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.

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/ß receptor alpha chain (Ifnar1)-deficient mice and a specific zebrafish model were used to study the implication of the biglycan (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/ß 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.

The Second Methylation in Psilocybin Biosynthesis Is Enabled by a Hydrogen Bonding Network Extending into the Secondary Sphere Surrounding the Methyltransferase Active Site.

The Psilocybe cubensis SAM-dependent methyltransferase, PsiM, catalyzes the last step in the biosynthesis of psilocybin. Likely evolved from monomethylating RNA methyltransferases, PsiM acquired a key amino acid exchange in the secondary sphere of the active site, M247N, which is responsible for its capacity to dimethylate. Two variants, PsiMN247M and PsiMN247A, were generated to further examine the role of Asn247 for mono- and dimethylation in PsiM. Herein, we present the kinetic profiles of both variants and crystal structures at resolutions between 0.9 and 1.0 Å. Each variant was crystallized as a ternary complex with the non-methylated acceptor substrate, norbaeocystin and S-adenosyl-l-homocysteine, and in a second complex with the cofactor analog, sinefungin, and the monomethylated substrate, baeocystin. Consistent with the inability of the variants to catalyze a second methyl transfer, these structures reveal catalytically non-productive conformations and a high level of disorder of the methylamine group of baeocystin. Additionally, both variants exhibit destabilization in the ß5-ß7 sheets and a conserved ß-turn of the core Rossmann fold, causing 20-fold reduced substrate binding and 2-fold lower catalytic efficiency even with norbaeocystin.

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.

Enzymatic Route toward 6-Methylated Baeocystin and Psilocybin.

Psilocybin and its direct precursor baeocystin are indole alkaloids of psychotropic Psilocybe mushrooms. The pharmaceutical interest in psilocybin as a treatment option against depression and anxiety is currently being investigated in advanced clinical trials. Here, we report a biocatalytic route to synthesize 6-methylated psilocybin and baeocystin from 4-hydroxy-6-methyl-l-tryptophan, which was decarboxylated and phosphorylated by the Psilocybe cubensis biosynthesis enzymes PsiD and PsiK. N-Methylation was catalyzed by PsiM. We further present an in silico structural model of PsiM that revealed a well-conserved SAM-binding core along with peripheral nonconserved elements that likely govern substrate preferences.

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.

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.

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.

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/.

Substrate recognition by the 4-hydroxytryptamine kinase PsiK in psilocybin biosynthesis.

Psilocybin, the natural hallucinogen from Psilocybe (magic) mushrooms, is a highly promising drug candidate for the treatment of depression and several other mental health conditions. Biosynthesis of psilocybin from the amino acid l-tryptophan involves four strictly sequential modifications. The third of these, ATP-dependent phosphorylation of the intermediate 4-hydroxytryptamine, is catalysed by PsiK. Here we present a crystallographic analysis and a structure-based mutagenesis study of this kinase, providing insight into its mode of substrate recognition. The results of our work will support future bioengineering efforts aimed at generating variants of psilocybin with enhanced therapeutic properties.

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.

Study of key residues in MERS-CoV and SARS-CoV-2 main proteases for resistance against clinically applied inhibitors nirmatrelvir and ensitrelvir.

The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is an epidemic, zoonotically emerging pathogen initially reported in Saudi Arabia in 2012. MERS-CoV has the potential to mutate or recombine with other coronaviruses, thus acquiring the ability to efficiently spread among humans and become pandemic. Its high mortality rate of up to 35% and the absence of effective targeted therapies call for the development of antiviral drugs for this pathogen. Since the beginning of the SARS-CoV-2 pandemic, extensive research has focused on identifying protease inhibitors for the treatment of SARS-CoV-2. Our intention was therefore to assess whether these protease inhibitors are viable options for combating MERS-CoV. To that end, we used previously established protease assays to quantify inhibition of SARS-CoV-2, MERS-CoV and other main proteases. Nirmatrelvir inhibited several of these proteases, whereas ensitrelvir was less broadly active. To simulate nirmatrelvir's clinical use against MERS-CoV and subsequent resistance development, we applied a safe, surrogate virus-based system. Using the surrogate virus, we previously selected hallmark mutations of SARS-CoV-2-Mpro, such as T21I, M49L, S144A, E166A/K/V and L167F. In the current study, we selected a pool of MERS-CoV-Mpro mutants, characterized the resistance and modelled the steric effect of catalytic site mutants S142G, S142R, S147Y and A171S.

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.

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/.

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.

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.