Protein crystallography for aspiring crystallographers or how to avoid pitfalls and traps in macromolecular structure determination

Structural Characterization of Heat Shock Protein 90β and Molecular Interactions with Geldanamycin and Ritonavir: A Computational Study

Drug repositioning is an important therapeutic strategy for treating breast cancer. Hsp90β chaperone is an attractive target for inhibiting cell progression. Its structure has a disordered and flexible linker region between the N-terminal and central domains. Geldanamycin was the first Hsp90β inhibitor to interact specifically at the N-terminal site. Owing to the toxicity of geldanamycin, we investigated the repositioning of ritonavir as an Hsp90β inhibitor, taking advantage of its proven efficacy against cancer. In this study, we used molecular modeling techniques to analyze the contribution of the Hsp90β linker region to the flexibility and interaction between the ligands geldanamycin, ritonavir, and Hsp90β. Our findings indicate that the linker region is responsible for the fluctuation and overall protein motion without disturbing the interaction between the inhibitors and the N-terminus. We also found that ritonavir established similar interactions with the substrate ATP triphosphate, filling the same pharmacophore zone.

Unveiling success determinants for AMB-assisted phase expansion of fusion proteins in ARP/wARP

Fusion proteins (FPs) are frequently utilized as a biotechnological tool in the determination of macromolecular structures using X-ray methods. Here, we explore the use of different protein tags in various FP, to obtain initial phases by using them in a partial molecular replacement (MR) and constructing the remaining FP structure with ARP/wARP. Usually, the tag is removed prior to crystallization, however leaving the tag on may facilitate crystal formation, and structural determination by expanding phases from known to unknown segments of the complex. In this study, the Protein Data Bank was mined for an up-to-date list of FPs with the most used protein tags, Maltose Binding Protein (MBP), Green Fluorescent Protein (GFP), Thioredoxin (TRX), Glutathione transferase (GST) and the Small Ubiquitin-like Modifier Protein (SUMO). Partial MR using the protein tag, followed by automatic model building, was tested on a subset of 116 FP. The efficiency of this method was analyzed and factors that influence the coordinate construction of a substantial portions of the fused protein were identified. Using MBP, GFP, and SUMO as phase generators it was possible to build at least 75 % of the protein of interest in 36 of the 116 cases tested. Our results reveal that tag selection has a significant impact; tags with greater structural stability, such as GFP, increase the success rate. Further statistical analysis identifies that resolution, Wilson B factor, solvent percentage, completeness, multiplicity, protein tag percentage in the FP (considering amino acids), and the linker length play pivotal roles using our approach. In cases where a structural homologous is absent, this method merits inclusion in the toolkit of protein crystallographers.

Investigating the Taenia solium Fatty Acid Binding Protein Superfamily for Their Immunological Outlook and Prospect for Therapeutic Targets

Taenia solium, like other helminthic parasites, lacks key components of cellular machinery required for endogenous lipid biosynthesis. This deficiency compels the parasite to obtain all of its lipid requirements from its host. The passage of lipids across the cell membrane is tightly regulated. To facilitate effective lipid transport, the cestode parasite utilizes certain lipid binding proteins called FABPs. These FABPs bind with the lipid ligands and allow the transport of lipids across the membranes and into the cytosol. Here, by integrating a computational with homology protein prediction tools, we had identified five FABPs in the T. solium proteome. We confirmed their presence by RNA expression analysis of respective genes from the parasite's cysticerci transcript. During the molecular modeling and MD simulation studies, two of them, TsM_000544100 and TsM_001185100, were most stable. Furthermore, they had a robust interaction with the IgG1 molecule, as evidenced by MD simulation. In addition, by employing in silico screening, we had identified potential ligand interacting residues that are present on the probable druggable site. In combination with in vitro cysticidal assays, enalaprilat dihydrate showed efficacy against cysticerci, which suggests that FABPs play a significant role in the cysticercus life cycle. Together, we provided a detailed distribution of all FABPs expressed by T. solium cysticerci and the critical role of TsM_001185100 in cysticercus viability.

Words of advice: teaching macromolecular crystallography

The ability to view structures of proteins at atomic resolution, facilitated by the rise of macromolecular crystallography, has had a tremendous impact in many areas of sciences, including molecular pharmacology, drug discovery and biotechnology. However, the teaching of macromolecular crystallography in universities across the globe has been less than optimal. This could be attributed to the interdisciplinary nature of this subject, making it appear esoteric and incomprehensible, at least at first glance, for students who have exclusive training in only one specific discipline. For the instructor, this problem is compounded further by the plethora of complex concepts and specialized terminologies that the science of macromolecular crystallography has accumulated over the course of its evolution. Moreover, the advent of robotics and several sophisticated software algorithms have reduced the incentive to understand the beautiful conceptual bedrock on which this subject is based. As a way of addressing some of the challenges delineated above, this Words of Advice article attempts to formulate the broad framework within which the teaching and learning of macromolecular crystallography should be approached. It advocates the acknowledgement that this is an interdisciplinary field, with substantial contributions from chemical, physical, biological and mathematical sciences, requiring the evolution of teaching approaches that acknowledge this reality. Moreover, it suggests the use of visual tools, use of computational resources and history to make the subject more relatable to students.

Structure and Dynamics Guiding Design of Antibody Therapeutics and Vaccines

Antibodies and other new antibody-like formats have emerged as one of the most rapidly growing classes of biotherapeutic proteins. Understanding the structural features that drive antibody function and, consequently, their molecular recognition is critical for engineering antibodies. Here, we present the structural architecture of conventional IgG antibodies alongside other formats. We emphasize the importance of considering antibodies as conformational ensembles in solution instead of focusing on single-static structures because their functions and properties are strongly governed by their dynamic nature. Thus, in this review, we provide an overview of the unique structural and dynamic characteristics of antibodies with respect to their antigen recognition, biophysical properties, and effector functions. We highlight the numerous technical advances in antibody structure prediction and design, enabled by the vast number of experimentally determined high-quality structures recorded with cryo-EM, NMR, and X-ray crystallography. Lastly, we assess antibody and vaccine design strategies in the context of structure and dynamics.

Involvement of the alpha-subunit N-terminus in the mechanism of the Na+,K+-ATPase

Previous studies have shown that cytoplasmic K+ release and the associated E2 → E1 conformational change of the Na+,K+-ATPase is a major rate-determining step of the enzyme's ion pumping cycle and hence a prime site of acute regulatory intervention. From the ionic strength dependence of the enzyme's distribution between the E2 and E1 states, it has also been found that E2 is stabilized by an electrostatic attraction. Any disruption of this electrostatic attraction would, thus, have profound effects on the rate of ion pumping. The aim of this paper is to identify the location of this interaction. Using enhanced-sampling molecular dynamics simulations with a predicted N-terminal structure added to the X-ray crystal structure of the Na+,K+-ATPase, a previously postulated salt bridge between Lys32 and Glu233 (rat sequence numbering) of the enzyme's α-subunit can be excluded. The residues never approach closely enough to form a salt bridge. In contrast, strong interactions with anionic lipid head groups were seen. To investigate the possibility of a protein-lipid interaction experimentally, the surface charge density of Na+,K+-ATPase-containing membrane fragments was estimated from zeta potential measurements to be 0.019 (± 0.001) C m-2. This is in good agreement with the charge density previously determined to be responsible for stabilization of the E2 state of 0.023 (± 0.009) C m-2 and the membrane charge density estimated here from published electron-microscopic images of 0.018C m-2. The results are, therefore, consistent with an interaction of the Na+,K+-ATPase α-subunit N-terminus with negatively-charged lipid head groups of the neighbouring cytoplasmic membrane surface as the origin of the electrostatic interaction stabilising the E2 state.

Technologies for Direct Detection of Covalent Protein-Drug Adducts

In the past two decades, drug candidates with a covalent binding mode have gained the interest of medicinal chemists, as several covalent anticancer drugs have successfully reached the clinic. As a covalent binding mode changes the relevant parameters to rank inhibitor potency and investigate structure-activity relationship (SAR), it is important to gather experimental evidence on the existence of a covalent protein-drug adduct. In this work, we review established methods and technologies for the direct detection of a covalent protein-drug adduct, illustrated with examples from (recent) drug development endeavors. These technologies include subjecting covalent drug candidates to mass spectrometric (MS) analysis, protein crystallography, or monitoring intrinsic spectroscopic properties of the ligand upon covalent adduct formation. Alternatively, chemical modification of the covalent ligand is required to detect covalent adducts by NMR analysis or activity-based protein profiling (ABPP). Some techniques are more informative than others and can also elucidate the modified amino acid residue or bond layout. We will discuss the compatibility of these techniques with reversible covalent binding modes and the possibilities to evaluate reversibility or obtain kinetic parameters. Finally, we expand upon current challenges and future applications. Overall, these analytical techniques present an integral part of covalent drug development in this exciting new era of drug discovery.

In silico modelling of the function of disease-related CAZymes

In silico modelling of proteins comprises a diversity of computational tools aimed to obtain structural, electronic, and/or dynamic information about these biomolecules, capturing mechanistic details that are challenging to experimental approaches, such as elusive enzyme-substrate complexes, short-lived intermediates, and reaction transition states (TS). The present article gives the reader insight on the use of in silico modelling techniques to understand complex catalytic reaction mechanisms of carbohydrate-active enzymes (CAZymes), along with the underlying theory and concepts that are important in this field. We start by introducing the significance of carbohydrates in nature and the enzymes that process them, CAZymes, highlighting the conformational flexibility of their carbohydrate substrates. Three commonly used in silico methods (classical molecular dynamics (MD), hybrid quantum mechanics/molecular mechanics (QM/MM), and enhanced sampling techniques) are described for nonexpert readers. Finally, we provide three examples of the application of these methods to unravel the catalytic mechanisms of three disease-related CAZymes: β-galactocerebrosidase (GALC), responsible for Krabbe disease; α-mannoside β-1,6-N-acetylglucosaminyltransferase V (MGAT5), involved in cancer; and O-fucosyltransferase 1 (POFUT1), involved in several human diseases such as leukemia and the Dowling-Degos disease.

CMM-An enhanced platform for interactive validation of metal binding sites

Metal ions bound to macromolecules play an integral role in many cellular processes. They can directly participate in catalytic mechanisms or be essential for the structural integrity of proteins and nucleic acids. However, their unique nature in macromolecules can make them difficult to model and refine, and a substantial portion of metal ions in the PDB are misidentified or poorly refined. CheckMyMetal (CMM) is a validation tool that has gained widespread acceptance as an essential tool for researchers working on metal-macromolecule complexes. CMM can be used during structure determination or to validate metal binding sites in structural models within the PDB. The functionalities of CMM have recently been greatly enhanced and provide researchers with additional information that can guide modeling decisions. The new version of CMM shows metals in the context of electron density maps and allows for on-the-fly refinement of metal binding sites. The improvements should increase the reproducibility of biomedical research. The web server is available at https://cmm.minorlab.org.

Simulating diffraction photographs based on molecular dynamics trajectories of a protein crystal: a new option to examine structure-solving strategies in protein crystallography

A molecular dynamics (MD)-based pipeline has been designed and implemented to emulate the entire process of collecting diffraction photographs and calculating crystallographic structures of proteins from them. Using a structure of lysozyme solved in-house, a supercell comprising 125 (5 × 5 × 5) crystal unit cells containing a total of 1000 protein molecules and explicit interstitial solvent was constructed. For this system, two 300 ns MD trajectories at 298 and 250 K were recorded. A series of snapshots from these trajectories were then used to simulate a fully realistic set of diffraction photographs, which were further fed into the standard pipeline for structure determination. The resulting structures show very good agreement with the underlying MD model not only in terms of coordinates but also in terms of B factors; they are also consistent with the original experimental structure. The developed methodology should find a range of applications, such as optimizing refinement protocols to solve crystal structures and extracting dynamics information from diffraction data or diffuse scattering.

Neutralizing monoclonal antibodies elicited by mosaic RBD nanoparticles bind conserved sarbecovirus epitopes

Increased immune evasion by SARS-CoV-2 variants of concern highlights the need for new therapeutic neutralizing antibodies. Immunization with nanoparticles co-displaying spike receptor-binding domains (RBDs) from eight sarbecoviruses (mosaic-8 RBD-nanoparticles) efficiently elicits cross-reactive polyclonal antibodies against conserved sarbecovirus RBD epitopes. Here, we identified monoclonal antibodies (mAbs) capable of cross-reactive binding and neutralization of animal sarbecoviruses and SARS-CoV-2 variants by screening single mouse B cells secreting IgGs that bind two or more sarbecovirus RBDs. Single-particle cryo-EM structures of antibody-spike complexes, including a Fab-Omicron complex, mapped neutralizing mAbs to conserved class 1/4 RBD epitopes. Structural analyses revealed neutralization mechanisms, potentials for intra-spike trimer cross-linking by IgGs, and induced changes in trimer upon Fab binding. In addition, we identified a mAb-resembling Bebtelovimab, an EUA-approved human class 3 anti-RBD mAb. These results support using mosaic RBD-nanoparticle vaccination to generate and identify therapeutic pan-sarbecovirus and pan-variant mAbs.

Discovery of new potent lysine specific histone demythelase-1 inhibitors (LSD-1) using structure based and ligand based molecular modelling and machine learning

Lysine-specific histone demethylase 1 (LSD-1) is an epigenetic enzyme that oxidatively cleaves methyl groups from monomethyl and dimethyl Lys4 of histone H3 and is highly overexpressed in different types of cancer. Therefore, it has been widely recognized as a promising therapeutic target for cancer therapy. Towards this end, we employed various Computer Aided Drug Design (CADD) approaches including pharmacophore modelling and machine learning. Pharmacophores generated by structure-based (SB) (either crystallographic-based or docking-based) and ligand-based (LB) (either supervised or unsupervised) modelling methods were allowed to compete within the context of genetic algorithm/machine learning and were assessed by Shapley additive explanation values (SHAP) to end up with three successful pharmacophores that were used to screen the National Cancer Institute (NCI) database. Seventy-five NCI hits were tested for their LSD-1 inhibitory properties against neuroblastoma SH-SY5Y cells, pancreatic carcinoma Panc-1 cells, glioblastoma U-87 MG cells and in vitro enzymatic assay, culminating in 3 nanomolar LSD-1 inhibitors of novel chemotypes.

Intrinsically disordered proteins in viral pathogenesis and infections

Disordered proteins serve a crucial part in many biological processes that go beyond the capabilities of ordered proteins. A large number of virus-encoded proteins have extremely condensed proteomes and genomes, which results in highly disordered proteins. The presence of these IDPs allows them to rapidly adapt to changes in their biological environment and play a significant role in viral replication and down-regulation of host defense mechanisms. Since viruses undergo rapid evolution and have a high rate of mutation and accumulation in their proteome, IDPs' insights into viruses are critical for understanding how viruses hijack cells and cause disease. There are many conformational changes that IDPs can adopt in order to interact with different protein partners and thus stabilize the particular fold and withstand high mutation rates. This chapter explains the molecular mechanism behind viral IDPs, as well as the significance of recent research in the field of IDPs, with the goal of gaining a deeper comprehension of the essential roles and functions played by viral proteins.

Fundamental Redesign of the TIGER2hs Kernel to Address Severe Parameter Sensitivity

Replica exchange molecular dynamics simulations are one of the most popular approaches to enhance conformational sampling of molecular systems. Applications range from protein folding to protein-protein or other host-guest interactions, as well as binding free energy calculations. While these methods are computationally expensive, highly accurate results can be obtained. We recently developed TIGER2hs, an improved version of the temperature intervals with global exchange of replicas (TIGER2) algorithm. This method combines the replica-based enhanced sampling in an explicit solvent with a hybrid solvent energy evaluation. During the exchange attempts, bulk water is replaced by an implicit solvent model, allowing sampling with significantly less replicas than parallel tempering (REMD). This enables accurate enhanced sampling calculations with only a fraction of computational resources compared to REMD. Our latest results highlight several issues with sampling imbalance and parameter sensitivity within the original TIGER2 exchange algorithms that affect the overall state populations. A high sensitivity on replica number and maximum temperature is eliminated by changing to a pairwise exchange kernel (PE) without additional sorting. Simulations are controlled by adjusting the average temperature change per exchange ⟨ΔT/χ⟩ to below 30 K to mimic a controlled temperature mixing of replicas similar to REMD. Thus, this parameter provides an applicable property for selecting combinations of replica number and maximum temperature to adjust simulations for best accuracy, with flexible resource investment. This increases the robustness of the method and ensures results in excellent agreement with REMD, as demonstrated for three different peptides.

Characterization of protein unfolding by fast cross-linking mass spectrometry using di-ortho-phthalaldehyde cross-linkers

Chemical cross-linking of proteins coupled with mass spectrometry is widely used in protein structural analysis. In this study we develop a class of non-hydrolyzable amine-selective di-ortho-phthalaldehyde (DOPA) cross-linkers, one of which is called DOPA2. Cross-linking of proteins with DOPA2 is 60-120 times faster than that with the N-hydroxysuccinimide ester cross-linker DSS. Compared with DSS cross-links, DOPA2 cross-links show better agreement with the crystal structures of tested proteins. More importantly, DOPA2 has unique advantages when working at low pH, low temperature, or in the presence of denaturants. Using staphylococcal nuclease, bovine serum albumin, and bovine pancreatic ribonuclease A, we demonstrate that DOPA2 cross-linking provides abundant spatial information about the conformations of progressively denatured forms of these proteins. Furthermore, DOPA2 cross-linking allows time-course analysis of protein conformational changes during denaturant-induced unfolding.

Modeling and Structure Determination of Homo-Oligomeric Proteins: An Overview of Challenges and Current Approaches

Protein homo-oligomerization is a very common phenomenon, and approximately half of proteins form homo-oligomeric assemblies composed of identical subunits. The vast majority of such assemblies possess internal symmetry which can be either exploited to help or poses challenges during structure determination. Moreover, aspects of symmetry are critical in the modeling of protein homo-oligomers either by docking or by homology-based approaches. Here, we first provide a brief overview of the nature of protein homo-oligomerization. Next, we describe how the symmetry of homo-oligomers is addressed by crystallographic and non-crystallographic symmetry operations, and how biologically relevant intermolecular interactions can be deciphered from the ordered array of molecules within protein crystals. Additionally, we describe the most important aspects of protein homo-oligomerization in structure determination by NMR. Finally, we give an overview of approaches aimed at modeling homo-oligomers using computational methods that specifically address their internal symmetry and allow the incorporation of other experimental data as spatial restraints to achieve higher model reliability.

Dr. Alexander Wlodawer-celebrating five decades of service to the structural biology community

This 75th birthday tribute to our Editorial Board member Alexander Wlodawer recounts his decades-long service to the community of structural biology researchers. His former and current colleagues tell the story of his upbringing and education, followed by an account of his dedication to quality and rigor in crystallography and structural science. The FEBS Journal Editor-in-Chief Seamus Martin further highlights Alex's outstanding contributions to the journal's success over many years.

'All That Glitters Is Not Gold': High-Resolution Crystal Structures of Ligand-Protein Complexes Need Not Always Represent Confident Binding Poses

Our understanding of the structure–function relationships of biomolecules and thereby applying it to drug discovery programs are substantially dependent on the availability of the structural information of ligand–protein complexes. However, the correct interpretation of the electron density of a small molecule bound to a crystal structure of a macromolecule is not trivial. Our analysis involving quality assessment of ~0.28 million small molecule–protein binding site pairs derived from crystal structures corresponding to ~66,000 PDB entries indicates that the majority (65%) of the pairs might need little (54%) or no (11%) attention. Out of the remaining 35% of pairs that need attention, 11% of the pairs (including structures with high/moderate resolution) pose serious concerns. Unfortunately, most users of crystal structures lack the training to evaluate the quality of a crystal structure against its experimental data and, in general, rely on the resolution as a ‘gold standard’ quality metric. Our work aims to sensitize the non-crystallographers that resolution, which is a global quality metric, need not be an accurate indicator of local structural quality. In this article, we demonstrate the use of several freely available tools that quantify local structural quality and are easy to use from a non-crystallographer’s perspective. We further propose a few solutions for consideration by the scientific community to promote quality research in structural biology and applied areas.

Unlocking the PIP-box: A peptide library reveals interactions that drive high-affinity binding to human PCNA

The human sliding clamp, Proliferating Cell Nuclear Antigen (hPCNA), interacts with over 200 proteins through a conserved binding motif, the PIP-box, to orchestrate DNA replication and repair. It is not clear how changes to the features of a PIP-box modulate protein binding and thus how they fine-tune downstream processes. Here, we present a systematic study of each position within the PIP-box to reveal how hPCNA-interacting peptides bind with drastically varied affinities. We synthesized a series of 27 peptides derived from the native protein p21 with small PIP-box modifications and another series of 19 peptides containing PIP-box binding motifs from other proteins. The hPCNA-binding affinity of all peptides, characterized as K_D values determined by surface plasmon resonance, spanned a 4000-fold range, from 1.83 nM to 7.59 μM. The hPCNA-bound peptide structures determined by X-ray crystallography and modeled computationally revealed intermolecular and intramolecular interaction networks that correlate with high hPCNA affinity. These data informed rational design of three new PIP-box sequences, testing of which revealed the highest affinity hPCNA-binding partner to date, with a K_D value of 1.12 nM, from a peptide with PIP-box QTRITEYF. This work showcases the sequence-specific nuances within the PIP-box that are responsible for high-affinity hPCNA binding, which underpins our understanding of how nature tunes hPCNA affinity to regulate DNA replication and repair processes. In addition, these insights will be useful to future design of hPCNA inhibitors.

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.

How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations

We review recent advances in modeling structural ensembles of transcription factors from nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopic data, integrated with molecular dynamics (MD) simulations. We focus on approaches that confirm computed conformational ensembles by sparse constraints obtained from magnetic resonance. This combination enables the deduction of functional and structural protein models even if nuclear Overhauser effects (NOEs) are too scarce for conventional structure determination. We highlight recent insights into the folding-upon-DNA binding transitions of intrinsically disordered transcription factors that could be assessed using such integrative approaches.

On the Effect of the Various Assumptions and Approximations used in Molecular Simulations on the Properties of Bio-Molecular Systems: Overview and Perspective on Issues

Computer simulations of molecular systems enable structure-energy-function relationships of molecular processes to be described at the sub-atomic, atomic, supra-atomic or supra-molecular level and plays an increasingly important role in chemistry, biology and physics. To interpret the results of such simulations appropriately, the degree of uncertainty and potential errors affecting the calculated properties must be considered. Uncertainty and errors arise from (1) assumptions underlying the molecular model, force field and simulation algorithms, (2) approximations implicit in the interatomic interaction function (force field), or when integrating the equations of motion, (3) the chosen values of the parameters that determine the accuracy of the approximations used, and (4) the nature of the system and the property of interest. In this overview, advantages and shortcomings of assumptions and approximations commonly used when simulating bio-molecular systems are considered. What the developers of bio-molecular force fields and simulation software can do to facilitate and broaden research involving bio-molecular simulations is also discussed.

Deflating the RNA Mg2+ bubble. Stereochemistry to the rescue!

Proper evaluation of the ionic structure of biomolecular systems through X ray and cryo-EM techniques remains challenging but is essential for advancing our understanding of the underlying structure/activity/solvent relationships. However, numerous studies overestimate the number of Mg2+ in deposited structures due to assignment errors finding their origin in improper consideration of stereochemical rules. Herein, to tackle such issues, we re-evaluate the PDBid 6QNR and 6SJ6 models of the ribosome ionic structure. We establish that stereochemical principles need to be carefully pondered when evaluating ion binding features, even when K+ anomalous signals are available as it is the case for the 6QNR PDB entry. For ribosomes, assignment errors can result in misleading conceptions of their solvent structure. For instance, present stereochemical analysis result in a significant decrease of the number of assigned Mg2+ in 6QNR, suggesting that K+ and not Mg2+ is the prevalent ion in the ribosome 1st solvation shell. We stress that the use of proper stereochemical guidelines in combination or not with other identification techniques, such as those pertaining to the detection of transition metals, of some anions and of K+ anomalous signals, is critical for deflating the current Mg2+ bubble witnessed in many ribosome and other RNA structures. We also stress that for the identification of lighter ions such as Mg2+, Na+, …, for which no anomalous signals can be detected, stereochemistry coupled with high resolution structures (<2.4 Å) remain the best currently available option.

Enhancing Protein Crystallization under a Magnetic Field

High-quality crystals are essential to ensure high-resolution structural information. Protein crystals are controlled by many factors, such as pH, temperature, and the ion concentration of crystalline solutions. We previously reported the development of a device dedicated to protein crystallization. In the current study, we have further modified and improved our device. Exposure to external magnetic field leads to alignment of the crystal toward a preferred direction depending on the magnetization energy. Each material has different magnetic susceptibilities depending on the individual direction of their unit crystal cells. One of the strategies to acquire a large crystal entails controlling the nucleation rate. Furthermore, exposure of a crystal to a magnetic field may lead to new morphologies by affecting the crystal volume, shape, and quality.

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.

VIRdb: a comprehensive database for interactive analysis of genes/proteins involved in the pathogenesis of vitiligo

Vitiligo is a chronic asymptomatic disorder affecting melanocytes from the basal layer of the epidermis which leads to a patchy loss of skin color. Even though it is one of the neglected disease conditions, people suffering from vitiligo are more prone to psychological disorders. As of now, various studies have been done in order to project auto-immune implications as the root cause. To understand the complexity of vitiligo, we propose the Vitiligo Information Resource (VIRdb) that integrates both the drug-target and systems approach to produce a comprehensive repository entirely devoted to vitiligo, along with curated information at both protein level and gene level along with potential therapeutics leads. These 25,041 natural compounds are curated from Natural Product Activity and Species Source Database. VIRdb is an attempt to accelerate the drug discovery process and laboratory trials for vitiligo through the computationally derived potential drugs. It is an exhaustive resource consisting of 129 differentially expressed genes, which are validated through gene ontology and pathway enrichment analysis. We also report 22 genes through enrichment analysis which are involved in the regulation of epithelial cell differentiation. At the protein level, 40 curated protein target molecules along with their natural hits that are derived through virtual screening. We also demonstrate the utility of the VIRdb by exploring the Protein-Protein Interaction Network and Gene-Gene Interaction Network of the target proteins and differentially expressed genes. For maintaining the quality and standard of the data in the VIRdb, the gold standard in bioinformatics toolkits like Cytoscape, Schrödinger's GLIDE, along with the server installation of MATLAB, are used for generating results. VIRdb can be accessed through "http://www.vitiligoinfores.com/".

Inhibition in multicopper oxidases: a critical review

This review critiques the literature on inhibition of O₂-reduction catalysis in multicopper oxidases like laccase and bilirubin oxidase and provide recommendations for best practice when carrying out experiments and interpreting published data.

αKlotho-FGF23 interactions and their role in kidney disease: a molecular insight

Following the serendipitous discovery of the ageing suppressor, αKlotho (αKl), several decades ago, a growing body of evidence has defined a pivotal role for its various forms in multiple aspects of vertebrate physiology and pathology. The transmembrane form of αKl serves as a co-receptor for the osteocyte-derived mineral regulator, fibroblast growth factor (FGF)23, principally in the renal tubules. However, compelling data also suggest that circulating soluble forms of αKl, derived from the same source, may have independent homeostatic functions either as a hormone, glycan-cleaving enzyme or lectin. Chronic kidney disease (CKD) is of particular interest as disruption of the FGF23-αKl axis is an early and common feature of disease manifesting in markedly deficient αKl expression, but FGF23 excess. Here we critically discuss recent findings in αKl biology that conflict with the view that soluble αKl has substantive functions independent of FGF23 signalling. Although the issue of whether soluble αKl can act without FGF23 has yet to be resolved, we explore the potential significance of these contrary findings in the context of CKD and highlight how this endocrine pathway represents a promising target for novel anti-ageing therapeutics.

Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix

Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks.

Opportunistic complexes of E. coli L-asparaginases with citrate anions

Active sites of enzymes are highly optimized for interactions with specific substrates, thus binding of opportunistic ligands is usually observed only in the absence of native substrates or products. However, during growth of crystals required for structure determination enzymes are often exposed to conditions significantly divergent from the native ones, leading to binding of unexpected ligands to active sites even in the presence of substrates. Failing to recognize this possibility may lead to incorrect interpretation of experimental results and to faulty conclusions. Here, we present several examples of binding of a citrate anion to the active sites of E. coli L-asparaginases I and II, even in the presence of the native substrate, L-Asn. A part of this report focuses on a comprehensive re-interpretation of structural results published previously for complexes of type I L-asparaginase (EcAI) from E. coli. In two re-refined structures a citrate anion forms an acyl-enzyme reaction intermediate with the catalytic threonine. These results emphasize the importance of careful and critical analysis during interpretation of crystallographic data.

Nucleobase carbonyl groups are poor Mg2+ inner-sphere binders but excellent monovalent ion binders-a critical PDB survey

Precise knowledge of Mg²⁺ inner-sphere binding site properties is vital for understanding the structure and function of nucleic acid systems. Unfortunately, the PDB, which represents the main source of Mg²⁺ binding sites, contains a substantial number of assignment issues that blur our understanding of the functions of these ions. Here, following a previous study devoted to Mg²⁺ binding to nucleobase nitrogens, we surveyed nucleic acid X-ray structures from the PDB with resolutions ≤2.9 Å to classify the Mg²⁺ inner-sphere binding patterns to nucleotide carbonyl, ribose hydroxyl, cyclic ether, and phosphodiester oxygen atoms. From this classification, we derived a set of "prior-knowledge" nucleobase Mg²⁺ binding sites. We report that crystallographic examples of trustworthy nucleobase Mg²⁺ binding sites are fewer than expected since many of those are associated with misidentified Na⁺ or K⁺ We also emphasize that binding of Na⁺ and K⁺ to nucleic acids is much more frequent than anticipated. Overall, we provide evidence derived from X-ray structures that nucleobases are poor inner-sphere binders for Mg²⁺ but good binders for monovalent ions. Based on strict stereochemical criteria, we propose an extended set of guidelines designed to help in the assignment and validation of ions directly contacting nucleobase and ribose atoms. These guidelines should help in the interpretation of X-ray and cryo-EM solvent density maps. When borderline Mg²⁺ stereochemistry is observed, alternative placement of Na⁺, K⁺, or Ca²⁺ must be considered. We also critically examine the use of lanthanides (Yb³⁺, Tb³⁺) as Mg²⁺ substitutes in crystallography experiments.

An Augmented Pocketome: Detection and Analysis of Small-Molecule Binding Pockets in Proteins of Known 3D Structure

Protein-ligand interactions form the basis of most cellular events. Identifying ligand binding pockets in proteins will greatly facilitate rationalizing and predicting protein function. Ligand binding sites are unknown for many proteins of known three-dimensional (3D) structure, creating a gap in our understanding of protein structure-function relationships. To bridge this gap, we detect pockets in proteins of known 3D structures, using computational techniques. This augmented pocketome (PocketDB) consists of 249,096 pockets, which is about seven times larger than what is currently known. We deduce possible ligand associations for about 46% of the newly identified pockets. The augmented pocketome, when subjected to clustering based on similarities among pockets, yielded 2,161 site types, which are associated with 1,037 ligand types, together providing fold-site-type-ligand-type associations. The PocketDB resource facilitates a structure-based function annotation, delineation of the structural basis of ligand recognition, and provides functional clues for domains of unknown functions, allosteric proteins, and druggable pockets.

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.

Homology-based loop modeling yields more complete crystallographic protein structures

Inherent protein flexibility, poor or low-resolution diffraction data or poorly defined electron-density maps often inhibit the building of complete structural models during X-ray structure determination. However, recent advances in crystallographic refinement and model building often allow completion of previously missing parts. This paper presents algorithms that identify regions missing in a certain model but present in homologous structures in the Protein Data Bank (PDB), and 'graft' these regions of interest. These new regions are refined and validated in a fully automated procedure. Including these developments in the PDB-REDO pipeline has enabled the building of 24 962 missing loops in the PDB. The models and the automated procedures are publicly available through the PDB-REDO databank and webserver. More complete protein structure models enable a higher quality public archive but also a better understanding of protein function, better comparison between homologous structures and more complete data mining in structural bioinformatics projects.

Egress and invasion machinery of malaria: an in-depth look into the structural and functional features of the flap dynamics of plasmepsin IX and X

Plasmepsins, a family of aspartic proteases expressed by Plasmodium falciparum parasite, have been identified as key mediators in the onset of lethal malaria. Precedence has been placed on this family of enzymes due their essential role in the virulence of the parasite, thus highlighting their importance as novel drug targets. A previously published study by our group proposed a set of parameters used to define the flap motion of aspartic proteases. These parameters were used in the study of Plm I-V and focused on the flap flexibility as well as structural dynamics. Recent studies have highlighted the essential role played by Plm IX and X in egress and invasion of the malarial parasite. This study aims to close the gap on the latter family, investigating the flap dynamics of Plms IX and X. Molecular dynamics simulations demonstrated an "open and close" mechanism at the region of the catalytic site. Further computation of the dihedral angles at the catalytic region revealed tractability at both the flap tip and flexible loop. This structural versatility enhances the interaction of variant ligand sizes, in comparison to other Plm family members. The results obtained from this study signify the essential role of structural flap dynamics and its resultant effect on the binding landscapes of Plm IX and X. We believe that this unique structural mechanism may be integrated in the design and development of effective anti-malarial drugs.

ISOLDE: a physically realistic environment for model building into low-resolution electron-density maps

This paper introduces ISOLDE, a new software package designed to provide an intuitive environment for high-fidelity interactive remodelling/refinement of macromolecular models into electron-density maps. ISOLDE combines interactive molecular-dynamics flexible fitting with modern molecular-graphics visualization and established structural biology libraries to provide an immersive interface wherein the model constantly acts to maintain physically realistic conformations as the user interacts with it by directly tugging atoms with a mouse or haptic interface or applying/removing restraints. In addition, common validation tasks are accelerated and visualized in real time. Using the recently described 3.8 Å resolution cryo-EM structure of the eukaryotic minichromosome maintenance (MCM) helicase complex as a case study, it is demonstrated how ISOLDE can be used alongside other modern refinement tools to avoid common pitfalls of low-resolution modelling and improve the quality of the final model. A detailed analysis of changes between the initial and final model provides a somewhat sobering insight into the dangers of relying on a small number of validation metrics to judge the quality of a low-resolution model.

Revealing the architecture of protein complexes by an orthogonal approach combining HDXMS, CXMS, and disulfide trapping

Many cellular functions necessitate structural assemblies of two or more associated proteins. The structural characterization of protein complexes using standard methods, such as X-ray crystallography, is challenging. Herein, we describe an orthogonal approach using hydrogen-deuterium-exchange mass spectrometry (HDXMS), cross-linking mass spectrometry (CXMS), and disulfide trapping to map interactions within protein complexes. HDXMS measures changes in solvent accessibility and hydrogen bonding upon complex formation; a decrease in HDX rate could account for newly formed intermolecular or intramolecular interactions. To distinguish between inter- and intramolecular interactions, we use a CXMS method to determine the position of direct interface regions by trapping intermolecular residues in close proximity to various cross-linkers (e.g., disuccinimidyl adipate (DSA)) of different lengths and reactive groups. Both MS-based experiments are performed on high-resolution mass spectrometers (e.g., an Orbitrap Elite hybrid mass spectrometer). The physiological relevance of the interactions identified through HDXMS and CXMS is investigated by transiently co-expressing cysteine mutant pairs, one mutant on each protein at the discovered interfaces, in an appropriate cell line, such as HEK293. Disulfide-trapped protein complexes are formed within cells spontaneously or are facilitated by addition of oxidation reagents such as H₂O₂ or diamide. Western blotting analysis, in the presence and absence of reducing reagents, is used to determine whether the disulfide bonds are formed in the proposed complex interface in physiologically relevant milieus. The procedure described here requires 1-2 months. We demonstrate this approach using the β2-adrenergic receptor-β-arrestin1 complex as the model system.

Assigning crystallographic electron densities with free energy calculations-The case of the fluoride channel Fluc

Approximately 90% of the structures in the Protein Data Bank (PDB) were obtained by X-ray crystallography or electron microscopy. Whereas the overall quality of structure is considered high, thanks to a wide range of tools for structure validation, uncertainties may arise from density maps of small molecules, such as organic ligands, ions or water, which are non-covalently bound to the biomolecules. Even with some experience and chemical intuition, the assignment of such disconnected electron densities is often far from obvious. In this study, we suggest the use of molecular dynamics (MD) simulations and free energy calculations, which are well-established computational methods, to aid in the assignment of ambiguous disconnected electron densities. Specifically, estimates of (i) relative binding affinities, for instance between an ion and water, (ii) absolute binding free energies, i.e., free energies for transferring a solute from bulk solvent to a binding site, and (iii) stability assessments during equilibrium simulations may reveal the most plausible assignments. We illustrate this strategy using the crystal structure of the fluoride specific channel (Fluc), which contains five disconnected electron densities previously interpreted as four fluoride and one sodium ion. The simulations support the assignment of the sodium ion. In contrast, calculations of relative and absolute binding free energies as well as stability assessments during free MD simulations suggest that four of the densities represent water molecules instead of fluoride. The assignment of water is compatible with the loss of these densities in the non-conductive F82I/F85I mutant of Fluc. We critically discuss the role of the ion force fields for the calculations presented here. Overall, these findings indicate that MD simulations and free energy calculations are helpful tools for modeling water and ions into crystallographic density maps.

Combining X-Ray Crystallography with Small Angle X-Ray Scattering to Model Unstructured Regions of Nsa1 from S. Cerevisiae

Determination of the full-length structure of ribosome assembly factor Nsa1 from Saccharomyces cerevisiae (S. cerevisiae) is challenging because of the disordered and protease labile C-terminus of the protein. This manuscript describes the methods to purify recombinant Nsa1 from S. cerevisiae for structural analysis by both X-ray crystallography and SAXS. X-ray crystallography was utilized to solve the structure of the well-ordered N-terminal WD40 domain of Nsa1, and then SAXS was used to resolve the structure of the C-terminus of Nsa1 in solution. Solution scattering data was collected from full-length Nsa1 in solution. The theoretical scattering amplitudes were calculated from the high-resolution crystal structure of the WD40 domain, and then a combination of rigid body and ab initio modeling revealed the C-terminus of Nsa1. Through this hybrid approach the quaternary structure of the entire protein was reconstructed. The methods presented here should be generally applicable for the hybrid structural determination of other proteins composed of a mix of structured and unstructured domains.

Validation of Molecular Simulation: An Overview of Issues

Computer simulation of molecular systems enables structure-energy-function relationships of molecular processes to be described at the sub-atomic, atomic, supra-atomic, or supra-molecular level. To interpret results of such simulations appropriately, the quality of the calculated properties must be evaluated. This depends on the way the simulations are performed and on the way they are validated by comparison to values Q^exp of experimentally observable quantities Q. One must consider 1) the accuracy of Q^exp , 2) the accuracy of the function Q(r^N ) used to calculate a Q-value based on a molecular configuration r^N of N particles, 3) the sensitivity of the function Q(r^N ) to the configuration r^N , 4) the relative time scales of the simulation and experiment, 5) the degree to which the calculated and experimental properties are equivalent, and 6) the degree to which the system simulated matches the experimental conditions. Experimental data is limited in scope and generally corresponds to averages over both time and space. A critical analysis of the various factors influencing the apparent degree of (dis)agreement between simulations and experiment is presented and illustrated using examples from the literature. What can be done to enhance the validation of molecular simulation is also discussed.

Cryo-EM: beyond the microscope

The pace at which cryo-EM is being adopted as a mainstream tool in structural biology has continued unabated over the past year. Initial successes in obtaining near-atomic resolution structures with cryo-EM were enabled to a large extent by advances in microscope and detector technology. Here, we review some of the complementary technical improvements that are helping sustain the cryo-EM revolution. We highlight advances in image processing that permit high resolution structure determination even in the presence of structural and conformational heterogeneity. We also review selected examples where biochemical strategies for membrane protein stabilization facilitate cryo-EM structure determination, and discuss emerging approaches for further improving the preparation of reliable plunge-frozen specimens.

Molecular modeling of biomolecules by paramagnetic NMR and computational hybrid methods

The 3D atomic structures of biomolecules and their complexes are key to our understanding of biomolecular function, recognition, and mechanism. However, it is often difficult to obtain structures, particularly for systems that are complex, dynamic, disordered, or exist in environments like cell membranes. In such cases sparse data from a variety of paramagnetic NMR experiments offers one possible source of structural information. These restraints can be incorporated in computer modeling algorithms that can accurately translate the sparse experimental data into full 3D atomic structures. In this review, we discuss various types of paramagnetic NMR/computational hybrid modeling techniques that can be applied to successful modeling of not only the atomic structure of proteins but also their interacting partners. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.

Resolving the cofactor-binding site in the proline biosynthetic enzyme human pyrroline-5-carboxylate reductase 1

Pyrroline-5-carboxylate reductase (PYCR) is the final enzyme in proline biosynthesis, catalyzing the NAD(P)H-dependent reduction of Δ1-pyrroline-5-carboxylate (P5C) to proline. Mutations in the PYCR1 gene alter mitochondrial function and cause the connective tissue disorder cutis laxa. Furthermore, PYCR1 is overexpressed in multiple cancers, and the PYCR1 knock-out suppresses tumorigenic growth, suggesting that PYCR1 is a potential cancer target. However, inhibitor development has been stymied by limited mechanistic details for the enzyme, particularly in light of a previous crystallographic study that placed the cofactor-binding site in the C-terminal domain rather than the anticipated Rossmann fold of the N-terminal domain. To fill this gap, we report crystallographic, sedimentation-velocity, and kinetics data for human PYCR1. Structures of binary complexes of PYCR1 with NADPH or proline determined at 1.9 Å resolution provide insight into cofactor and substrate recognition. We see NADPH bound to the Rossmann fold, over 25 Å from the previously proposed site. The 1.85 Å resolution structure of a ternary complex containing NADPH and a P5C/proline analog provides a model of the Michaelis complex formed during hydride transfer. Sedimentation velocity shows that PYCR1 forms a concentration-dependent decamer in solution, consistent with the pentamer-of-dimers assembly seen crystallographically. Kinetic and mutational analysis confirmed several features seen in the crystal structure, including the importance of a hydrogen bond between Thr-238 and the substrate as well as limited cofactor discrimination.

Mg2+ ions: do they bind to nucleobase nitrogens?

Given the many roles proposed for Mg2+ in nucleic acids, it is essential to accurately determine their binding modes. Here, we surveyed the PDB to classify Mg2+ inner-sphere binding patterns to nucleobase imine N1/N3/N7 atoms. Among those, purine N7 atoms are considered to be the best nucleobase binding sites for divalent metals. Further, Mg2+ coordination to N7 has been implied in several ribozyme catalytic mechanisms. We report that Mg2+ assigned near imine nitrogens derive mostly from poor interpretations of electron density patterns and are most often misidentified Na+, K+, NH4+ ions, water molecules or spurious density peaks. Consequently, apart from few documented exceptions, Mg2+ ions do not bind to N7 atoms. Without much of a surprise, Mn2+, Zn2+ and Cd2+, which have a higher affinity for nitrogens, may contact N7 atoms when present in crystallization buffers. In this respect, we describe for the first time a potential Zn2+ ribosomal binding site involving two purine N7 atoms. Further, we provide a set of guidelines to help in the assignment of Mg2+ in crystallographic, cryo-EM, NMR and model building practices and discuss implications of our findings related to ion substitution experiments.