Trinuclear copper biocatalytic center forms an active site of thiocyanate dehydrogenase.

Biocatalytic copper centers are generally involved in the activation and reduction of dioxygen, with only few exceptions known. Here we report the discovery and characterization of a previously undescribed copper center that forms the active site of a copper-containing enzyme thiocyanate dehydrogenase (suggested EC 1.8.2.7) that was purified from the haloalkaliphilic sulfur-oxidizing bacterium of the genus Thioalkalivibrio ubiquitous in saline alkaline soda lakes. The copper cluster is formed by three copper ions located at the corners of a near-isosceles triangle and facilitates a direct thiocyanate conversion into cyanate, elemental sulfur, and two reducing equivalents without involvement of molecular oxygen. A molecular mechanism of catalysis is suggested based on high-resolution three-dimensional structures, electron paramagnetic resonance (EPR) spectroscopy, quantum mechanics/molecular mechanics (QM/MM) simulations, kinetic studies, and the results of site-directed mutagenesis.

Association of Coding Variants in Hydroxysteroid 17-beta Dehydrogenase 14 (HSD17B14) with Reduced Progression to End Stage Kidney Disease in Type 1 Diabetes.

BACKGROUND: Rare variants in gene coding regions likely have a greater impact on disease-related phenotypes than common variants through disruption of their encoded protein. We searched for rare variants associated with onset of ESKD in individuals with type 1 diabetes at advanced kidney disease stage. METHODS: Gene-based exome array analyses of 15,449 genes in five large incidence cohorts of individuals with type 1 diabetes and proteinuria were analyzed for survival time to ESKD, testing the top gene in a sixth cohort (n=2372/1115 events all cohorts) and replicating in two retrospective case-control studies (n=1072 cases, 752 controls). Deep resequencing of the top associated gene in five cohorts confirmed the findings. We performed immunohistochemistry and gene expression experiments in human control and diseased cells, and in mouse ischemia reperfusion and aristolochic acid nephropathy models. RESULTS: Protein coding variants in the hydroxysteroid 17-ß dehydrogenase 14 gene (HSD17B14), predicted to affect protein structure, had a net protective effect against development of ESKD at exome-wide significance (n=4196; P value=3.3 × 10-7). The HSD17B14 gene and encoded enzyme were robustly expressed in healthy human kidney, maximally in proximal tubular cells. Paradoxically, gene and protein expression were attenuated in human diabetic proximal tubules and in mouse kidney injury models. Expressed HSD17B14 gene and protein levels remained low without recovery after 21 days in a murine ischemic reperfusion injury model. Decreased gene expression was found in other CKD-associated renal pathologies. CONCLUSIONS: HSD17B14 gene is mechanistically involved in diabetic kidney disease. The encoded sex steroid enzyme is a druggable target, potentially opening a new avenue for therapeutic development.

Synchrotron Radiation as a Tool for Macromolecular X-Ray Crystallography: a XXI Century Perspective.

Intense X-rays available at powerful synchrotron beamlines provide macromolecular crystallographers with an incomparable tool for investigating biological phenomena on an atomic scale. The resulting insights into the mechanism's underlying biological processes have played an essential role and shaped biomedical sciences during the last 30 years, considered the "golden age" of structural biology. In this review, we analyze selected aspects of the impact of synchrotron radiation on structural biology. Synchrotron beamlines have been used to determine over 70% of all macromolecular structures deposited into the Protein Data Bank (PDB). These structures were deposited by over 13,000 different research groups. Interestingly, despite the impressive advances in synchrotron technologies, the median resolution of macromolecular structures determined using synchrotrons has remained constant throughout the last 30 years, at about 2 Å. Similarly, the median times from the data collection to the deposition and release have not changed significantly. We describe challenges to reproducibility related to recording all relevant data and metadata during the synchrotron experiments, including diffraction images. Finally, we discuss some of the recent opinions suggesting a diminishing importance of X-ray crystallography due to impressive advances in Cryo-EM and theoretical modeling. We believe that synchrotrons of the future will increasingly evolve towards a life science center model, where X-ray crystallography, Cryo-EM, and other experimental and computational resources and knowledge are encompassed within a versatile research facility. The recent response of crystallographers to the COVID-19 pandemic suggests that X-ray crystallography conducted at synchrotron beamlines will continue to play an essential role in structural biology and drug discovery for years to come.

Automatic recognition of ligands in electron density by machine learning.

Motivation: The correct identification of ligands in crystal structures of protein complexes is the cornerstone of structure-guided drug design. However, cognitive bias can sometimes mislead investigators into modeling fictitious compounds without solid support from the electron density maps. Ligand identification can be aided by automatic methods, but existing approaches are based on time-consuming iterative fitting. Results: Here we report a new machine learning algorithm called CheckMyBlob that identifies ligands from experimental electron density maps. In benchmark tests on portfolios of up to 219 931 ligand binding sites containing the 200 most popular ligands found in the Protein Data Bank, CheckMyBlob markedly outperforms the existing automatic methods for ligand identification, in some cases doubling the recognition rates, while requiring significantly less time. Our work shows that machine learning can improve the automation of structure modeling and significantly accelerate the drug screening process of macromolecule-ligand complexes. Availability and implementation: Code and data are available on GitHub at https://github.com/dabrze/CheckMyBlob. Supplementary information: Supplementary data are available at Bioinformatics online.

Correction to: Classification, substrate specificity and structural features of D-2-hydroxyacid dehydrogenases: 2HADH knowledgebase.

Following publication of the original article [1], we have been notified that some important information was omitted by the authors from the Competing interests section. The declaration should read as below.

A close look onto structural models and primary ligands of metallo-ß-lactamases.

ß-Lactamases are hydrolytic enzymes capable of opening the ß-lactam ring of antibiotics such as penicillin, thus endowing the bacteria that produce them with antibiotic resistance. Of particular medical concern are metallo-ß-lactamases (MBLs), with an active site built around coordinated Zn cations. MBLs are pan-reactive enzymes that can break down almost all classes of ß-lactams, including such last-resort antibiotics as carbapenems. They are not only broad-spectrum-reactive but are often plasmid-borne (e.g., the New Delhi enzyme, NDM), and can spread horizontally even among unrelated bacteria. Acquired MBLs are encoded by mobile genetic elements, which often include other resistance genes, making the microbiological situation particularly alarming. There is an urgent need to develop MBL inhibitors in order to rescue our antibiotic armory. A number of such efforts have been undertaken, most notably using the 3D structures of various MBLs as drug-design targets. Structure-guided drug discovery depends on the quality of the structures that are collected in the Protein Data Bank (PDB) and on the consistency of the information in dedicated ß-lactamase databases. We conducted a careful review of the crystal structures of class B ß-lactamases, concluding that the quality of these structures varies widely, especially in the regions where small molecules interact with the macromolecules. In a number of examples the interpretation of the bound ligands (e.g., inhibitors, substrate/product analogs) is doubtful or even incorrect, and it appears that in some cases the modeling of ligands was not supported by electron density. For ten MBL structures, alternative interpretations of the original diffraction data could be proposed and the new models have been deposited in the PDB. In four cases, these models, prepared jointly with the authors of the original depositions, superseded the previous deposits. This review emphasizes the importance of critical assessment of structural models describing key drug design targets at the level of the raw experimental data. Since the structures reviewed here are the basis for ongoing design of new MBL inhibitors, it is important to identify and correct the problems with ambiguous crystallographic interpretations, thus enhancing reproducibility in this highly medically relevant area.

Structural, Biochemical, and Evolutionary Characterizations of Glyoxylate/Hydroxypyruvate Reductases Show Their Division into Two Distinct Subfamilies.

The d-2-hydroxyacid dehydrogenase (2HADH) family illustrates a complex evolutionary history with multiple lateral gene transfers and gene duplications and losses. As a result, the exact functional annotation of individual members can be extrapolated to a very limited extent. Here, we revise the previous simplified view on the classification of the 2HADH family; specifically, we show that the previously delineated glyoxylate/hydroxypyruvate reductase (GHPR) subfamily consists of two evolutionary separated GHRA and GHRB subfamilies. We compare two representatives of these subfamilies from Sinorhizobium meliloti (SmGhrA and SmGhrB), employing a combination of biochemical, structural, and bioinformatics approaches. Our kinetic results show that both enzymes reduce several 2-ketocarboxylic acids with overlapping, but not equivalent, substrate preferences. SmGhrA and SmGhrB show highest activity with glyoxylate and hydroxypyruvate, respectively; in addition, only SmGhrB reduces 2-keto-d-gluconate, and only SmGhrA reduces pyruvate (with low efficiency). We present nine crystal structures of both enzymes in apo forms and in complexes with cofactors and substrates/substrate analogues. In particular, we determined a crystal structure of SmGhrB with 2-keto-d-gluconate, which is the biggest substrate cocrystallized with a 2HADH member. The structures reveal significant differences between SmGhrA and SmGhrB, both in the overall structure and within the substrate-binding pocket, offering insight into the molecular basis for the observed substrate preferences and subfamily differences. In addition, we provide an overview of all GHRA and GHRB structures complexed with a ligand in the active site.

Classification, substrate specificity and structural features of D-2-hydroxyacid dehydrogenases: 2HADH knowledgebase.

BACKGROUND: The family of D-isomer specific 2-hydroxyacid dehydrogenases (2HADHs) contains a wide range of oxidoreductases with various metabolic roles as well as biotechnological applications. Despite a vast amount of biochemical and structural data for various representatives of the family, the long and complex evolution and broad sequence diversity hinder functional annotations for uncharacterized members. RESULTS: We report an in-depth phylogenetic analysis, followed by mapping of available biochemical and structural data on the reconstructed phylogenetic tree. The analysis suggests that some subfamilies comprising enzymes with similar yet broad substrate specificity profiles diverged early in the evolution of 2HADHs. Based on the phylogenetic tree, we present a revised classification of the family that comprises 22 subfamilies, including 13 new subfamilies not studied biochemically. We summarize characteristics of the nine biochemically studied subfamilies by aggregating all available sequence, biochemical, and structural data, providing comprehensive descriptions of the active site, cofactor-binding residues, and potential roles of specific structural regions in substrate recognition. In addition, we concisely present our analysis as an online 2HADH enzymes knowledgebase. CONCLUSIONS: The knowledgebase enables navigation over the 2HADHs classification, search through collected data, and functional predictions of uncharacterized 2HADHs. Future characterization of the new subfamilies may result in discoveries of enzymes with novel metabolic roles and with properties beneficial for biotechnological applications.

A transient post-translational modification of active site cysteine alters binding properties of the parkinsonism protein DJ-1.

Mutations in the human protein DJ-1 cause early onset of Parkinson's disease. A reactive cysteine residue (Cys106) of DJ-1 is crucial for its protective function, although the underlying mechanisms are unclear. Here we show that a fraction of bacterially expressed polyhistidine-tagged human DJ-1 could not be eluted from a Ni-nitrilotriacetate (Ni-NTA) column with 150 mM imidazole. This unusually tight binding was accompanied by the appearance of blue violet color on the Ni-NTA column. We demonstrate by X-ray crystallography that Cys106 is carboxymethylated in a fraction of DJ-1 tightly bound to Ni-NTA and that the replacement of Cys106 by serine abrogates the tight binding and the appearance of blue violet color. However, carboxymethylation of purified DJ-1 is insufficient to confer the tight binding to Ni-NTA. Moreover, when eluted protein was re-applied to the Ni-NTA column, no tight binding was observed, indicating that the formation of high affinity complex with Ni-NTA depends on a transient modification of Cys106 that transforms into a Cys106-carboxymethyl adduct upon elution from Ni-NTA. We conclude that an unknown metabolite reacts with Cys106 of DJ-1 to result in a transient post-translational modification. This modification is distinct from simple oxidation to sulfinic or sulfenic acids and confers altered binding properties to DJ-1 suggesting that it could serve as a signal for sensing oxidant stress.

Refining the macromolecular model - achieving the best agreement with the data from X-ray diffraction experiment.

Refinement of macromolecular X-ray crystal structures involves using complex software with hundreds of different settings. The complexity of underlying concepts and the sheer amount sof instructions may make it difficult for less experienced crystallographers to achieve optimal results in their refinements. This tutorial review offers guidelines for choosing the best settings for the reciprocal-space refinement of macromolecular models and provides practical tips for manual model correction. To help aspiring crystallographers navigate the process, some of the most practically important concepts of protein structure refinement are described. Among the topics covered are the use and purpose of R-free, geometrical restraints, restraints on atomic displacement parameters (ADPs), refinement weights, various parametrizations of ADPs (full anisotropic refinement and TLS), and omit maps. We also give practical tips for manual model correction in Coot, modelling of side-chains with poor or missing density, and ligand identification, fitting, and refinement.

Magnesium-binding architectures in RNA crystal structures: validation, binding preferences, classification and motif detection.

The ubiquitous presence of magnesium ions in RNA has long been recognized as a key factor governing RNA folding, and is crucial for many diverse functions of RNA molecules. In this work, Mg(2+)-binding architectures in RNA were systematically studied using a database of RNA crystal structures from the Protein Data Bank (PDB). Due to the abundance of poorly modeled or incorrectly identified Mg(2+) ions, the set of all sites was comprehensively validated and filtered to identify a benchmark dataset of 15 334 'reliable' RNA-bound Mg(2+) sites. The normalized frequencies by which specific RNA atoms coordinate Mg(2+) were derived for both the inner and outer coordination spheres. A hierarchical classification system of Mg(2+) sites in RNA structures was designed and applied to the benchmark dataset, yielding a set of 41 types of inner-sphere and 95 types of outer-sphere coordinating patterns. This classification system has also been applied to describe six previously reported Mg(2+)-binding motifs and detect them in new RNA structures. Investigation of the most populous site types resulted in the identification of seven novel Mg(2+)-binding motifs, and all RNA structures in the PDB were screened for the presence of these motifs.

NADP-Dependent Aldehyde Dehydrogenase from Archaeon Pyrobaculum sp.1860: Structural and Functional Features.

We present the functional and structural characterization of the first archaeal thermostable NADP-dependent aldehyde dehydrogenase AlDHPyr1147. In vitro, AlDHPyr1147 catalyzes the irreversible oxidation of short aliphatic aldehydes at 60-85°Ð¡, and the affinity of AlDHPyr1147 to the NADP+ at 60°Ð¡ is comparable to that for mesophilic analogues at 25°Ð¡. We determined the structures of the apo form of AlDHPyr1147 (3.04 Å resolution), three binary complexes with the coenzyme (1.90, 2.06, and 2.19 Å), and the ternary complex with the coenzyme and isobutyraldehyde as a substrate (2.66 Å). The nicotinamide moiety of the coenzyme is disordered in two binary complexes, while it is ordered in the ternary complex, as well as in the binary complex obtained after additional soaking with the substrate. AlDHPyr1147 structures demonstrate the strengthening of the dimeric contact (as compared with the analogues) and the concerted conformational flexibility of catalytic Cys287 and Glu253, as well as Leu254 and the nicotinamide moiety of the coenzyme. A comparison of the active sites of AlDHPyr1147 and dehydrogenases characterized earlier suggests that proton relay systems, which were previously proposed for dehydrogenases of this family, are blocked in AlDHPyr1147, and the proton release in the latter can occur through the substrate channel.

Structural and biochemical characterisation of Co2+-binding sites on serum albumins and their interplay with fatty acids.

Serum albumin-Co2+ interactions are of clinical importance. They play a role in mediating the physiological effects associated with cobalt toxicity and are central to the albumin cobalt binding (ACB) assay for diagnosis of myocardial ischemia. To further understand these processes, a deeper understanding of albumin-Co2+ interactions is required. Here, we present the first crystallographic structures of human serum albumin (HSA; three structures) and equine serum albumin (ESA; one structure) in complex with Co2+. Amongst a total of sixteen sites bearing a cobalt ion across the structures, two locations were prominent, and they relate to metal-binding sites A and B. Site-directed mutagenesis and isothermal titration calorimetry (ITC) were employed to characterise sites on HSA. The results indicate that His9 and His67 contribute to the primary (putatively corresponding to site B) and secondary Co2+-binding sites (site A), respectively. The presence of additional multiple weak-affinity Co2+ binding sites on HSA was also supported by ITC studies. Furthermore, addition of 5 molar equivalents of the non-esterified fatty acid palmitate (C16:0) reduced the Co2+-binding affinity at both sites A and B. The presence of bound myristate (C14:0) in the HSA crystal structures provided insight into the fatty acid-mediated structural changes that diminish the affinity of the protein toward Co2+. Together, these data provide further support for the idea that ischemia-modified albumin corresponds to albumin with excessive fatty-acid loading. Collectively, our findings provide a comprehensive understanding of the molecular underpinnings governing Co2+ binding to serum albumin.

Organism-specific differences in the binding of ketoprofen to serum albumin.

Serum albumin is a circulatory transport protein that has a highly conserved sequence and structure across mammalian organisms. Its ligand-binding properties are of importance as albumin regulates the pharmacokinetics of many drugs. Due to the high degree of structural conservation between mammalian albumins, nonhuman albumins such as bovine serum albumin or animal models are often used to understand human albumin-drug interactions. Ketoprofen is a popular nonsteroidal anti-inflammatory drug that is transported by albumin. Here, it is revealed that ketoprofen exhibits different binding-site preferences when interacting with human serum albumin compared with other mammalian albumins, despite the conservation of binding sites across species. The reasons for the observed differences were explored, including identifying ketoprofen binding determinants at specific sites and the influence of fatty acids and other ligands on drug binding. The presented results reveal that the drug-binding properties of albumins cannot easily be predicted based only on a complex of albumin from another organism and the conservation of drug sites between species. This work shows that understanding organism-dependent differences is essential for assessing the suitability of particular albumins for structural or biochemical studies.

New ligand-binding sites identified in the crystal structures of ß-lactoglobulin complexes with desipramine.

The homodimeric ß-lactoglobulin belongs to the lipocalin family of proteins that transport a wide range of hydrophobic molecules and can be modified by mutagenesis to develop specificity for novel groups of ligands. In this work, new lactoglobulin variants, FAF (I56F/L39A/M107F) and FAW (I56F/L39A/M107W), were produced and their interactions with the tricyclic drug desipramine (DSM) were studied using X-ray crystallography, calorimetry (ITC) and circular dichroism (CD). The ITC and CD data showed micromolar affinity of the mutants for DSM and interactions according to the classical one-site binding model. However, the crystal structures unambiguously showed that the FAF and FAW dimers are capable of binding DSM not only inside the ß-barrel as expected, but also at the dimer interface and at the entrance to the binding pocket. The presented high-resolution crystal structures therefore provide important evidence of the existence of alternative ligand-binding sites in the ß-lactoglobulin molecule. Analysis of the crystal structures highlighted the importance of shape complementarity for ligand recognition and selectivity. The binding sites identified in the crystal structures of the FAF-DSM and FAW-DSM complexes together with data from the existing literature are used to establish a systematic classification of the ligand-binding sites in the ß-lactoglobulin molecule.

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.

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.

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.

State-of-the-Art Data Management: Improving the Reproducibility, Consistency, and Traceability of Structural Biology and in Vitro Biochemical Experiments.

Efficient and comprehensive data management is an indispensable component of modern scientific research and requires effective tools for all but the most trivial experiments. The LabDB system developed and used in our laboratory was originally designed to track the progress of a structure determination pipeline in several large National Institutes of Health (NIH) projects. While initially designed for structural biology experiments, its modular nature makes it easily applied in laboratories of various sizes in many experimental fields. Over many years, LabDB has transformed into a sophisticated system integrating a range of biochemical, biophysical, and crystallographic experimental data, which harvests data both directly from laboratory instruments and through human input via a web interface. The core module of the system handles many types of universal laboratory management data, such as laboratory personnel, chemical inventories, storage locations, and custom stock solutions. LabDB also tracks various biochemical experiments, including spectrophotometric and fluorescent assays, thermal shift assays, isothermal titration calorimetry experiments, and more. LabDB has been used to manage data for experiments that resulted in over 1200 deposits to the Protein Data Bank (PDB); the system is currently used by the Center for Structural Genomics of Infectious Diseases (CSGID) and several large laboratories. This chapter also provides examples of data mining analyses and warnings about incomplete and inconsistent experimental data. These features, together with its capabilities for detailed tracking, analysis, and auditing of experimental data, make the described system uniquely suited to inspect potential sources of irreproducibility in life sciences research.