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.

Recognizing and validating ligands with CheckMyBlob.

Structure-guided drug design depends on the correct identification of ligands in crystal structures of protein complexes. However, the interpretation of the electron density maps is challenging and often burdened with confirmation bias. Ligand identification can be aided by automatic methods such as CheckMyBlob, a machine learning algorithm that learns to generalize ligand descriptions from sets of moieties deposited in the Protein Data Bank. Here, we present the CheckMyBlob web server, a platform that can identify ligands in unmodeled fragments of electron density maps or validate ligands in existing models. The server processes PDB/mmCIF and MTZ files and returns a ranking of 10 most likely ligands for each detected electron density blob along with interactive 3D visualizations. Additionally, for each prediction/validation, a plugin script is generated that enables users to conduct a detailed analysis of the server results in Coot. The CheckMyBlob web server is available at https://checkmyblob.bioreproducibility.org.

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.

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. DATABASE: Validated models of CoV-2 proteins are available in a dedicated, publicly accessible web service https://covid-19.bioreproducibility.org.

3D domain swapping in the TIM barrel of the α subunit of Streptococcus pneumoniae tryptophan synthase.

Tryptophan synthase catalyzes the last two steps of tryptophan biosynthesis in plants, fungi and bacteria. It consists of two protein chains, designated α and ß, encoded by trpA and trpB genes, that function as an αßßα complex. Structural and functional features of tryptophan synthase have been extensively studied, explaining the roles of individual residues in the two active sites in catalysis and allosteric regulation. TrpA serves as a model for protein-folding studies. In 1969, Jackson and Yanofsky observed that the typically monomeric TrpA forms a small population of dimers. Dimerization was postulated to take place through an exchange of structural elements of the monomeric chains, a phenomenon later termed 3D domain swapping. The structural details of the TrpA dimer have remained unknown. Here, the crystal structure of the Streptococcus pneumoniae TrpA homodimer is reported, demonstrating 3D domain swapping in a TIM-barrel fold for the first time. The N-terminal domain comprising the H0-S1-H1-S2 elements is exchanged, while the hinge region corresponds to loop L2 linking strand S2 to helix H2'. The structural elements S2 and L2 carry the catalytic residues Glu52 and Asp63. As the S2 element is part of the swapped domain, the architecture of the catalytic apparatus in the dimer is recreated from two protein chains. The homodimer interface overlaps with the α-ß interface of the tryptophan synthase αßßα heterotetramer, suggesting that the 3D domain-swapped dimer cannot form a complex with the ß subunit. In the crystal, the dimers assemble into a decamer comprising two pentameric rings.

Conformation-dependent restraints for polynucleotides: the sugar moiety.

Stereochemical restraints are commonly used to aid the refinement of macromolecular structures obtained by experimental methods at lower resolution. The standard restraint library for nucleic acids has not been updated for over two decades and needs revision. In this paper, geometrical restraints for nucleic acids sugars are derived using information from high-resolution crystal structures in the Cambridge Structural Database. In contrast to the existing restraints, this work shows that different parts of the sugar moiety form groups of covalent geometry dependent on various chemical and conformational factors, such as the type of ribose or the attached nucleobase, and ring puckering or rotamers of the glycosidic (χ) or side-chain (γ) torsion angles. Moreover, the geometry of the glycosidic link and the endocyclic ribose bond angles are functionally dependent on χ and sugar pucker amplitude (τm), respectively. The proposed restraints have been positively validated against data from the Nucleic Acid Database, compared with an ultrahigh-resolution Z-DNA structure in the Protein Data Bank, and tested by re-refining hundreds of crystal structures in the Protein Data Bank. The conformation-dependent sugar restraints presented in this work are publicly available in REFMAC, PHENIX and SHELXL format through a dedicated RestraintLib web server with an API function.

Accurate geometrical restraints for Watson-Crick base pairs.

Geometrical restraints provide key structural information for the determination of biomolecular structures at lower resolution by experimental methods such as crystallography or cryo-electron microscopy. In this work, restraint targets for nucleic acids bases are derived from three different sources and compared: small-molecule crystal structures in the Cambridge Structural Database (CSD), ultrahigh-resolution structures in the Protein Data Bank (PDB) and quantum-mechanical (QM) calculations. The best parameters are those based on CSD structures. After over two decades, the standard library of Parkinson et al. [(1996), Acta Cryst. D52, 57-64] is still valid, but improvements are possible with the use of the current CSD database. The CSD-derived geometry is fully compatible with Watson-Crick base pairs, as comparisons with QM results for isolated and paired bases clearly show that the CSD targets closely correspond to proper base pairing. While the QM results are capable of distinguishing between single and paired bases, their level of accuracy is, on average, nearly two times lower than for the CSD-derived targets when gauged by root-mean-square deviations from ultrahigh-resolution structures in the PDB. Nevertheless, the accuracy of QM results appears sufficient to provide stereochemical targets for synthetic base pairs where no reliable experimental structural information is available. To enable future tests for this approach, QM calculations are provided for isocytosine, isoguanine and the iCiG base pair.

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.

Data mining of iron(II) and iron(III) bond-valence parameters, and their relevance for macromolecular crystallography.

The bond-valence model is a reliable way to validate assumed oxidation states based on structural data. It has successfully been employed for analyzing metal-binding sites in macromolecule structures. However, inconsistent results for heme-based structures suggest that some widely used bond-valence R0 parameters may need to be adjusted in certain cases. Given the large number of experimental crystal structures gathered since these initial parameters were determined and the similarity of binding sites in organic compounds and macromolecules, the Cambridge Structural Database (CSD) is a valuable resource for refining metal-organic bond-valence parameters. R0 bond-valence parameters for iron(II), iron(III) and other metals have been optimized based on an automated processing of all CSD crystal structures. Almost all R0 bond-valence parameters were reproduced, except for iron-nitrogen bonds, for which distinct R0 parameters were defined for two observed subpopulations, corresponding to low-spin and high-spin states, of iron in both oxidation states. The significance of this data-driven method for parameter discovery, and how the spin state affects the interpretation of heme-containing proteins and iron-binding sites in macromolecular structures, are discussed.

Conformation-dependent restraints for polynucleotides: I. Clustering of the geometry of the phosphodiester group.

The refinement of macromolecular structures is usually aided by prior stereochemical knowledge in the form of geometrical restraints. Such restraints are also used for the flexible sugar-phosphate backbones of nucleic acids. However, recent highly accurate structural studies of DNA suggest that the phosphate bond angles may have inadequate description in the existing stereochemical dictionaries. In this paper, we analyze the bonding deformations of the phosphodiester groups in the Cambridge Structural Database, cluster the studied fragments into six conformation-related categories and propose a revised set of restraints for the O-P-O bond angles and distances. The proposed restraints have been positively validated against data from the Nucleic Acid Database and an ultrahigh-resolution Z-DNA structure in the Protein Data Bank. Additionally, the manual classification of PO4 geometry is compared with geometrical clusters automatically discovered by machine learning methods. The machine learning cluster analysis provides useful insights and a practical example for general applications of clustering algorithms for automatic discovery of hidden patterns of molecular geometry. Finally, we describe the implementation and application of a public-domain web server for automatic generation of the proposed restraints.

Protonation and geometry of histidine rings.

The presence of H atoms connected to either or both of the two N atoms of the imidazole moiety in a histidine residue affects the geometry of the five-membered ring. Analysis of the imidazole moieties found in histidine residues of atomic resolution protein crystal structures in the Protein Data Bank (PDB), and in small-molecule structures retrieved from the Cambridge Structural Database (CSD), identified characteristic patterns of bond lengths and angles related to the protonation state of the imidazole moiety. Using discriminant analysis, two functions could be defined, corresponding to linear combinations of the four most sensitive stereochemical parameters, two bond lengths (ND1-CE1 and CE1-NE2) and two endocyclic angles (-ND1- and -NE2-), that uniquely identify the protonation states of all imidazole moieties in the CSD and can be used to predict which N atom(s) of the histidine side chains in protein structures are protonated. Updated geometrical restraint target values are proposed for differently protonated histidine side chains for use in macromolecular refinement.

ANS complex of St John's wort PR-10 protein with 28 copies in the asymmetric unit: a fiendish combination of pseudosymmetry with tetartohedral twinning.

Hyp-1, a pathogenesis-related class 10 (PR-10) protein from St John's wort (Hypericum perforatum), was crystallized in complex with the fluorescent probe 8-anilino-1-naphthalene sulfonate (ANS). The highly pseudosymmetric crystal has 28 unique protein molecules arranged in columns with sevenfold translational noncrystallographic symmetry (tNCS) along c and modulated X-ray diffraction with intensity crests at l = 7n and l = 7n ± 3. The translational NCS is combined with pseudotetragonal rotational NCS. The crystal was a perfect tetartohedral twin, although detection of twinning was severely hindered by the pseudosymmetry. The structure determined at 2.4 Šresolution reveals that the Hyp-1 molecules (packed as ß-sheet dimers) have three novel ligand-binding sites (two internal and one in a surface pocket), which was confirmed by solution studies. In addition to 60 Hyp-1-docked ligands, there are 29 interstitial ANS molecules distributed in a pattern that violates the arrangement of the protein molecules and is likely to be the generator of the structural modulation. In particular, whenever the stacked Hyp-1 molecules are found closer together there is an ANS molecule bridging them.

ACHESYM: an algorithm and server for standardized placement of macromolecular models in the unit cell.

Despite the existence of numerous useful conventions in structural crystallography, for example for the choice of the asymmetric part of the unit cell or of reciprocal space, surprisingly no standards are in use for the placement of the molecular model in the unit cell, often leading to inconsistencies or confusion. A conceptual solution for this problem has been proposed for macromolecular crystal structures based on the idea of the anti-Cheshire unit cell. Here, a program and server (called ACHESYM; http://achesym.ibch.poznan.pl) are presented for the practical implementation of this concept. In addition, the first task of ACHESYM is to find an optimal (compact) macromolecular assembly if more than one polymer chain exists. ACHESYM processes PDB (atomic parameters and TLS matrices) and mmCIF (diffraction data) input files to produce a new coordinate set and to reindex the reflections and modify their phases, if necessary.

Heterocyclic tautomerism: reassignment of two crystal structures of 2-amino-1,3-thiazolidin-4-one derivatives.

The structures of 5-(2-hydroxyethyl)-2-[(pyridin-2-yl)amino]-1,3-thiazolidin-4-one, C10H11N3O2S, (I), and ethyl 4-[(4-oxo-1,3-thiazolidin-2-yl)amino]benzoate, C12H12N2O3S, (II), which are identical to the entries with refcodes GACXOZ [Vána et al. (2009). J. Heterocycl. Chem. 46, 635-639] and HEGLUC [Behbehani & Ibrahim (2012). Molecules, 17, 6362-6385], respectively, in the Cambridge Structural Database [Allen (2002). Acta Cryst. B58, 380-388], have been redetermined at 130 K. This structural study shows that both investigated compounds exist in their crystal structures as the tautomer with the carbonyl-imine group in the five-membered heterocyclic ring and an exocyclic amine N atom, rather than the previously reported tautomer with a secondary amide group and an exocyclic imine N atom. The physicochemical and spectroscopic data of the two investigated compounds are the same as those of GACXOZ and HEGLUC, respectively. In the thiazolidin-4-one system of (I), the S and chiral C atoms, along with the hydroxyethyl group, are disordered. The thiazolidin-4-one fragment takes up two alternative locations in the crystal structure, which allows the molecule to adopt R and S configurations. The occupancy factors of the disordered atoms are 0.883 (2) (for the R configuration) and 0.117 (2) (for the S configuration). In (I), the main factor that determines the crystal packing is a system of hydrogen bonds, involving both strong N-H...N and O-H...O and weak C-H...O hydrogen bonds, linking the molecules into a three-dimensional hydrogen-bond network. On the other hand, in (II), the molecules are linked via N-H...O hydrogen bonds into chains.

Conformational space and vibrational spectra of 2-[(2,4-dimethoxyphenyl)amino]-1,3-thiazolidin-4-one.

In this work we present the results of a study of the X-ray structure of 2-[(2,4-dimethoxyphenyl)amino]-1,3-thiazolidin-4-one. Using the FTIR spectra in solid state and results of ab initio calculations we explain the issue of the tautomerism of this molecule. The compound is shown to exist as the 2-amino tautomer rather 2-imino tautomer. Here we consider eight possible tautomers. On the basis of the vibrational spectra we can eliminate five possible tautomers, as not existing in the solid state. As the most possible tautomeric form we have found keto 2-amino form.

Multiwavefront digital holographic television.

This paper presents the full technology chain supporting wide angle digital holographic television from holographic capture of real world objects/scenes to holographic display with an extended viewing angle. The data are captured with multiple CCD cameras located around an object. The display system is based on multiple tilted spatial light modulators (SLMs) arranged in a circular configuration. The capture-display system is linked by a holographic data processing module, which allows for significant decoupling of the capture and display systems. The presented experimental results, based on the reconstruction of real world, variable in time scenes, illustrates imaging dynamics, viewing angle and quality.

2-[N-(2,4-Dimeth-oxy-phen-yl)acetamido]-1,3-thia-zol-4-yl acetate.

The title compound, C15H16N2O5S, is a product of the reaction of 2-(2,4-dimeth-oxy-phenyl-amino)-1,3-thia-zol-4(5H)-one with acetic anhydride. The presence of the acetyl and acet-oxy groups in the mol-ecule indicates that the starting thia-zole exists as a tautomer in the reaction mixture with exocyclic amino and enol moieties. The acetyl group is tilted slightly from the heterocyclic ring plane [dihedral angle = 4.46 (11)°], while the acet-oxy group is almost perpendicular to this ring [dihedral angle = 88.14 (12)°]. An intra-molecular acet-yl-meth-oxy C-H⋯O inter-action is noted. In the crystal, mol-ecules are connected into a three-dimensional architecture by C-H⋯O inter-actions.

3ß-Acet-oxy-12α-chloro-d-friedooleanan-28,14ß-olide.

The title compound, C(32)H(49)ClO(4), was obtained along with nitrile and lactam products in the POCl(3)-catalysed Beckmann rearrangement from 3ß-acet-oxy-12-hydroxyiminoolean-28-olic acid methyl ester. The mechanism of the transformation leading to the title compound remains unclear and requires further investigation. Rings A, B and E are in chair conformations, ring C has a twisted-boat conformation, ring D a conformation halfway between boat and twisted-boat and rings D and E are cis-fused. In the crystal, mol-ecules are connected by weak inter-molecular C-H⋯O hydrogen bonds into layers extending parallel to the bc plane.