Crystallography and chemistry should always go together: a cautionary tale of protein complexes with cisplatin and carboplatin

Towards a dependable data set of structures for L-asparaginase research

The Protein Data Bank (PDB) includes a carefully curated treasury of experimentally derived structural data on biological macromolecules and their various complexes. Such information is fundamental for a multitude of projects that involve large-scale data mining and/or detailed evaluation of individual structures of importance to chemistry, biology and, most of all, to medicine, where it provides the foundation for structure-based drug discovery. However, despite extensive validation mechanisms, it is almost inevitable that among the ∼215 000 entries there will occasionally be suboptimal or incorrect structure models. It is thus vital to apply careful verification procedures to those segments of the PDB that are of direct medicinal interest. Here, such an analysis was carried out for crystallographic models of L-asparaginases, enzymes that include approved drugs for the treatment of certain types of leukemia. The focus was on the adherence of the atomic coordinates to the rules of stereochemistry and their agreement with the experimental electron-density maps. Whereas the current clinical application of L-asparaginases is limited to two bacterial proteins and their chemical modifications, the field of investigations of such enzymes has expanded tremendously in recent years with the discovery of three entirely different structural classes and with numerous reports, not always quite reliable, of the anticancer properties of L-asparaginases of different origins.

MetalHawk: Enhanced Classification of Metal Coordination Geometries by Artificial Neural Networks

The chemical properties of metal complexes are strongly dependent on the number and geometrical arrangement of ligands coordinated to the metal center. Existing methods for determining either coordination number or geometry rely on a trade-off between accuracy and computational costs, which hinders their application to the study of large structure data sets. Here, we propose MetalHawk (https://github.com/vrettasm/MetalHawk), a machine learning-based approach to perform simultaneous classification of metal site coordination number and geometry through artificial neural networks (ANNs), which were trained using the Cambridge Structural Database (CSD) and Metal Protein Data Bank (MetalPDB). We demonstrate that the CSD-trained model can be used to classify sites belonging to the most common coordination numbers and geometry classes with balanced accuracy equal to 96.51% for CSD-deposited metal sites. The CSD-trained model was also found to be capable of classifying bioinorganic metal sites from the MetalPDB database, with balanced accuracy equal to 84.29% on the whole PDB data set and to 91.66% on manually reviewed sites in the PDB validation set. Moreover, we report evidence that the output vectors of the CSD-trained model can be considered as a proxy indicator of metal-site distortions, showing that these can be interpreted as a low-dimensional representation of subtle geometrical features present in metal site structures.

Molecular Gas-Phase Conformational Ensembles

Accurately determining the global minima of a molecular structure is important in diverse scientific fields, including drug design, materials science, and chemical synthesis. Conformational search engines serve as valuable tools for exploring the extensive conformational space of molecules and for identifying energetically favorable conformations. In this study, we present a comparison of Auto3D, CREST, Balloon, and ETKDG (from RDKit), which are freely available conformational search engines, to evaluate their effectiveness in locating global minima. These engines employ distinct methodologies, including machine learning (ML) potential-based, semiempirical, and force field-based approaches. To validate these methods, we propose the use of collisional cross-section (CCS) values obtained from ion mobility-mass spectrometry studies. We hypothesize that experimental gas-phase CCS values can provide experimental evidence that we likely have the global minimum for a given molecule. To facilitate this effort, we used our gas-phase conformation library (GPCL) which currently consists of the full ensembles of 20 small molecules and can be used by the community to validate any conformational search engine. Further members of the GPCL can be readily created for any molecule of interest using our standard workflow used to compute CCS values, expanding the ability of the GPCL in validation exercises. These innovative validation techniques enhance our understanding of the conformational landscape and provide valuable insights into the performance of conformational generation engines. Our findings shed light on the strengths and limitations of each search engine, enabling informed decisions for their utilization in various scientific fields, where accurate molecular structure determination is crucial for understanding biological activity and designing targeted interventions. By facilitating the identification of reliable conformations, this study significantly contributes to enhancing the efficiency and accuracy of molecular structure determination, with particular focus on metabolite structure elucidation. The findings of this research also provide valuable insights for developing effective workflows for predicting the structures of unknown compounds with high precision.

Will the Interactions of Some Platinum (II)-Based Drugs with B-Vitamins Reduce Their Therapeutic Effect in Cancer Patients? Comparison of Chemotherapeutic Agents such as Cisplatin, Carboplatin and Oxaliplatin-A Review

Pt (II) derivatives show anti-cancer activity by interacting with nucleobases of DNA, thus causing some spontaneous and non-spontaneous reactions. As a result, mono- and diaqua products are formed which further undergo complexation with guanine or adenine. Consequently, many processes are triggered, which lead to the death of the cancer cell. The theoretical and experimental studies confirm that such types of interactions can also occur with other chemical compounds. The vitamins from B group have a similar structure to the nucleobases of DNA and have aromatic rings with single-pair orbitals. Theoretical and experimental studies were performed to describe the interactions of B vitamins with Pt (II) derivatives such as cisplatin, oxaliplatin and carboplatin. The obtained results were compared with the values for guanine. Two levels of simulations were implemented at the theoretical level, namely, B3LYP/6-31G(d,p) with LANL2DZ bases set for platinum atoms and MN15/def2-TZVP. The polarizable continuum model (IEF-PCM preparation) and water as a solvent were used. UV-Vis spectroscopy was used to describe the drug-nucleobase and drug-B vitamin interactions. Values of the free energy (ΔG_r) show spontaneous reactions with mono- and diaqua derivatives of cisplatin and oxaliplatin; however, interactions with diaqua derivatives are more preferable. The strength of these interactions was also compared. Carboplatin products have the weakest interaction with the studied structures. The presence of non-covalent interactions was demonstrated in the tested complexes. A good agreement between theory and experiment was also demonstrated.

Crystal Structure of the Human Copper Chaperone ATOX1 Bound to Zinc Ion

The bioavailability of copper (Cu) in human cells may depend on a complex interplay with zinc (Zn) ions. We investigated the ability of the Zn ion to target the human Cu-chaperone Atox1, a small cytosolic protein capable of anchoring Cu(I), by a conserved surface-exposed Cys-X-X-Cys (CXXC) motif, and deliver it to Cu-transporting ATPases in the trans-Golgi network. The crystal structure of Atox1 loaded with Zn displays the metal ion bridging the CXXC motifs of two Atox1 molecules in a homodimer. The identity and location of the Zn ion were confirmed through the anomalous scattering of the metal by collecting X-ray diffraction data near the Zn K-edge. Furthermore, soaking experiments of the Zn-loaded Atox1 crystals with a strong chelating agent, such as EDTA, caused only limited removal of the metal ion from the tetrahedral coordination cage, suggesting a potential role of Atox1 in Zn metabolism and, more generally, that Cu and Zn transport mechanisms could be interlocked in human cells.

Machine learning differentiates enzymatic and non-enzymatic metals in proteins

Metalloenzymes are 40% of all enzymes and can perform all seven classes of enzyme reactions. Because of the physicochemical similarities between the active sites of metalloenzymes and inactive metal binding sites, it is challenging to differentiate between them. Yet distinguishing these two classes is critical for the identification of both native and designed enzymes. Because of similarities between catalytic and non-catalytic  metal binding sites, finding physicochemical features that distinguish these two types of metal sites can indicate aspects that are critical to enzyme function. In this work, we develop the largest structural dataset of enzymatic and non-enzymatic metalloprotein sites to date. We then use a decision-tree ensemble machine learning model to classify metals bound to proteins as enzymatic or non-enzymatic with 92.2% precision and 90.1% recall. Our model scores electrostatic and pocket lining features as more important than pocket volume, despite the fact that volume is the most quantitatively different feature between enzyme and non-enzymatic sites. Finally, we find our model has overall better performance in a side-to-side comparison against other methods that differentiate enzymatic from non-enzymatic sequences. We anticipate that our model's ability to correctly identify which metal sites are responsible for enzymatic activity could enable identification of new enzymatic mechanisms and de novo enzyme design.

Structural insights into protein folding, stability and activity using in vivo perdeuteration of hen egg-white lysozyme

This structural and biophysical study exploited a method of perdeuterating hen egg-white lysozyme based on the expression of insoluble protein in Escherichia coli followed by in-column chemical refolding. This allowed detailed comparisons with perdeuterated lysozyme produced in the yeast Pichia pastoris, as well as with unlabelled lysozyme. Both perdeuterated variants exhibit reduced thermal stability and enzymatic activity in comparison with hydrogenated lysozyme. The thermal stability of refolded perdeuterated lysozyme is 4.9°C lower than that of the perdeuterated variant expressed and secreted in yeast and 6.8°C lower than that of the hydrogenated Gallus gallus protein. However, both perdeuterated variants exhibit a comparable activity. Atomic resolution X-ray crystallographic analyses show that the differences in thermal stability and enzymatic function are correlated with refolding and deuteration effects. The hydrogen/deuterium isotope effect causes a decrease in the stability and activity of the perdeuterated analogues; this is believed to occur through a combination of changes to hydrophobicity and protein dynamics. The lower level of thermal stability of the refolded perdeuterated lysozyme is caused by the unrestrained Asn103 peptide-plane flip during the unfolded state, leading to a significant increase in disorder of the Lys97-Gly104 region following subsequent refolding. An ancillary outcome of this study has been the development of an efficient and financially viable protocol that allows stable and active perdeuterated lysozyme to be more easily available for scientific applications.

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.

The Affinity of Carboplatin to B-Vitamins and Nucleobases

Platinum compounds have found wide application in the treatment of various types of cancer and carboplatin is one of the main platinum-based drugs used as antitumor agents. The anticancer activity of carboplatin arises from interacting with DNA and inducing programmed cell death. However, such interactions may occur with other chemical compounds, such as vitamins containing aromatic rings with lone-pair orbitals, which reduces the anti-cancer effect of carboplatin. The most important aspect of the conducted research was related to the evaluation of carboplatin affinity to vitamins from the B group and the potential impact of such interactions on the reduction of therapeutic capabilities of carboplatin in anticancer therapy. Realized computations, including estimation of Gibbs Free Energies, allowed for the identification of the most reactive molecule, namely vitamin B6 (pyridoxal phosphate). In this case, the computational estimations indicating carboplatin reactivity were confirmed by spectrophotometric measurements.

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.

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.

On the evolution of the quality of macromolecular models in the PDB

Crystallographic models of biological macromolecules have been ranked using the quality criteria associated with them in the Protein Data Bank (PDB). The outcomes of this quality analysis have been correlated with time and with the journals that published papers based on those models. The results show that the overall quality of PDB structures has substantially improved over the last ten years, but this period of progress was preceded by several years of stagnation or even depression. Moreover, the study shows that the historically observed negative correlation between journal impact and the quality of structural models presented therein seems to disappear as time progresses.

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.

The Crystal Structure of the Manganese Superoxide Dismutase from Geobacillus stearothermophilus: Parker and Blake (1988) Revisited

Superoxide dismutase (SOD) is an almost ubiquitous metalloenzyme in aerobic organisms that catalyses the disproportionation of superoxide. Geobacillus stearothermophilus MnSOD is the only published MnSOD structure that does not have its coordinates publicly available, yet it is one of the more cited structures in the SOD literature. The structure has now been refined with modern programs, yielding a significantly improved structure which has been deposited in the Protein Data Bank. Importantly, the further refined structure reveals the presence of a catalytically important fifth ligand, water, to the metal centre, as observed in other SOD structures.

The biophysics of superoxide dismutase-1 and amyotrophic lateral sclerosis

Few proteins have come under such intense scrutiny as superoxide dismutase-1 (SOD1). For almost a century, scientists have dissected its form, function and then later its malfunction in the neurodegenerative disease amyotrophic lateral sclerosis (ALS). We now know SOD1 is a zinc and copper metalloenzyme that clears superoxide as part of our antioxidant defence and respiratory regulation systems. The possibility of reduced structural integrity was suggested by the first crystal structures of human SOD1 even before deleterious mutations in the sod1 gene were linked to the ALS. This concept evolved in the intervening years as an impressive array of biophysical studies examined the characteristics of mutant SOD1 in great detail. We now recognise how ALS-related mutations perturb the SOD1 maturation processes, reduce its ability to fold and reduce its thermal stability and half-life. Mutant SOD1 is therefore predisposed to monomerisation, non-canonical self-interactions, the formation of small misfolded oligomers and ultimately accumulation in the tell-tale insoluble inclusions found within the neurons of ALS patients. We have also seen that several post-translational modifications could push wild-type SOD1 down this toxic pathway. Recently we have come to view ALS as a prion-like disease where both the symptoms, and indeed SOD1 misfolding itself, are transmitted to neighbouring cells. This raises the possibility of intervention after the initial disease presentation. Several small-molecule and biologic-based strategies have been devised which directly target the SOD1 molecule to change the behaviour thought to be responsible for ALS. Here we provide a comprehensive review of the many biophysical advances that sculpted our view of SOD1 biology and the recent work that aims to apply this knowledge for therapeutic outcomes in ALS.

The Integrated Resource for Reproducibility in Macromolecular Crystallography: Experiences of the first four years

It has been increasingly recognized that preservation and public accessibility of primary experimental data are cornerstones necessary for the reproducibility of empirical sciences. In the field of molecular crystallography, many journals now recommend that authors of manuscripts presenting a new crystal structure should deposit their primary experimental data (X-ray diffraction images) to one of the dedicated resources created in recent years. Here, we describe our experiences developing the Integrated Resource for Reproducibility in Molecular Crystallography (IRRMC) and describe several examples of a crucial role that diffraction data can play in improving previously determined protein structures. In its first four years, several hundred crystallographers have deposited data from over 5200 diffraction experiments performed at over 60 different synchrotron beamlines or home sources all over the world. In addition to improving the resource and curating submitted data, we have been building a pipeline for extraction or, in some cases, reconstruction of the metadata necessary for seamless automated processing. Preliminary analysis indicates that about 95% of the archived data can be automatically reprocessed. A high rate of reprocessing success shows the feasibility of using the automated metadata extraction and automated processing as a validation step for the deposition of raw diffraction images. The IRRMC is guided by the Findable, Accessible, Interoperable, and Reusable data management principles.

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.

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

β-Lactamases are hydrolytic enzymes capable of opening the β-lactam ring of antibiotics such as penicillin, thus endowing the bacteria that produce them with antibiotic resistance. Of particular medical concern are metallo-β-lactamases (MBLs), with an active site built around coordinated Zn cations. MBLs are pan-reactive enzymes that can break down almost all classes of β-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 β-lactamase databases. We conducted a careful review of the crystal structures of class B β-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.

Principles and methods used to grow and optimize crystals of protein-metallodrug adducts, to determine metal binding sites and to assign metal ligands

The characterization of the interactions between biological macromolecules (proteins and nucleic acids) and metal-based drugs is a fundamental prerequisite for understanding their mechanisms of action. X-ray crystallography enables the structural analysis of such complexes with atomic level detail. However, this approach requires the preparation of highly diffracting single crystals, the measurement of diffraction patterns and the structural analysis and interpretation of macromolecule-metal interactions from electron density maps. In this review, we describe principles and methods used to grow and optimize crystals of protein-metallodrug adducts, to determine metal binding sites and to assign and validate metal ligands. Examples from the literature and experience in our own laboratory are provided and key challenges are described, notably crystallization and molecular model refinement against the X-ray diffraction data.

Characterizing metal-binding sites in proteins with X-ray crystallography

Metals have crucial roles in many physiological, pathological, toxicological, pharmaceutical, and diagnostic processes. Proper handling of metal-containing macromolecule samples for structural studies is not trivial, and failure to handle them properly is often a source of irreproducibility caused by issues such as pH changes, incorporation of unexpected metals, or oxidization/reduction of the metal. This protocol outlines the guidelines and best practices for characterizing metal-binding sites in protein structures and alerts experimenters to potential pitfalls during the preparation and handling of metal-containing protein samples for X-ray crystallography studies. The protocol features strategies for controlling the sample pH and the metal oxidation state, recording X-ray fluorescence (XRF) spectra, and collecting diffraction data sets above and below the corresponding metal absorption edges. This protocol should allow experimenters to gather sufficient evidence to unambiguously determine the identity and location of the metal of interest, as well as to accurately characterize the coordinating ligands in the metal binding environment within the protein. Meticulous handling of metal-containing macromolecule samples as described in this protocol should enhance experimental reproducibility in biomedical sciences, especially in X-ray macromolecular crystallography. For most samples, the protocol can be completed within a period of 7-190 d, most of which (2-180 d) is devoted to growing the crystal. The protocol should be readily understandable to structural biologists, particularly protein crystallographers with an intermediate level of experience.

Protein metalation by metal-based drugs: X-ray crystallography and mass spectrometry studies

The combined use of X-ray crystallography and mass spectrometry represents a valuable strategy to investigate and characterize protein metalation induced by anticancer metal-based drugs. Here, we summarize a series of significant results recently obtained in our laboratories upon the examination of the structures of several adducts of proteins with representative metallodrugs (mostly containing ruthenium, gold and platinum). The general mechanisms of protein metalation that emerge from a careful comparative analysis of these structures are illustrated and their mechanistic implications are discussed. Possible directions for future work in the field are delineated.

The science is in the data

Understanding published research results should be through one's own eyes and include the opportunity to work with raw diffraction data to check the various decisions made in the analyses by the original authors. Today, preserving raw diffraction data is technically and organizationally viable at a growing number of data archives, both centralized and distributed, which are empowered to register data sets and obtain a preservation descriptor, typically a 'digital object identifier'. This introduces an important role of preserving raw data, namely understanding where we fail in or could improve our analyses. Individual science area case studies in crystallography are provided.

Prediction of the interaction of metallic moieties with proteins: An update for protein-ligand docking techniques

In this article, we present a new approach to expand the range of application of protein-ligand docking methods in the prediction of the interaction of coordination complexes (i.e., metallodrugs, natural and artificial cofactors, etc.) with proteins. To do so, we assume that, from a pure computational point of view, hydrogen bond functions could be an adequate model for the coordination bonds as both share directionality and polarity aspects. In this model, docking of metalloligands can be performed without using any geometrical constraints or energy restraints. The hard work consists in generating the convenient atom types and scoring functions. To test this approach, we applied our model to 39 high-quality X-ray structures with transition and main group metal complexes bound via a unique coordination bond to a protein. This concept was implemented in the protein-ligand docking program GOLD. The results are in very good agreement with the experimental structures: the percentage for which the RMSD of the simulated pose is smaller than the X-ray spectra resolution is 92.3% and the mean value of RMSD is < 1.0 Å. Such results also show the viability of the method to predict metal complexes-proteins interactions when the X-ray structure is not available. This work could be the first step for novel applicability of docking techniques in medicinal and bioinorganic chemistry and appears generalizable enough to be implemented in most protein-ligand docking programs nowadays available. © 2017 Wiley Periodicals, Inc.

Molstack-Interactive visualization tool for presentation, interpretation, and validation of macromolecules and electron density maps

Our understanding of the world of biomolecular structures is based upon the interpretation of macromolecular models, of which ∼90% are an interpretation of electron density maps. This structural information guides scientific progress and exploration in many biomedical disciplines. The Protein Data Bank's web portals have made these structures available for mass scientific consumption and greatly broaden the scope of information presented in scientific publications. The portals provide numerous quality metrics; however, the portion of the structure that is most vital for interpretation of the function may have the most difficult to interpret electron density and this ambiguity is not reflected by any single metric. The possible consequences of basing research on suboptimal models make it imperative to inspect the agreement of a model with its experimental evidence. Molstack, a web-based interactive publishing platform for structural data, allows users to present density maps and structural models by displaying a collection of maps and models, including different interpretation of one's own data, re-refinements, and corrections of existing structures. Molstack organizes the sharing and dissemination of these structural models along with their experimental evidence as an interactive session. Molstack was designed with three groups of users in mind; researchers can present the evidence of their interpretation, reviewers and readers can independently judge the experimental evidence of the authors' conclusions, and other researchers can present or even publish their new hypotheses in the context of prior results. The server is available at http://molstack.bioreproducibility.org.

Databases, Repositories, and Other Data Resources in Structural Biology

Structural biology, like many other areas of modern science, produces an enormous amount of primary, derived, and "meta" data with a high demand on data storage and manipulations. Primary data come from various steps of sample preparation, diffraction experiments, and functional studies. These data are not only used to obtain tangible results, like macromolecular structural models, but also to enrich and guide our analysis and interpretation of various biomedical problems. Herein we define several categories of data resources, (a) Archives, (b) Repositories, (c) Databases, and (d) Advanced Information Systems, that can accommodate primary, derived, or reference data. Data resources may be used either as web portals or internally by structural biology software. To be useful, each resource must be maintained, curated, as well as integrated with other resources. Ideally, the system of interconnected resources should evolve toward comprehensive "hubs", or Advanced Information Systems. Such systems, encompassing the PDB and UniProt, are indispensable not only for structural biology, but for many related fields of science. The categories of data resources described herein are applicable well beyond our usual scientific endeavors.

Perspectives and expectations in structural bioinformatics of metalloproteins

Recent papers highlight the presence of large numbers of compressed angles in metal ion coordination geometries for metalloprotein entries in the worldwide Protein Data Bank, due mainly to multidentate coordination. The prevalence of these compressed angles has raised the controversial idea that significantly populated aberrant or even novel coordination geometries may exist. Some of these papers have undergone severe criticism, apparently due to views held that only canonical coordination geometries exist in significant numbers. While criticism of controversial ideas is warranted and to be expected, we believe that a line was crossed where unfair criticism was put forth to discredit an inconvenient result that compressed angles exist in large numbers, which does not support the dogmatic canonical coordination geometry view. We present a review of the major controversial results and their criticisms, pointing out both good suggestions that have been incorporated in new analyses, but also unfair criticism that was put forth to support a particular view. We also suggest that better science is enabled through: (i) a more collegial and collaborative approach in future critical reviews and (ii) the requirement for a description of methods and data including source code and visualizations that enables full reproducibility of results. Proteins 2017; 85:938-944. © 2016 Wiley Periodicals, Inc.

CheckMyMetal: a macromolecular metal-binding validation tool

Metals are essential in many biological processes, and metal ions are modeled in roughly 40% of the macromolecular structures in the Protein Data Bank (PDB). However, a significant fraction of these structures contain poorly modeled metal-binding sites. CheckMyMetal (CMM) is an easy-to-use metal-binding site validation server for macromolecules that is freely available at http://csgid.org/csgid/metal_sites. The CMM server can detect incorrect metal assignments as well as geometrical and other irregularities in the metal-binding sites. Guidelines for metal-site modeling and validation in macromolecules are illustrated by several practical examples grouped by the type of metal. These examples show CMM users (and crystallographers in general) problems they may encounter during the modeling of a specific metal ion.

Sharing Big Data

Macromolecular Big Data provide numerous challenges and a number of initiatives that are starting to overcome these issues are discussed.

Raw diffraction data preservation and reuse: overview, update on practicalities and metadata requirements

A topical review is presented of the rapidly developing interest in and storage options for the preservation and reuse of raw data within the scientific domain of the IUCr and its Commissions, each of which operates within a great diversity of instrumentation. A résumé is included of the case for raw diffraction data deposition. An overall context is set by highlighting the initiatives of science policy makers towards an 'Open Science' model within which crystallographers will increasingly work in the future; this will bring new funding opportunities but also new codes of procedure within open science frameworks. Skills education and training for crystallographers will need to be expanded. Overall, there are now the means and the organization for the preservation of raw crystallographic diffraction data via different types of archive, such as at universities, discipline-specific repositories (Integrated Resource for Reproducibility in Macromol-ecular Crystallography, Structural Biology Data Grid), general public data repositories (Zenodo, ResearchGate) and centralized neutron and X-ray facilities. Formulation of improved metadata descriptors for the raw data types of each of the IUCr Commissions is in progress; some detailed examples are provided. A number of specific case studies are presented, including an example research thread that provides complete open access to raw data.

A public database of macromolecular diffraction experiments

The low reproducibility of published experimental results in many scientific disciplines has recently garnered negative attention in scientific journals and the general media. Public transparency, including the availability of `raw' experimental data, will help to address growing concerns regarding scientific integrity. Macromolecular X-ray crystallography has led the way in requiring the public dissemination of atomic coordinates and a wealth of experimental data, making the field one of the most reproducible in the biological sciences. However, there remains no mandate for public disclosure of the original diffraction data. The Integrated Resource for Reproducibility in Macromolecular Crystallography (IRRMC) has been developed to archive raw data from diffraction experiments and, equally importantly, to provide related metadata. Currently, the database of our resource contains data from 2920 macromolecular diffraction experiments (5767 data sets), accounting for around 3% of all depositions in the Protein Data Bank (PDB), with their corresponding partially curated metadata. IRRMC utilizes distributed storage implemented using a federated architecture of many independent storage servers, which provides both scalability and sustainability. The resource, which is accessible via the web portal at http://www.proteindiffraction.org, can be searched using various criteria. All data are available for unrestricted access and download. The resource serves as a proof of concept and demonstrates the feasibility of archiving raw diffraction data and associated metadata from X-ray crystallographic studies of biological macromolecules. The goal is to expand this resource and include data sets that failed to yield X-ray structures in order to facilitate collaborative efforts that will improve protein structure-determination methods and to ensure the availability of `orphan' data left behind for various reasons by individual investigators and/or extinct structural genomics projects.

Cisplatin-Protein Interactions: Unexpected Drug Binding to N-Terminal Amine and Lysine Side Chains

Literature studies carried out by mass spectrometry and X-ray crystallography have demonstrated that cisplatin is able to bind proteins mainly close to Met, His, and free Cys side chains. To identify possible alternative modes of cisplatin binding to proteins at the molecular level, here we have solved the high-resolution X-ray structure of the adduct formed in the reaction between the drug and the model protein thaumatin, which does not contain any His and free Cys residues and possesses just one buried Met. Our data reveal unexpected cisplatin binding sites on the protein surface that could have general significance: cisplatin fragments -[Pt(NH3)2Cl](+), -[Pt(NH3)Cl2], and -[Pt(NH3)2(OH2)](2+) bind to a protein N-terminus and close to Lys and Glu side chains.

Effect of temperature on the interaction of cisplatin with the model protein hen egg white lysozyme

The products of the reaction between cisplatin (CDDP) and the model protein hen egg white lysozyme (HEWL) at 20, 37 and 55 °C in pure water were studied by UV-Vis absorption spectroscopy, intrinsic fluorescence and circular dichroism, dynamic and electrophoretic light scattering and inductively coupled plasma mass spectrometry. X-ray structures were also solved for the adducts formed at 20 and 55 °C. Data demonstrate that high temperature facilitates the formation of CDDP-HEWL adducts, where Pt atoms bind ND1 atom of His15 or NE2 atom of His15 and NH1 atom of Arg14. Our study suggests that high human body temperature (fever) could increase the rate of drug binding to proteins thus enhancing possible toxic side effects related to CDDP administration.

Prior knowledge or freedom of interpretation? A critical look at a recently published classification of "novel" Zn binding sites

In a recently published article (Yao, Flight, Rouchka, and Moseley, Proteins 2015;83:1470-1487) the authors proposed novel Zn coordination patterns in protein structures, apparently discovered using an unprejudiced approach to the information collected in the Protein data Bank (PDB), which they advocated as superior to the prior-knowledge-informed paradigm. In our assessment of those propositions we demonstrate here that most, if not all, of the "new" coordination geometries are fictitious, as they are based on incorrectly interpreted protein crystal structures, which in themselves are often not error-free. The flaws of interpretation include partial or wrong Zn sites, missed or wrong ligands, ignored crystal symmetry and ligands, etc. In conclusion, we warn against using this and similar meta-analyses that ignore chemical and crystallographic knowledge, and emphasize the importance of safeguarding structural databases against bad apples. Proteins 2016; 84:770-776. © 2016 Wiley Periodicals, Inc.

Re-refinement of 4xan: hen egg-white lysozyme with carboplatin in sodium bromide solution

An addendum is published to Tanley et al. [(2014), Acta Cryst. F70, 1135–1142].

A re-refinement of 4xan, hen egg-white lysozyme (HEWL) with carboplatin crystallized in NaBr solution, has been made and is published here as an addendum to Tanley et al. [(2014), Acta Cryst. F70, 1135–1142]. This follows a previous re-refinement and PDB deposition (4yem) by Shabalin et al. [(2015), Acta Cryst. D71, 1965–1979]. The critical evaluation of the original PDB deposition (4xan), and the subsequent critical examination of the re-refined structure (4yem), has led to an improved model (PDB code 5hmj).

Re-refinement of 4g4a: room-temperature X-ray diffraction study of cisplatin and its binding to His15 of HEWL after 14 months chemical exposure in the presence of DMSO

A re-refinement of 4g4a, the room-temperature X-ray diffraction study of cisplatin and its binding to His15 of HEWL after 14 months chemical exposure in the presence of DMSO is published as an addendum to Tanley et al. [(2012), Acta Cryst. F68, 1300-1306]. This example illustrates the benefits of sharing raw diffraction images, as well as structure factors and molecular coordinates, as the diffraction resolution of the study is now much improved at 1.70 Å.

Safeguarding Structural Data Repositories against Bad Apples

Structural biology research generates large amounts of data, some deposited in public databases or repositories, but a substantial remainder never becomes available to the scientific community. In addition, some of the deposited data contain less or more serious errors that may bias the results of data mining. Thorough analysis and discussion of these problems is needed to ameliorate this situation. This perspective is an attempt to propose some solutions and encourage both further discussion and action on the part of the relevant organizations, in particular the PDB and various bodies of the International Union of Crystallography.

Fitmunk: improving protein structures by accurate, automatic modeling of side-chain conformations

Improvements in crystallographic hardware and software have allowed automated structure-solution pipelines to approach a near-`one-click' experience for the initial determination of macromolecular structures. However, in many cases the resulting initial model requires a laborious, iterative process of refinement and validation. A new method has been developed for the automatic modeling of side-chain conformations that takes advantage of rotamer-prediction methods in a crystallographic context. The algorithm, which is based on deterministic dead-end elimination (DEE) theory, uses new dense conformer libraries and a hybrid energy function derived from experimental data and prior information about rotamer frequencies to find the optimal conformation of each side chain. In contrast to existing methods, which incorporate the electron-density term into protein-modeling frameworks, the proposed algorithm is designed to take advantage of the highly discriminatory nature of electron-density maps. This method has been implemented in the program Fitmunk, which uses extensive conformational sampling. This improves the accuracy of the modeling and makes it a versatile tool for crystallographic model building, refinement and validation. Fitmunk was extensively tested on over 115 new structures, as well as a subset of 1100 structures from the PDB. It is demonstrated that the ability of Fitmunk to model more than 95% of side chains accurately is beneficial for improving the quality of crystallographic protein models, especially at medium and low resolutions. Fitmunk can be used for model validation of existing structures and as a tool to assess whether side chains are modeled optimally or could be better fitted into electron density. Fitmunk is available as a web service at http://kniahini.med.virginia.edu/fitmunk/server/ or at http://fitmunk.bitbucket.org/.

The young person's guide to the PDB

The Protein Data Bank (PDB), created in 1971 when merely seven protein crystal structures were known, today holds over 120, 000 experimentally-determined three-dimensional models of macromolecules, including gigantic structures comprised of hundreds of thousands of atoms, such as ribosomes and viruses. Most of the deposits come from X-ray crystallography experiments, with important contributions also made by NMR spectroscopy and, recently, by the fast growing Cryo-Electron Microscopy. Although the determination of a macromolecular crystal structure is now facilitated by advanced experimental tools and by sophisticated software, it is still a highly complicated research process requiring specialized training, skill, experience and a bit of luck. Understanding the plethora of structural information provided by the PDB requires that its users (consumers) have at least a rudimentary initiation. This is the purpose of this educational overview.

X-ray crystallography over the past decade for novel drug discovery - where are we heading next?

INTRODUCTION

Macromolecular X-ray crystallography has been the primary methodology for determining the three-dimensional structures of proteins, nucleic acids and viruses. Structural information has paved the way for structure-guided drug discovery and laid the foundations for structural bioinformatics. However, X-ray crystallography still has a few fundamental limitations, some of which may be overcome and complemented using emerging methods and technologies in other areas of structural biology.

AREAS COVERED

This review describes how structural knowledge gained from X-ray crystallography has been used to advance other biophysical methods for structure determination (and vice versa). This article also covers current practices for integrating data generated by other biochemical and biophysical methods with those obtained from X-ray crystallography. Finally, the authors articulate their vision about how a combination of structural and biochemical/biophysical methods may improve our understanding of biological processes and interactions.

EXPERT OPINION

X-ray crystallography has been, and will continue to serve as, the central source of experimental structural biology data used in the discovery of new drugs. However, other structural biology techniques are useful not only to overcome the major limitation of X-ray crystallography, but also to provide complementary structural data that is useful in drug discovery. The use of recent advancements in biochemical, spectroscopy and bioinformatics methods may revolutionize drug discovery, albeit only when these data are combined and analyzed with effective data management systems. Accurate and complete data management is crucial for developing experimental procedures that are robust and reproducible.