Ivan G. Shabalin

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

The anticancer activity of platinum-containing drugs such as cisplatin and carboplatin is considered to primarily arise from their interactions with nucleic acids; nevertheless, these drugs, or the products of their hydrolysis, also bind to proteins, potentially leading to the known side effects of the treatments. Here, over 40 crystal structures deposited in the Protein Data Bank (PDB) of cisplatin and carboplatin complexes of several proteins were analysed. Significant problems of either a crystallographic or a chemical nature were found in most of the presented atomic models and they could be traced to less or more serious deficiencies in the data-collection and refinement procedures. The re-evaluation of these data and models was possible thanks to their mandatory or voluntary deposition in publicly available databases, emphasizing the point that the availability of such data is critical for making structural science reproducible. Based on this analysis of a selected group of macromolecular structures, the importance of deposition of raw diffraction data is stressed and a procedure for depositing, tracking and using re-refined crystallographic models is suggested.

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, Mg2+-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 Mg2+ ions, the set of all sites was comprehensively validated and filtered to identify a benchmark dataset of 15 334 ‘reliable’ RNA-bound Mg2+ sites. The normalized frequencies by which specific RNA atoms coordinate Mg2+ were derived for both the inner and outer coordination spheres. A hierarchical classification system of Mg2+ 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 Mg2+-binding motifs and detect them in new RNA structures. Investigation of the most populous site types resulted in the identification of seven novel Mg2+-binding motifs, and all RNA structures in the PDB were screened for the presence of these motifs.

CheckMyMetal: a macromolecular metal-binding validation tool

The metal-site validation tool CheckMyMetal is described, with examples to follow.

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.

Protein purification and crystallization artifacts: The tale usually not told.

The misidentification of a protein sample, or contamination of a sample with the wrong protein, may be a potential reason for the non‐reproducibility of experiments. This problem may occur in the process of heterologous overexpression and purification of recombinant proteins, as well as purification of proteins from natural sources. If the contaminated or misidentified sample is used for crystallization, in many cases the problem may not be detected until structures are determined. In the case of functional studies, the problem may not be detected for years. Here several procedures that can be successfully used for the identification of crystallized protein contaminants, including: (i) a lattice parameter search against known structures, (ii) sequence or fold identification from partially built models, and (iii) molecular replacement with common contaminants as search templates have been presented. A list of common contaminant structures to be used as alternative search models was provided. These methods were used to identify four cases of purification and crystallization artifacts. This report provides troubleshooting pointers for researchers facing difficulties in phasing or model building.

Crystal structure of equine serum albumin in complex with cetirizine reveals a novel drug binding site.

Serum albumin (SA) is the main transporter of drugs in mammalian blood plasma. Here, we report the first crystal structure of equine serum albumin (ESA) in complex with antihistamine drug cetirizine at a resolution of 2.1Å. Cetirizine is bound in two sites--a novel drug binding site (CBS1) and the fatty acid binding site 6 (CBS2). Both sites differ from those that have been proposed in multiple reports based on equilibrium dialysis and fluorescence studies for mammalian albumins as cetirizine binding sites. We show that the residues forming the binding pockets in ESA are highly conserved in human serum albumin (HSA), and suggest that binding of cetirizine to HSA will be similar. In support of that hypothesis, we show that the dissociation constants for cetirizine binding to CBS2 in ESA and HSA are identical using tryptophan fluorescence quenching. Presence of lysine and arginine residues that have been previously reported to undergo nonenzymatic glycosylation in CBS1 and CBS2 suggests that cetirizine transport in patients with diabetes could be altered. A review of all available SA structures from the PDB shows that in addition to the novel drug binding site we present here (CBS1), there are two pockets on SA capable of binding drugs that do not overlap with fatty acid binding sites and have not been discussed in published reviews.

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.

Structure of anabolic ornithine carbamoyltransferase from Campylobacter jejuni at 2.7 Å resolution

Anabolic ornithine transcarbamoylase (aOTC) catalyzes the reaction between carbamoyl phosphate (CP) and L-ornithine (ORN) to form L-citrulline and phosphate in the urea cycle and L-arginine biosynthesis. The crystal structure of unliganded aOTC from Campylobacter jejuni (Cje aOTC) was determined at 2.7 Å resolution and refined to an R(work) of 20.3% and an R(free) of 24.0%. Cje aOTC is a trimer that forms a head-to-head pseudohexamer in the asymmetric unit. Each monomer is composed of an N-terminal CP-binding domain and a C-terminal ORN-binding domain joined by two interdomain helices. The Cje aOTC structure presents an open conformation of the enzyme with a relatively flexible orientation of the ORN-binding domain respective to the CP-binding domain. The conformation of the B2-H3 loop (residues 68-78), which is involved in binding CP in an adjacent subunit of the trimer, differs from that seen in homologous proteins with CP bound. The loop containing the ORN-binding motif (DxxxSMG, residues 223-230) has a conformation that is different from those observed in unliganded OTC structures from other species, but is similar to those in structures with bound ORN analogs. The major differences in tertiary structure between Cje aOTC and human aOTC are described.

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.

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.