting structure models of CoV‐2 proteins and depositing them in the Protein Data Bank (PDB), usually without time embargo and before publication. Since the structures from the first‐line research are produced in an accelerated mode, there is an elevated chance of mistakes and errors, with the ultimate risk of hindering, rather than speeding up, drug development. In the present work, we have used model‐validation metrics and examined the electron density maps for the deposited models of CoV‐2 proteins and a sample of related proteins available in the PDB as of April 1, 2020. We present these results with the aim of helping the biomedical community establish a better‐validated pool of data. The proteins are divided into groups according to their structure and function. In most cases, no major corrections were necessary. However, in several cases significant revisions in the functionally sensitive area of protein–inhibitor complexes or for bound ions justified correction, re‐refinement, and eventually reversioning in the PDB. The re‐refined coordinate files and a tool for facilitating model comparisons are available at https://covid-19.bioreproducibility.org.

Controlled dehydration, structural flexibility and gadolinium MRI contrast compound binding in the human plasma glycoprotein afamin

Afamin, which is a human blood plasma glycoprotein, a putative multifunctional transporter of hydrophobic molecules and a marker for metabolic syndrome, poses multiple challenges for crystallographic structure determination, both practically and in analysis of the models. Several hundred crystals were analysed, and an unusual variability in cell volume and difficulty in solving the structure despite an ∼34% sequence identity with nonglycosylated human serum albumin indicated that the molecule exhibits variable and context-sensitive packing, despite the simplified glycosylation in insect cell-expressed recombinant afamin. Controlled dehydration of the crystals was able to stabilize the orthorhombic crystal form, reducing the number of molecules in the asymmetric unit from the monoclinic form and changing the conformational state of the protein. An iterative strategy using fully automatic experiments available on MASSIF-1 was used to quickly determine the optimal protocol to achieve the phase transition, which should be readily applicable to many types of sample. The study also highlights the drawback of using a single crystallographic structure model for computational modelling purposes given that the conformational state of the binding sites and the electron density in the binding site, which is likely to result from PEGs, greatly varies between models. This also holds for the analysis of nonspecific low-affinity ligands, where often a variety of fragments with similar uncertainty can be modelled, inviting interpretative bias. As a promiscuous transporter, afamin also seems to bind gadoteridol, a magnetic resonance imaging contrast compound, in at least two sites. One pair of gadoteridol molecules is located near the human albumin Sudlow site, and a second gadoteridol molecule is located at an intermolecular site in proximity to domain IA. The data from the co-crystals support modern metrics of data quality in the context of the information that can be gleaned from data sets that would be abandoned on classical measures.

Expression, Purification, Crystallization, and Enzyme Assays of Fumarylacetoacetate Hydrolase Domain-Containing Proteins

Fumarylacetoacetate hydrolase (FAH) domain-containing proteins (FAHD) are identified members of the FAH superfamily in eukaryotes. Enzymes of this superfamily generally display multi-functionality, involving mainly hydrolase and decarboxylase mechanisms. This article presents a series of consecutive methods for the expression and purification of FAHD proteins, mainly FAHD protein 1 (FAHD1) orthologues among species (human, mouse, nematodes, plants, etc.). Covered methods are protein expression in E. coli, affinity chromatography, ion exchange chromatography, preparative and analytical gel filtration, crystallization, X-ray diffraction, and photometric assays. Concentrated protein of high levels of purity (>98%) may be employed for crystallization or antibody production. Proteins of similar or lower quality may be employed in enzyme assays or used as antigens in detection systems (Western-Blot, ELISA). In the discussion of this work, the identified enzymatic mechanisms of FAHD1 are outlined to describe its hydrolase and decarboxylase bi-functionality in more detail.

Against Method: Table 1-Cui Bono?

The almost universally required "Table 1," summarizing data-collection and data-processing statistics, has in its present form outlived its usefulness in almost all publications of biomolecular crystal structure reports. Information contained in "Table 1" is insufficient to evaluate or repeat the experiment; is redundant with information extractable from deposited diffraction data; and includes data items whose meaning is under increased scrutiny in the crystallographic community. Direct and consistent extraction and analysis of data quality metrics from preferably unmerged intensity data with graphical presentation of reciprocal space features, including impact on map and model features, should replace "Table 1."

Expression, Purification, and Biochemical Characterization of Human Afamin

Afamin is an 87 kDa glycoprotein with five predicted N-glycosylation sites. Afamin's glycan abundance contributes to conformational and chemical inhomogeneity presenting great challenges for molecular structure determination. For the purpose of studying the structure of afamin, various forms of recombinantly expressed human afamin (rhAFM) with different glycosylation patterns were thus created. Wild-type rhAFM and various hypoglycosylated forms were expressed in CHO, CHO-Lec1, and HEK293T cells. Fully nonglycosylated rhAFM was obtained by transfection of point-mutated cDNA to delete all N-glycosylation sites of afamin. Wild-type and hypo/nonglycosylated rhAFM were purified from cell culture supernatants by immobilized metal ion affinity and size exclusion chromatography. Glycan analysis of purified proteins demonstrated differences in micro- and macro-heterogeneity of glycosylation enabling the comparison between hypoglycosylated, wild-type rhAFM, and native plasma afamin. Because antibody fragments can work as artificial chaperones by stabilizing the structure of proteins and consequently enhance the chance for successful crystallization, we incubated a Fab fragment of the monoclonal anti-afamin antibody N14 with human afamin and obtained a stoichiometric complex. Subsequent results showed sufficient expression of various partially or nonglycosylated forms of rhAFM in HEK293T and CHO cells and revealed that glycosylation is not necessary for expression and secretion.

Detect, correct, retract: How to manage incorrect structural models

The massive technical and computational progress of biomolecular crystallography has generated some adverse side effects. Most crystal structure models, produced by crystallographers or well-trained structural biologists, constitute useful sources of information, but occasional extreme outliers remind us that the process of structure determination is not fail-safe. The occurrence of severe errors or gross misinterpretations raises fundamental questions: Why do such aberrations emerge in the first place? How did they evade the sophisticated validation procedures which often produce clear and dire warnings, and why were severe errors not noticed by the depositors themselves, their supervisors, referees and editors? Once detected, what can be done to either correct, improve or eliminate such models? How do incorrect models affect the underlying claims or biomedical hypotheses they were intended, but failed, to support? What is the long-range effect of the propagation of such errors? And finally, what mechanisms can be envisioned to restore the validity of the scientific record and, if necessary, retract publications that are clearly invalidated by the lack of experimental evidence? We suggest that cognitive bias and flawed epistemology are likely at the root of the problem. By using examples from the published literature and from public repositories such as the Protein Data Bank, we provide case summaries to guide correction or improvement of structural models. When strong claims are unsustainable because of a deficient crystallographic model, removal of such a model and even retraction of the affected publication are necessary to restore the integrity of the scientific record.

Structural Evidence for a Role of the Multi-functional Human Glycoprotein Afamin in Wnt Transport

Afamin, a human plasma glycoprotein and putative transporter of hydrophobic molecules, has been shown to act as extracellular chaperone for poorly soluble, acylated Wnt proteins, forming a stable, soluble complex with functioning Wnt proteins. The 2.1-Å crystal structure of glycosylated human afamin reveals an almost exclusively hydrophobic binding cleft capable of harboring large hydrophobic moieties. Lipid analysis confirms the presence of lipids, and density in the primary binding pocket of afamin was modeled as palmitoleic acid, presenting the native O-acylation on serine 209 in human Wnt3a. The modeled complex between the experimental afamin structure and a Wnt3a homology model based on the XWnt8-Fz8-CRD fragment complex crystal structure is compelling, with favorable interactions comparable with the crystal structure complex. Afamin readily accommodates the conserved palmitoylated serine 209 of Wnt3a, providing a structural basis how afamin solubilizes hydrophobic and poorly soluble Wnt proteins.

Twilight reloaded: the peptide experience

The potential causes of the misinterpretation of peptide density in a significant number of protein–peptide complex structures are analyzed, together with suggestions for good practice and specific education aimed at minimizing overinterpretation and mistakes in protein–peptide complex structure models.

The de facto commoditization of biomolecular crystallography as a result of almost disruptive instrumentation automation and continuing improvement of software allows any sensibly trained structural biologist to conduct crystallo­graphic studies of biomolecules with reasonably valid outcomes: that is, models based on properly interpreted electron density. Robust validation has led to major mistakes in the protein part of structure models becoming rare, but some depositions of protein–peptide complex structure models, which generally carry significant interest to the scientific community, still contain erroneous models of the bound peptide ligand. Here, the protein small-molecule ligand validation tool Twilight is updated to include peptide ligands. (i) The primary technical reasons and potential human factors leading to problems in ligand structure models are presented; (ii) a new method used to score peptide-ligand models is presented; (iii) a few instructive and specific examples, including an electron-density-based analysis of peptide-ligand structures that do not contain any ligands, are discussed in detail; (iv) means to avoid such mistakes and the implications for database integrity are discussed and (v) some suggestions as to how journal editors could help to expunge errors from the Protein Data Bank are provided.

Validation of Protein-Ligand Crystal Structure Models: Small Molecule and Peptide Ligands

Models of target proteins in complex with small molecule ligands or peptide ligands are of significant interest to the biomedical research community. Structure-guided lead discovery and structure-based drug design make extensive use of such models. The bound ligands comprise only a small fraction of the total X-ray scattering mass, and therefore particular care must be taken to properly validate the atomic model of the ligand as experimental data can often be scarce. The ligand model must be validated against both the primary experimental data and the local environment, specifically: (1) the primary evidence in the form of the electron density, (2) examined for reasonable stereochemistry, and (3) the chemical plausibility of the binding interactions must be inspected. Tools that assist the researcher in the validation process are presented.

The N14 anti-afamin antibody Fab: a rare VL1 CDR glycosylation, crystallographic re-sequencing, molecular plasticity and conservative versus enthusiastic modelling

The monoclonal antibody N14 is used as a detection antibody in ELISA kits for the human glycoprotein afamin, a member of the albumin family, which has recently gained interest in the capture and stabilization of Wnt signalling proteins, and for its role in metabolic syndrome and papillary thyroid carcinoma. As a rare occurrence, the N14 Fab is N-glycosylated at Asn26L at the onset of the VL1 antigen-binding loop, with the α-1-6 core fucosylated complex glycan facing out of the L1 complementarity-determining region. The crystal structures of two non-apparent (pseudo) isomorphous crystals of the N14 Fab were analyzed, which differ significantly in the elbow angles, thereby cautioning against the overinterpretation of domain movements upon antigen binding. In addition, the map quality at 1.9 Å resolution was sufficient to crystallographically re-sequence the variable VL and VH domains and to detect discrepancies in the hybridoma-derived sequence. Finally, a conservatively refined parsimonious model is presented and its statistics are compared with those from a less conservatively built model that has been modelled more enthusiastically. Improvements to the PDB validation reports affecting ligands, clashscore and buried surface calculations are suggested.

Correcting the record of structural publications requires joint effort of the community and journal editors

Seriously flawed and even fictional models of biomolecular crystal structures, although rare, still persist in the record of structural repositories and databases. The ensuing problems of database contamination and persistence of publications based on incorrect structure models must be effectively addressed. The burden cannot be simply left to the critical voices who take the effort to contribute dissenting comments that are mostly ignored. The entire structural biology community, and particularly the journal editors who exercise significant power in this respect, must engage in a constructive dialog lest structural biology lose its credibility as an evidence-based empirical science.

Protein stability: a crystallographer's perspective

Protein stability is a topic of major interest for the biotechnology, pharmaceutical and food industries, in addition to being a daily consideration for academic researchers studying proteins. An understanding of protein stability is essential for optimizing the expression, purification, formulation, storage and structural studies of proteins. In this review, discussion will focus on factors affecting protein stability, on a somewhat practical level, particularly from the view of a protein crystallographer. The differences between protein conformational stability and protein compositional stability will be discussed, along with a brief introduction to key methods useful for analyzing protein stability. Finally, tactics for addressing protein-stability issues during protein expression, purification and crystallization will be discussed.

Only seeing is believing - the power of evidence and reason

Biomolecular crystallography is a mature science that provides an instructive example for modern inductive reasoning as a model for Bayesian epistemology in empirical science. Fundamental scientific epistemology requires that a strong claim is supported by strong and convincing proof. Biomolecular crystallography, based on solid foundations of rich experimental data and extensive prior knowledge provides a prime example for modern, evidence based reasoning that strongly relies on assessments of plausibility based on prior knowledge while at the same time constantly delivering some of the most novel and exciting results based on new experimental evidence. As a consequence of the solid underlying physical principles and its mathematical rigor, crystallography as a mature science could be almost fool proof - were it not for the human element.

The solvent component of macromolecular crystals

The mother liquor from which a biomolecular crystal is grown will contain water, buffer molecules, native ligands and cofactors, crystallization precipitants and additives, various metal ions, and often small-molecule ligands or inhibitors. On average, about half the volume of a biomolecular crystal consists of this mother liquor, whose components form the disordered bulk solvent. Its scattering contributions can be exploited in initial phasing and must be included in crystal structure refinement as a bulk-solvent model. Concomitantly, distinct electron density originating from ordered solvent components must be correctly identified and represented as part of the atomic crystal structure model. Herein, are reviewed (i) probabilistic bulk-solvent content estimates, (ii) the use of bulk-solvent density modification in phase improvement, (iii) bulk-solvent models and refinement of bulk-solvent contributions and (iv) modelling and validation of ordered solvent constituents. A brief summary is provided of current tools for bulk-solvent analysis and refinement, as well as of modelling, refinement and analysis of ordered solvent components, including small-molecule ligands.

Origin and use of crystallization phase diagrams

Crystallization phase diagrams are frequently used to conceptualize the phase relations and also the processes taking place during the crystallization of macromolecules. While a great deal of freedom is given in crystallization phase diagrams owing to a lack of specific knowledge about the actual phase boundaries and phase equilibria, crucial fundamental features of phase diagrams can be derived from thermodynamic first principles. Consequently, there are limits to what can be reasonably displayed in a phase diagram, and imagination may start to conflict with thermodynamic realities. Here, the commonly used `crystallization phase diagrams' are derived from thermodynamic excess properties and their limitations and appropriate use is discussed.

Models of protein-ligand crystal structures: trust, but verify

X-ray crystallography provides the most accurate models of protein-ligand structures. These models serve as the foundation of many computational methods including structure prediction, molecular modelling, and structure-based drug design. The success of these computational methods ultimately depends on the quality of the underlying protein-ligand models. X-ray crystallography offers the unparalleled advantage of a clear mathematical formalism relating the experimental data to the protein-ligand model. In the case of X-ray crystallography, the primary experimental evidence is the electron density of the molecules forming the crystal. The first step in the generation of an accurate and precise crystallographic model is the interpretation of the electron density of the crystal, typically carried out by construction of an atomic model. The atomic model must then be validated for fit to the experimental electron density and also for agreement with prior expectations of stereochemistry. Stringent validation of protein-ligand models has become possible as a result of the mandatory deposition of primary diffraction data, and many computational tools are now available to aid in the validation process. Validation of protein-ligand complexes has revealed some instances of overenthusiastic interpretation of ligand density. Fundamental concepts and metrics of protein-ligand quality validation are discussed and we highlight software tools to assist in this process. It is essential that end users select high quality protein-ligand models for their computational and biological studies, and we provide an overview of how this can be achieved.

Cleaning protocols for crystallization robots: preventing protease contamination

The protease in the commonly used commercial low-foam enzyme cleaner Zymit cannot be completely blocked by EDTA, a widely used inhibitor of metalloproteases, at concentrations of up to 5 mM. Severe protein degradation was observed in crystallization drops after EDTA-containing wash steps unless residual Zymit protease was removed with NaOH at a concentration of at least 0.1 M. Wash steps with 0.1% SDS were also ineffective in completely removing the remaining Zymit activity. Protocols including wash steps with at least 0.1 M NaOH, as for example specified in the original ZENM protocol, are recommended to completely deactivate Zymit protease activity.

Expression and purification of human Afamin for structure/function analysis

Protein glycosylation plays an important role in protein stability, folding, and secretion but presents a major challenge for protein crystallization. Crystallization of highly glycosylated proteins is often difficult because of conformational and chemical inhomogeneity of the glycan decorations. Therefore, it is almost always necessary to modify the material to obtain a conformational homogenous protein that can crystallize. (1) We have explored several avenues in the case of the human 87 kDa glycoprotein afamin. Afamin (AFM), a member of the albumin gene family, is mainly expressed in the liver and secreted into the bloodstream. (2) Elevated afamin plasma concentrations are associated with major diseases such as metabolic syndrome and cancer;(3) however, pathophysiological functions are largely unknown. Therefore, we are pursuing the crystal structure of various forms of recombinantly expressed human afamin (rhAFM) for structure guided exploration and analysis of its function. Multiple variants of rhAFM are pursued: 1) fully glycosylated wild-type rhAFM (expressed in CHO cell lines); 2) rhAFM complexed with Fab fragments of two anti-AFM mAbs, 3) enzymatic deglycosylation of rhAFM with PGNaseF, 4) partially glycosylated rhAFM (expressed in glycosylation-deficient Lec1-CHO cells); and 5) glycosylation-free rhAFM, obtained from HEK293 cells virally transfected with a cDNA mutant lacking all 5 glycosylation sites by replacement of ASN with ASP. Yields of up to 2 mg/mL glycosilation free mutant rhAFM in HEK273 cells have been comparable to native rhAFM. C-terminal His6-tagged rhAFM was captured by Ni-IMAC from serum-free cell culture supernatants. All variants and Fab-AFM complexes were polished via SEC yielding pure products per SDS-PAGE and immunoblot analysis. Crystals have been obtained from Fab fragments and crystalline spherulites which are useful for microseeding from Fab-AFM complexes.

The human intellect is the source of its own problems: Ligands of fancy

Fundamental scientific epistemology requires that a strong claim is supported by strong and convincing proof. As an example, the proposition of a ligand bound to a target protein in a precise conformation and pose presents a very strong claim, and confirming (positive omit difference) electron density will provide the correspondingly strong experimental evidence. A survey of ligand structure models has revealed that in an unexpectedly large number of ligand structures, the required electron density is not present or does not sufficiently support the proposed ligand pose. Upon detailed analysis, it emerged that the origin of such fanciful models lies in the simple neglect of the most basic fundamentals of scientific epistemology, which appears not to be formally taught in some science curricula. A brief introduction into the importance of evidence and its balance with prior expectations in a Bayesian system of empirical reasoning on hand of protein-ligand complex structure examples is therefore provided for young and aspiring scientists. It particular affects early career researchers when fictitious models intended to support bio-medically relevant hypotheses delay the progress of science by unsupported claims: grants cannot be funded when they contradict models believed to be true, and valuable taxpayer money can be squandered trying to pursue science based on false premises. Poor and at minimum self-deceptive work threatens to become systemic and accepted over the course of time unless young researches take full ownership and responsibility for their exciting and important work and resist any postmodern relativism threatening to erode the credibility of their profession.

Ten years of probabilistic estimates of biocrystal solvent content: new insights via nonparametric kernel density estimate

The probabilistic estimate of the solvent content (Matthews probability) was first introduced in 2003. Given that the Matthews probability is based on prior information, revisiting the empirical foundation of this widely used solvent-content estimate is appropriate. The parameter set for the original Matthews probability distribution function employed in MATTPROB has been updated after ten years of rapid PDB growth. A new nonparametric kernel density estimator has been implemented to calculate the Matthews probabilities directly from empirical solvent-content data, thus avoiding the need to revise the multiple parameters of the original binned empirical fit function. The influence and dependency of other possible parameters determining the solvent content of protein crystals have been examined. Detailed analysis showed that resolution is the primary and dominating model parameter correlated with solvent content. Modifications of protein specific density for low molecular weight have no practical effect, and there is no correlation with oligomerization state. A weak, and in practice irrelevant, dependency on symmetry and molecular weight is present, but cannot be satisfactorily explained by simple linear or categorical models. The Bayesian argument that the observed resolution represents only a lower limit for the true diffraction potential of the crystal is maintained. The new kernel density estimator is implemented as the primary option in the MATTPROB web application at http://www.ruppweb.org/mattprob/.

Avoidable errors in deposited macromolecular structures: an impediment to efficient data mining

Whereas the vast majority of the more than 85 000 crystal structures of macromolecules currently deposited in the Protein Data Bank are of high quality, some suffer from a variety of imperfections. Although this fact has been pointed out in the past, it is still worth periodic updates so that the metadata obtained by global analysis of the available crystal structures, as well as the utilization of the individual structures for tasks such as drug design, should be based on only the most reliable data. Here, selected abnormal deposited structures have been analysed based on the Bayesian reasoning that the correctness of a model must be judged against both the primary evidence as well as prior knowledge. These structures, as well as information gained from the corresponding publications (if available), have emphasized some of the most prevalent types of common problems. The errors are often perfect illustrations of the nature of human cognition, which is frequently influenced by preconceptions that may lead to fanciful results in the absence of proper validation. Common errors can be traced to negligence and a lack of rigorous verification of the models against electron density, creation of non-parsimonious models, generation of improbable numbers, application of incorrect symmetry, illogical presentation of the results, or violation of the rules of chemistry and physics. Paying more attention to such problems, not only in the final validation stages but during the structure-determination process as well, is necessary not only in order to maintain the highest possible quality of the structural repositories and databases but most of all to provide a solid basis for subsequent studies, including large-scale data-mining projects. For many scientists PDB deposition is a rather infrequent event, so the need for proper training and supervision is emphasized, as well as the need for constant alertness of reason and critical judgment as absolutely necessary safeguarding measures against such problems. Ways of identifying more problematic structures are suggested so that their users may be properly alerted to their possible shortcomings.

Approaches to automated protein crystal harvesting

The harvesting of protein crystals is almost always a necessary step in the determination of a protein structure using X-ray crystallographic techniques. However, protein crystals are usually fragile and susceptible to damage during the harvesting process. For this reason, protein crystal harvesting is the single step that remains entirely dependent on skilled human intervention. Automation has been implemented in the majority of other stages of the structure-determination pipeline, including cloning, expression, purification, crystallization and data collection. The gap in automation between crystallization and data collection results in a bottleneck in throughput and presents unfortunate opportunities for crystal damage. Several automated protein crystal harvesting systems have been developed, including systems utilizing microcapillaries, microtools, microgrippers, acoustic droplet ejection and optical traps. However, these systems have yet to be commonly deployed in the majority of crystallography laboratories owing to a variety of technical and cost-related issues. Automation of protein crystal harvesting remains essential for harnessing the full benefits of fourth-generation synchrotrons, free-electron lasers and microfocus beamlines. Furthermore, automation of protein crystal harvesting offers several benefits when compared with traditional manual approaches, including the ability to harvest microcrystals, improved flash-cooling procedures and increased throughput.

Visualizing ligand molecules in Twilight electron density

Three-dimensional models of protein structures determined by X-ray crystallography are based on the interpretation of experimentally derived electron-density maps. The real-space correlation coefficient (RSCC) provides an easily comprehensible, objective measure of the residue-based fit of atom coordinates to electron density. Among protein structure models, protein-ligand complexes are of special interest, given their contribution to understanding the molecular underpinnings of biological activity and to drug design. For consumers of such models, it is not trivial to determine the degree to which ligand-structure modelling is biased by subjective electron-density interpretation. A standalone script, Twilight, is presented for the analysis, visualization and annotation of a pre-filtered set of 2815 protein-ligand complexes deposited with the PDB as of 15 January 2012 with ligand RSCC values that are below a threshold of 0.6. It also provides simplified access to the visualization of any protein-ligand complex available from the PDB and annotated by the Uppsala Electron Density Server. The script runs on various platforms and is available for download at http://www.ruppweb.org/twilight/.

Techniques, tools and best practices for ligand electron-density analysis and results from their application to deposited crystal structures

As a result of substantial instrumental automation and the continuing improvement of software, crystallographic studies of biomolecules are conducted by non-experts in increasing numbers. While improved validation almost ensures that major mistakes in the protein part of structure models are exceedingly rare, in ligand-protein complex structures, which in general are most interesting to the scientist, ambiguous ligand electron density is often difficult to interpret and the modelled ligands are generally more difficult to properly validate. Here, (i) the primary technical reasons and potential human factors leading to problems in ligand structure models are presented; (ii) the most common categories of building errors or overinterpretation are classified; (iii) a few instructive and specific examples are discussed in detail, including an electron-density-based analysis of ligand structures that do not contain any ligands; (iv) means of avoiding such mistakes are suggested and the implications for database validity are discussed and (v) a user-friendly software tool that allows non-expert users to conveniently inspect ligand density is provided.

Model building, refinement and validation

An introduction to the proceedings of the CCP4 Study Weekend held at the University of Warwick on the 6–7 January 2011.

Detection and analysis of unusual features in the structural model and structure-factor data of a birch pollen allergen

Physically improbable features in the model of the birch pollen structure Bet v 1d (PDB entry 3k78) are faithfully reproduced in electron density generated with the deposited structure factors, but these structure factors themselves exhibit properties that are characteristic of data calculated from a simple model and are inconsistent with the data and error model obtained through experimental measurements. The refinement of the 3k78 model against these structure factors leads to an isomorphous structure different from the deposited model with an implausibly small R value (0.019). The abnormal refinement is compared with normal refinement of an isomorphous variant structure of Bet v 1l (PDB entry 1fm4). A variety of analytical tools, including the application of Diederichs plots, Rσ plots and bulk-solvent analysis are discussed as promising aids in validation. The examination of the Bet v 1d structure also cautions against the practice of indicating poorly defined protein chain residues through zero occupancies. The recommendation to preserve diffraction images is amplified.

First experiences with semi-autonomous robotic harvesting of protein crystals

The demonstration unit of the Universal Micromanipulation Robot (UMR) capable of semi-autonomous protein crystal harvesting has been tested and evaluated by independent users. We report the status and capabilities of the present unit scheduled for deployment in a high-throughput protein crystallization center. We discuss operational aspects as well as novel features such as micro-crystal handling and drip-cryoprotection, and we extrapolate towards the design of a fully autonomous, integrated system capable of reliable crystal harvesting. The positive to enthusiastic feedback from the participants in an evaluation workshop indicates that genuine demand exists and the effort and resources to develop autonomous protein crystal harvesting robotics are justified.

Structure of Rv1848 (UreA), the Mycobacterium tuberculosis urease gamma subunit

The crystal structure of the urease gamma subunit (UreA) from Mycobacterium tuberculosis, Rv1848, has been determined at 1.8 A resolution. The asymmetric unit contains three copies of Rv1848 arranged into a homotrimer that is similar to the UreA trimer in the structure of urease from Klebsiella aerogenes. Small-angle X-ray scattering experiments indicate that the Rv1848 protein also forms trimers in solution. The observed homotrimer and the organization of urease genes within the M. tuberculosis genome suggest that M. tuberculosis urease has the (alphabetagamma)(3) composition observed for other bacterial ureases. The gamma subunit may be of primary importance for the formation of the urease quaternary structure.