Protein crystallography for non-crystallographers, or how to get the best (but not more) from published macromolecular structures

Rational design of monomeric IL37 variants guided by stability and dynamical analyses of IL37 dimers

IL37 plays important roles in the regulation of innate immunity and its oligomeric status is critical to these roles. In its monomeric state, IL37 can effectively inhibit the inflammatory response of IL18 by binding to IL18Rα, a capacity lost in its dimeric form, underlining the pivotal role of the oligomeric status of IL37 in its anti-inflammatory action. Until now, two IL37 dimer structures have been deposited in PDB, reflecting a substantial difference in their dimer interfaces. Given this discrepancy, we analyzed the PDB structures of the IL37 dimer (PDB IDs: 6ncu, 5hn1) along with a AF2-multimer prediction by molecular dynamics (MD) simulations. Results showed that the 5hn1 and AF2-predicted dimers have the same interface and stably maintained their conformations throughout simulations, while the recent IL37 dimer (PDB ID: 6ncu) with a different interface did not, proposing a possible issue with the recent IL37 dimer structure (6ncu). Next, focusing on the stable dimer structures, we have identified five critical positions of V71/Y85/I86/E89/S114, three new positions compared to the literature, that would reduce dimer stability without affecting the monomer structure. Two quintuple mutants were tested by MD simulations and showed partial or complete dissociation of the dimer. Overall, the insights gained from this study reinforce the validity of the 5hn1 and AF2 multimer structures, while also advancing our understanding of the IL37 dimer interface through the generation of monomer-locked IL37 variants.

Robust and automatic beamstop shadow outlier rejection: combining crystallographic statistics with modern clustering under a semi-supervised learning strategy

During the automatic processing of crystallographic diffraction experiments, beamstop shadows are often unaccounted for or only partially masked. As a result of this, outlier reflection intensities are integrated, which is a known issue. Traditional statistical diagnostics have only limited effectiveness in identifying these outliers, here termed Not-Excluded-unMasked-Outliers (NEMOs). The diagnostic tool AUSPEX allows visual inspection of NEMOs, where they form a typical pattern: clusters at the low-resolution end of the AUSPEX plots of intensities or amplitudes versus resolution. To automate NEMO detection, a new algorithm was developed by combining data statistics with a density-based clustering method. This approach demonstrates a promising performance in detecting NEMOs in merged data sets without disrupting existing data-reduction pipelines. Re-refinement results indicate that excluding the identified NEMOs can effectively enhance the quality of subsequent structure-determination steps. This method offers a prospective automated means to assess the efficacy of a beamstop mask, as well as highlighting the potential of modern pattern-recognition techniques for automating outlier exclusion during data processing, facilitating future adaptation to evolving experimental strategies.

Structural characterization of green fluorescent protein in the I-state

Green fluorescent protein (GFP) is widely utilized as a fluorescent tag in biochemical fields. Whereas the intermediate (I) state has been proposed in the photoreaction cycle in addition to the A and B states, until now the structure of I has only been estimated by computational studies. In this paper, we report the crystal structures of the I stabilizing variants of GFP at high resolutions where respective atoms can be observed separately. Comparison with the structures in the other states highlights the structural feature of the I state. The side chain of one of the substituted residues, Val203, adopts the gauche- conformation observed for Thr203 in the A state, which is different from the B state. On the other hand, His148 interacts with the chromophore by ordinary hydrogen bonding with a distance of 2.85 Å, while the weaker interaction by longer distances is observed in the A state. Therefore, it was indicated that it is possible to distinguish three states A, B and I by the two hydrogen bond distances Oγ-Thr203···Oη-chromophore and Nδ1-His148···Oη-chromophore. We discuss the characteristics of the I intermediate of wild-type GFP on the bases of the structure estimated from the variant structures by quantum chemical calculations.

ARCIMBOLDO at low resolution: Verification for coiled coils and globular proteins

Crystallography at low resolution must determine the atomic model from less experimental observations, which is challenging in the absence of a model. In addition, model bias is more severe when independent experimental data are scarce. Our methods solve the phase problem by combining the location of accurate model fragments using Phaser with density modification and interpretation of the resulting maps using SHELXE. From a partial, correct structure, the density modification process and the stereochemical constraints draw the rest of the structure, validating the result. This same principle is now exploited at low resolution. Coiled coils are important, ubiquitous structures but notoriously difficult to phase and to predict. Both correct solutions and incorrect ones are poorly discriminated by the crystallographic figures of merit as long as helices are correctly oriented. We incorporate coiled-coil verification, designed to set up competing, incompatible structural hypotheses to probe both the results and establish the power of the data to discriminate them. Efficiency of coiled-coil phasing and validation in test cases from 3 to 4 Å is demonstrated in ARCIMBOLDO_LITE, placing single helices, and in ARCIMBOLDO_SHREDDER, with fragments derived from AlphaFold models. SHELXE tracing at low resolution has been enhanced, maintaining its local character but extending the environment assessment. For non-helical structures, verification is demonstrated in the fragment location process. Its use is exemplified with the solution of the VSR1 structure at 3.5 Å, depending on LLG optimization and the emergence of new features in the electron density. Relying on verification, we have extended the use of the ARCIMBOLDO software to low resolution.

In situ serial crystallography facilitates 96-well plate structural analysis at low symmetry

The advent of serial crystallography has rejuvenated and popularized room-temperature X-ray crystal structure determination. Structures determined at physiological temperature reveal protein flexibility and dynamics. In addition, challenging samples (e.g. large complexes, membrane proteins and viruses) form fragile crystals that are often difficult to harvest for cryo-crystallography. Moreover, a typical serial crystallography experiment requires a large number of microcrystals, mainly achievable through batch crystallization. Many medically relevant samples are expressed in mammalian cell lines, producing a meager quantity of protein that is incompatible with batch crystallization. This can limit the scope of serial crystallography approaches. Direct in situ data collection from a 96-well crystallization plate enables not only the identification of the best diffracting crystallization condition but also the possibility for structure determination under ambient conditions. Here, we describe an in situ serial crystallography (iSX) approach, facilitating direct measurement from crystallization plates mounted on a rapidly exchangeable universal plate holder deployed at a microfocus beamline, ID23-2, at the European Synchrotron Radiation Facility. We applied our iSX approach on a challenging project, autotaxin, a therapeutic target expressed in a stable human cell line, to determine the structure in the lowest-symmetry P1 space group at 3.0 Å resolution. Our in situ data collection strategy provided a complete dataset for structure determination while screening various crystallization conditions. Our data analysis reveals that the iSX approach is highly efficient at a microfocus beamline, improving throughput and demonstrating how crystallization plates can be routinely used as an alternative method of presenting samples for serial crystallography experiments at synchrotrons.

CheckMyMetal (CMM): validating metal-binding sites in X-ray and cryo-EM data

Identifying and characterizing metal-binding sites (MBS) within macromolecular structures is imperative for elucidating their biological functions. CheckMyMetal (CMM) is a web based tool that facilitates the interactive validation of MBS in structures determined through X-ray crystallography and cryo-electron microscopy (cryo-EM). Recent updates to CMM have significantly enhanced its capability to efficiently handle large datasets generated from cryo-EM structural analyses. In this study, we address various challenges inherent in validating MBS within both X-ray and cryo-EM structures. Specifically, we examine the difficulties associated with accurately identifying metals and modeling their coordination environments by considering the ongoing reproducibility challenges in structural biology and the critical importance of well annotated, high-quality experimental data. CMM employs a sophisticated framework of rules rooted in the valence bond theory for MBS validation. We explore how CMM validation parameters correlate with the resolution of experimentally derived structures of macromolecules and their complexes. Additionally, we showcase the practical utility of CMM by analyzing a representative cryo-EM structure. Through a comprehensive examination of experimental data, we demonstrate the capability of CMM to advance MBS characterization and identify potential instances of metal misassignment.

Energy filtering enables macromolecular MicroED data at sub-atomic resolution

High resolution information is important for accurate structure modelling. However, this level of detail is typically difficult to attain in macromolecular crystallography because the diffracted intensities rapidly fade with increasing resolution. The problem cannot be circumvented by increasing the fluence as this leads to detrimental radiation damage. Previously, we demonstrated that high quality MicroED data can be obtained at low flux conditions using electron counting with direct electron detectors. The improved sensitivity and accuracy of these detectors essentially eliminate the read-out noise, such that the measurement of faint high-resolution reflections is limited by other sources of noise. Inelastic scattering is a major contributor of such noise, increasing background counts and broadening diffraction spots. Here, we demonstrate that a substantial improvement in signal-to-noise ratio can be achieved using an energy filter to largely remove the inelastically scattered electrons. This strategy resulted in sub-atomic resolution MicroED data from proteinase K crystals, enabling accurate structure modelling and the visualization of detailed features. Interestingly, filtering out the noise revealed diffuse scattering phenomena that can hold additional structural information. Our findings suggest that combining energy filtering and electron counting can provide more accurate measurements at higher resolution, providing better insights into protein function and facilitating more precise model refinement.

FitScore: a fast machine learning-based score for 3D virtual screening enrichment

Enhancing virtual screening enrichment has become an urgent problem in computational chemistry, driven by increasingly large databases of commercially available compounds, without a commensurate drop in in vitro screening costs. Docking these large databases is possible with cloud-scale computing. However, rapid docking necessitates compromises in scoring, often leading to poor enrichment and an abundance of false positives in docking results. This work describes a new scoring function composed of two parts - a knowledge-based component that predicts the probability of a particular atom type being in a particular receptor environment, and a tunable weight matrix that converts the probability predictions into a dimensionless score suitable for virtual screening enrichment. This score, the FitScore, represents the compatibility between the ligand and the binding site and is capable of a high degree of enrichment across standardized docking test sets.

A Structure-Activity Investigation of the Fungal Metabolite (-)-TAN-2483B: Inhibition of Bruton's Tyrosine Kinase

The natural product (-)-TAN-2483B is a fungal secondary metabolite which displays promising anti-cancer and immunomodulatory activity. Our previous syntheses of (-)-TAN-2483B and sidechain analogues uncovered inhibitory activity against Bruton's tyrosine kinase (Btk), an established drug target for various leukaemia and immunological diseases. A structure-based computational study using ensemble docking and molecular dynamics was performed to determine plausible binding modes for (-)-TAN-2483B and analogues in the Btk binding site. These hypotheses guided the design of new analogues which were synthesised and their inhibitory activities determined, providing insights into the structural determinants of the furopyranone scaffold that confer both activity and selectivity for Btk. These findings offer new perspectives for generating optimised (-)-TAN-2483B-based kinase inhibitors for the treatment of leukaemia and immunological diseases.

Opportunities for Insight into the Mechanism of Efficient CO2/CO Interconversion at a Nickel-Iron Cluster in CO Dehydrogenase

The reduction of CO2 with low overpotential and high selectivity is a crucial challenge in catalysis. Fortunately, natural systems have evolved enzymes that achieve this catalytic reaction very efficiently at a complex nickel-iron-sulfur cluster within carbon monoxide dehydrogenase (CODH). Extensive biochemical, crystallographic, and spectroscopic work has been done to understand the structures and mechanism involved in the catalytic cycle, which are summarized here from the perspective of mechanistic organometallic chemistry. We highlight the ambiguities in the data and suggest experiments that could lead to clearer understanding of the mechanism and structures of intermediates at the active-site cluster. These include parallel crystallography and spectroscopy, as well as the preparation of synthetic analogues that help to interpret structural and spectroscopic signatures.

Protein3D: Enabling analysis and extraction of metal-containing sites from the Protein Data Bank with molSimplify

Metalloenzymes catalyze a wide range of chemical transformations, with the active site residues playing a key role in modulating chemical reactivity and selectivity. Unlike smaller synthetic catalysts, a metalloenzyme active site is embedded in a larger protein, which makes interrogation of electronic properties and geometric features with quantum mechanical calculations challenging. Here we implement the ability to fetch crystallographic structures from the Protein Data Bank and analyze the metal binding sites in the program molSimplify. We show the usefulness of the newly created protein3D class to extract the local environment around non-heme iron enzymes containing a two histidine motif and prepare 372 structures for quantum mechanical calculations. Our implementation of protein3D serves to expand the range of systems molSimplify can be used to analyze and will enable high-throughput study of metal-containing active sites in proteins.

Characterisation of the heme aqua-ligand coordination environment in an engineered peroxygenase cytochrome P450 variant

The cytochrome P450 enzymes (CYPs) are heme-thiolate monooxygenases that catalyse the insertion of an oxygen atom into the C-H bonds of organic molecules. In most CYPs, the activation of dioxygen by the heme is aided by an acid-alcohol pair of residues located in the I-helix of the enzyme. Mutation of the threonine residue of this acid-alcohol pair of CYP199A4, from the bacterium Rhodospeudomonas palustris HaA2, to a glutamate residue induces peroxygenase activity. In the X-ray crystal structures of this variant an interaction of the glutamate side chain and the distal aqua ligand of the heme was observed and this results in this ligand not being readily displaced in the peroxygenase mutant on the addition of substrate. Here we use a range of bulky hydrophobic and nitrogen donor containing ligands in an attempt to displace the distal aqua ligand of the T252E mutant of CYP199A4. Ligand binding was assessed by UV-visible absorbance spectroscopy, native mass spectrometry, electron paramagnetic resonance and X-ray crystallography. None of the ligands tested, even the nitrogen donor ligands which bind directly to the iron in the wild-type enzyme, resulted in displacement of the aqua ligand. Therefore, modification of the I-helix threonine residue to a glutamate residue results in a significant strengthening of the ferric distal aqua ligand. This ligand was not displaced using any of the ligands during this study and this provides a rationale as to why this mutant can shutdown the monooxygenase pathway of this enzyme and switch to peroxygenase activity.

Phylogenetic and Protein Structure Analyses Provide Insight into the Evolution and Diversification of the CD36 Domain "Apex" among Scavenger Receptor Class B Proteins across Eukarya

The cluster of differentiation 36 (CD36) domain defines the characteristic ectodomain associated with class B scavenger receptor (SR-B) proteins. In bilaterians, SR-Bs play critical roles in diverse biological processes including innate immunity functions such as pathogen recognition and apoptotic cell clearance, as well as metabolic sensing associated with fatty acid uptake and cholesterol transport. Although previous studies suggest this protein family is ancient, SR-B diversity across Eukarya has not been robustly characterized. We analyzed SR-B homologs identified from the genomes and transcriptomes of 165 diverse eukaryotic species. The presence of highly conserved amino acid motifs across major eukaryotic supergroups supports the presence of a SR-B homolog in the last eukaryotic common ancestor. Our comparative analyses of SR-B protein structure identify the retention of a canonical asymmetric beta barrel tertiary structure within the CD36 ectodomain across Eukarya. We also identify multiple instances of independent lineage-specific sequence expansions in the apex region of the CD36 ectodomain-a region functionally associated with ligand-sensing. We hypothesize that a combination of both sequence expansion and structural variation in the CD36 apex region may reflect the evolution of SR-B ligand-sensing specificity between diverse eukaryotic clades.

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.

New insight into the traditional model of the coagulation cascade and its regulation: illustrated review of a three-dimensional view

The coagulation process relies on an intricate network of three-dimensional structural interactions and subtle biological regulations. In the present review, we illustrate the state of the art of the structural biology of the coagulation cascade by surveying the Protein Data Bank and the EBI AlphaFold databases. Investigations performed in the last decade have provided structural information on essentially all players involved in the process. Indeed, the initial characterization of specific and rather canonical domains has been progressively extended to complicated multidomain proteins. Recently, the application of cryogenic electron microscopy techniques has unraveled the structural features of highly complex coagulation factors, which has led to enhanced understanding. This review initially focuses on the structure of the individual factors as a function of their involvement in intrinsic, extrinsic, and common pathways. A specific emphasis is given to what is known or unknown on the structural basis of each step of the cascade. Available data providing clues on the structural recognition of the factors involved in the functional partnerships of the pathways are illustrated. Recent structures of important complexes formed by these proteins with regulators are described, focusing on the drugs used as anticoagulants and on their reversal agents. Finally, we highlight the different roles that innovative biomolecules such as aptamers may have in the regulation of the cascade.

Binding site plasticity regulation of the FimH catch-bond mechanism

The bacterial fimbrial adhesin FimH is a remarkable and well-studied catch-bond protein found at the tip of E. coli type 1 pili, which allows pathogenic strains involved in urinary tract infections to bind high-mannose glycans exposed on human epithelia. The catch-bond behavior of FimH, where the strength of the interaction increases when a force is applied to separate the two partners, enables the bacteria to resist clearance when they are subjected to shear forces induced by urine flow. Two decades of experimental studies performed at the single-molecule level, as well as x-ray crystallography and modeling studies, have led to a consensus picture whereby force separates the binding domain from an inhibitor domain, effectively triggering an allosteric conformational change in the former. This force-induced allostery is thought to be responsible for an increased binding affinity at the core of the catch-bond mechanism. However, some important questions remain, the most challenging one being that the crystal structures corresponding to these two allosteric states show almost superimposable binding site geometries, which questions the molecular origin for the large difference in affinity. Using molecular dynamics with a combination of enhanced-sampling techniques, we demonstrate that the static picture provided by the crystal structures conceals a variety of binding site conformations that have a key impact on the apparent affinity. Crucially, the respective populations in each of these conformations are very different between the two allosteric states of the binding domain, which can then be related to experimental affinity measurements. We also evidence a previously unappreciated but important effect: in addition to the well-established role of the force as an allosteric regulator via domain separation, application of force tends to directly favor the high-affinity binding site conformations. We hypothesize that this additional "local" catch-bond effect could delay unbinding between the bacteria and the host cell before the "global" allosteric transition occurs, as well as stabilizing the complex even more once in the high-affinity allosteric 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.

Modelling SARS-CoV-2 spike-protein mutation effects on ACE2 binding

The binding affinity of the SARS-CoV-2 spike (S)-protein to the human membrane protein ACE2 is critical for virus function. Computational structure-based screening of new S-protein mutations for ACE2 binding lends promise to rationalize virus function directly from protein structure and ideally aid early detection of potentially concerning variants. We used a computational protocol based on cryo-electron microscopy structures of the S-protein to estimate the change in ACE2-affinity due to S-protein mutation (ΔΔG_bind) in good trend agreement with experimental ACE2 affinities. We then expanded predictions to all possible S-protein mutations in 21 different S-protein-ACE2 complexes (400,000 ΔΔG_bind data points in total), using mutation group comparisons to reduce systematic errors. The results suggest that mutations that have arisen in major variants as a group maintain ACE2 affinity significantly more than random mutations in the total protein, at the interface, and at evolvable sites. Omicron mutations as a group had a modest change in binding affinity compared to mutations in other major variants. The single-mutation effects seem consistent with ACE2 binding being optimized and maintained in omicron, despite increased importance of other selection pressures (antigenic drift), however, epistasis, glycosylation and in vivo conditions will modulate these effects. Computational prediction of SARS-CoV-2 evolution remains far from achieved, but the feasibility of large-scale computation is substantially aided by using many structures and mutation groups rather than single mutation effects, which are very uncertain. Our results demonstrate substantial challenges but indicate ways forward to improve the quality of computer models for assessing SARS-CoV-2 mutation effects.

Continuous Validation Across Macromolecular Structure Determination Process

The overall quality of the experimentally determined structures contained in the PDB is exceptionally high, mainly due to the continuous improvement of model building and structural validation programs. Improving reproducibility on a large scale requires expanding the concept of validation in structural biology and all other disciplines to include a broader framework that encompasses the entire project. A successful approach to science requires diligent attention to detail and a focus on the future. An earnest commitment to data availability and reuse is essential for scientific progress, be that by human minds or artificial intelligence.

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.

In Silico and In Vitro Antiviral Activity Evaluation of Prodigiosin from Serratia marcescens Against Enterovirus 71

Prodigiosin, a red linear tripyrrole pigment found in Serratia marcescens, is one such naturally occurring compound that has gained wide attention owing to its numerous biological activities, including antibacterial, antifungal, antimalarial, anticancer, and immunosuppressive properties. This study was conducted to evaluate the possible antiviral activity of prodigiosin against Enterovirus 71, a causative agent of hand, foot, and mouth disease (HFMD). Preliminary studies were done in silico by analyzing the interaction of prodigiosin with amino acid residues of five EV71-target proteins. Interaction refinement analysis with FireDock revealed that 2C helicase (-48.01 kcal/moL) has the most negative global energy, followed by capsid (-36.52 kcal/moL), 3C protease (-34.16 kcal/moL), 3D RNA polymerase (-30.93 kcal/moL) and 2A protease (-20.61 kcal/moL). These values are indicative of the interaction strength. Prodigiosin was shown to form chemical bonds with specific amino acid residues in capsid (Gln-30, Asn-223), 2A protease (Trp-33, Trp-142), 2C helicase (Tyr-150, His-151, Gln-169, Ser-212), 3C protease (Glu-50), and 3D RNA polymerase (Ala-239, Tyr-237). To investigate further, prodigiosin was extracted from S. marcescens using a methanolic extraction method. In vitro studies revealed that prodigiosin, with an IC50 value of 0.5112 μg/mL, reduced virus titers by 0.17 log (32.39%) in 30 min and 0.19 log (35.43%) in 60 min. The findings suggest that prodigiosin has antiviral activity with an intermediate inhibitory effect against EV71. As a result of this research, new biological activities of prodigiosin have been identified.

Pea and lentil 7S globulin crystal structures with comparative immunoglobulin epitope mapping

Legumes represent an affordable high protein, nutrient dense food source. However, the vast majority of legume crops contain proteins that are known allergens for susceptible individuals. These include proteins from the 7S globulin family, which comprise a vast majority of seed storage proteins. Here, the crystal structures of 7S globulins from Pisum sativum L. (pea) and Lens culinaris Medicus (lentil) are presented for the first time, including pea vicillin and convicilin, and lentil vicilin. All three structures maintain the expected 7S globulin fold, with trimeric quaternary structure and monomers comprised of β-barrel N- and C-modules. The potential impact of sequence differences on structure and packing in the different crystal space groups is noted, with potential relevance to packing upon seed deposition. Mapping on the obtained crystal structures highlights significant Ig epitope overlap between pea, lentil, peanut and soya bean and significant coverage of the entire seed storage protein, emphasizing the challenge in addressing food allergies. How recently developed biologicals might be refined to be more effective, or how these seed storage proteins might be modified in planta to be less immuno-reactive remain challenges for the future. With legumes representing an affordable, high protein, nutrient dense food source, this work will enable important research in the context of global food security and human health on an ongoing basis.

G-quadruplex DNA: A Longer Story

G-quadruplexes (G4s) are distinctive four-stranded DNA or RNA structures found within cells that are thought to play functional roles in gene regulation and transcription, translation, recombination, and DNA damage/repair. While G4 structures can be uni-, bi-, or tetramolecular with respect to strands, folded unimolecular conformations are most significant in vivo. Unimolecular G4 can potentially form in sequences with runs of guanines interspersed with what will become loops in the folded structure: 5'G_xL_yG_xL_yG_xL_yG_x, where x is typically 2-4 and y is highly variable. Such sequences are highly conserved and specifically located in genomes. In the folded structure, guanines from each run combine to form planar tetrads with four hydrogen-bonded guanine bases; these tetrads stack on one another to produce four strand segments aligned in specific parallel or antiparallel orientations, connected by the loop sequences. Three types of loops (lateral, diagonal, or "propeller") have been identified. The stacked tetrads form a central cavity that features strong coordination sites for monovalent cations that stabilize the G4 structure, with potassium or sodium preferred. A single monomeric G4 typically forms from a sequence containing roughly 20-30 nucleotides. Such short sequences have been the primary focus of X-ray crystallographic or NMR studies that have produced high-resolution structures of a variety of monomeric G4 conformations. These structures are often used as the basis for drug design efforts to modulate G4 function.We believe that the focus on monomeric G4 structures formed by such short sequences is perhaps myopic. Such short sequences for structural studies are often arbitrarily selected and removed from their native genomic sequence context, and then are often changed from their native sequences by base substitutions or deletions intended to optimize the formation of a homogeneous G4 conformation. We believe instead that G-quadruplexes prefer company and that in a longer natural sequence context multiple adjacent G4 units can form to combine into more complex multimeric G4 structures with richer topographies than simple monomeric forms. Bioinformatic searches of the human genome show that longer sequences with the potential for forming multiple G4 units are common. Telomeric DNA, for example, has a single-stranded overhang of hundreds of nucleotides with the requisite repetitive sequence with the potential for formation of multiple G4s. Numerous extended promoter sequences have similar potentials for multimeric G4 formation. X-ray crystallography and NMR methods are challenged by these longer sequences (>30 nt), so other tools are needed to explore the possible multimeric G4 landscape. We have implemented an integrated structural biology approach to address this challenge. This approach integrates experimental biophysical results with atomic-level molecular modeling and molecular dynamics simulations that provide quantitatively testable model structures. In every long sequence we have studied so far, we found that multimeric G4 structures readily form, with a surprising diversity of structures dependent on the exact native sequence used. In some cases, stable hairpin duplexes form along with G4 units to provide an even richer landscape. This Account provides an overview of our approach and recent progress and provides a new perspective on the G-quadruplex folding landscape.

Structural heterogeneity and precision of implications drawn from cryo-electron microscopy structures: SARS-CoV-2 spike-protein mutations as a test case

Protein structures may be used to draw functional implications at the residue level, but how sensitive are these implications to the exact structure used? Calculation of the effects of SARS-CoV-2 S-protein mutations based on experimental cryo-electron microscopy structures have been abundant during the pandemic. To understand the precision of such estimates, we studied three distinct methods to estimate stability changes for all possible mutations in 23 different S-protein structures (3.69 million ΔΔG values in total) and explored how random and systematic errors can be remedied by structure-averaged mutation group comparisons. We show that computational estimates have low precision, due to method and structure heterogeneity making results for single mutations uninformative. However, structure-averaged differences in mean effects for groups of substitutions can yield significant results. Illustrating this protocol, functionally important natural mutations, despite individual variations, average to a smaller stability impact compared to other possible mutations, independent of conformational state (open, closed). In summary, we document substantial issues with precision in structure-based protein modeling and recommend sensitivity tests to quantify these effects, but also suggest partial solutions to the problem in the form of structure-averaged “ensemble” estimates for groups of residues when multiple structures are available.

A computational chemistry-driven hypothesis on the mode of action of Hipposudoric Acid and related analogs

Aim: To elucidate the mode of action of the hipposudoric acid derivatives and identify hit compounds for synthesis. Materials & methods: Structural fragments of known bioactive fluorenes were introduced onto the hipposudoric acid scaffold to yield novel derivatives. The binding motifs of the novel compounds were compared to the pharmacophore of DHFR co-crystallized with Methotrexate (MTX). Results: Several of the novel compounds showed binding affinities that exceeded the affinity of the docked endogenous ligand (dihydrofolic acid). Conclusion: This study indicates that compounds 3r₁₂, 3r₉, 1s₉ and 3r₁₀ are promising candidates for synthesis and pharmacological evaluation.

SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural sources

Proteins isolated from natural sources can be composed of a mixture of isoforms with similar physicochemical properties that coexist in the final steps of purification. Yet, even where unverified, the assumed sequence is enforced throughout the structural studies. Herein, we propose a novel perspective to address the usually neglected sequence heterogeneity of natural products by integrating biophysical, genetic and structural data in our program SEQUENCE SLIDER. The aim is to assess the evidence supporting chemical composition in structure determination. Locally, we interrogate the experimental map to establish which side chains are supported by the structural data, and the genetic information relating sequence conservation is integrated into this statistic. Hence, we build a constrained peptide database, containing most probable sequences to interpret mass spectrometry data (MS). In parallel, we perform MS de novo sequencing with genomic-based algorithms to detect point mutations. We calibrated SLIDER with Gallus gallus lysozyme, whose sequence is unequivocally established and numerous natural isoforms are reported. We used SLIDER to characterize a metalloproteinase and a phospholipase A2-like protein from the venom of Bothrops moojeni and a crotoxin from Crotalus durissus collilineatus. This integrated approach offers a more realistic structural descriptor to characterize macromolecules isolated from natural sources.

Structure and Mutations of SARS-CoV-2 Spike Protein: A Focused Overview

The spike protein (S-protein) of SARS-CoV-2, the protein that enables the virus to infect human cells, is the basis for many vaccines and a hotspot of concerning virus evolution. Here, we discuss the outstanding progress in structural characterization of the S-protein and how these structures facilitate analysis of virus function and evolution. We emphasize the differences in reported structures and that analysis of structure-function relationships is sensitive to the structure used. We show that the average residue solvent exposure in nearly complete structures is a good descriptor of open vs closed conformation states. Because of structural heterogeneity of functionally important surface-exposed residues, we recommend using averages of a group of high-quality protein structures rather than a single structure before reaching conclusions on specific structure-function relationships. To illustrate these points, we analyze some significant chemical tendencies of prominent S-protein mutations in the context of the available structures. In the discussion of new variants, we emphasize the selectivity of binding to ACE2 vs prominent antibodies rather than simply the antibody escape or ACE2 affinity separately. We note that larger chemical changes, in particular increased electrostatic charge or side-chain volume of exposed surface residues, are recurring in mutations of concern, plausibly related to adaptation to the negative surface potential of human ACE2. We also find indications that the fixated mutations of the S-protein in the main variants are less destabilizing than would be expected on average, possibly pointing toward a selection pressure on the S-protein. The richness of available structures for all of these situations provides an enormously valuable basis for future research into these structure-function relationships.

Effective prediction of short hydrogen bonds in proteins via machine learning method

Short hydrogen bonds (SHBs), whose donor and acceptor heteroatoms lie within 2.7 Å, exhibit prominent quantum mechanical characters and are connected to a wide range of essential biomolecular processes. However, exact determination of the geometry and functional roles of SHBs requires a protein to be at atomic resolution. In this work, we analyze 1260 high-resolution peptide and protein structures from the Protein Data Bank and develop a boosting based machine learning model to predict the formation of SHBs between amino acids. This model, which we name as machine learning assisted prediction of short hydrogen bonds (MAPSHB), takes into account 21 structural, chemical and sequence features and their interaction effects and effectively categorizes each hydrogen bond in a protein to a short or normal hydrogen bond. The MAPSHB model reveals that the type of the donor amino acid plays a major role in determining the class of a hydrogen bond and that the side chain Tyr-Asp pair demonstrates a significant probability of forming a SHB. Combining electronic structure calculations and energy decomposition analysis, we elucidate how the interplay of competing intermolecular interactions stabilizes the Tyr-Asp SHBs more than other commonly observed combinations of amino acid side chains. The MAPSHB model, which is freely available on our web server, allows one to accurately and efficiently predict the presence of SHBs given a protein structure with moderate or low resolution and will facilitate the experimental and computational refinement of protein structures.

The Non-continuum Nature of Eukaryotic Transcriptional Regulation

Eukaryotic transcription factors are versatile mediators of specificity in gene regulation. This versatility is achieved through mutual specification by context-specific DNA binding on the one hand, and identity-specific protein-protein partnerships on the other. This interactivity, known as combinatorial control, enables a repertoire of complex transcriptional outputs that are qualitatively disjoint, or non-continuum, with respect to binding affinity. This feature contrasts starkly with prokaryotic gene regulators, whose activities in general vary quantitatively in step with binding affinity. Biophysical studies on prokaryotic model systems and more recent investigations on transcription factors highlight an important role for folded state dynamics and molecular hydration in protein/DNA recognition. Analysis of molecular models of combinatorial control and recent literature in low-affinity gene regulation suggest that transcription factors harbor unique conformational dynamics that are inaccessible or unused by prokaryotic DNA-binding proteins. Thus, understanding the intrinsic dynamics involved in DNA binding and co-regulator recruitment appears to be a key to understanding how transcription factors mediate non-continuum outcomes in eukaryotic gene expression, and how such capability might have evolved from ancient, structurally conserved counterparts.

Caseinolytic Proteins (Clp) in the Genus Klebsiella: Special Focus on ClpK

Caseinolytic proteins (Clp), which are present in both prokaryotes and eukaryotes, play a major role in cell protein quality control and survival of bacteria in harsh environmental conditions. Recently, a member of this protein family, ClpK was identified in a pathogenic strain of Klebsiella pneumoniae which was responsible for nosocomial infections. ClpK is linked to the thermal stress survival of this pathogen. The genome wide analysis of Clp proteins in Klebsiella spp. indicates that ClpK is present in only 34% of the investigated strains. This suggests that the uptake of the clpk gene is selective and may only be taken up by a pathogen that needs to survive harsh environmental conditions. In silico analyses and molecular dynamic simulations show that ClpK is mainly α-helical and is highly dynamic. ClpK was successfully expressed and purified to homogeneity using affinity and anion exchange chromatography. Biophysical characterization of ClpK showed that it is predominantly alpha-helical, and this is in agreement with in silico analysis of the protein structure. Furthermore, the purified protein is biologically active and hydrolyses ATP in a concentration- dependent manner.

Purification, Crystallization, and Preliminary Crystallographic Studies of Human As(III) S-Adenosylmethionine Methyltransferase (hAS3MT)

Exposure to environmental arsenic is associated with serious of health issues such as cancer, diabetes and developmental delays in infants and children. In human liver, As(III) S-adenosylmethionine methyl transferase (hAS3MT) (EC 2.1.1.137) was proposed to be an detoxification process by methylation of inorganic arsenite into pentavalent methyl MAs(V) and dimethyl arsenite DMAs(V). More recently the first product was shown to be highly toxic and potentially carcinogenic trivalent methylarsenite (MAs(III)). Our studies are designed to elucidate the mechanism of AS3MT and its contribution to arsenic-related diseases. Here, we report the first crystallization and preliminary X-ray diffraction analysis of the human AS3MT enzyme. The crystals belong to the monoclinic P1211 space group with unit cell parameters of a = 135.03 Å, b = 260.44 Å, c = 279.03 Å, α = 90.00°, β = 93.36°, γ = 90.00°.

Polymorphism in early development: The account of MBQ-167

With McCrone's famous statement in mind, we set out to investigate the polymorphic behavior of a small-molecule dual inhibitor of Rac and Cdc42, currently undergoing preclinical trials. Herein, we report the existence of two polymorphs for 9-ethyl-3-(5-phenyl-1H-1,2,3-triazol-3-yl)-9H-carbazole (MBQ-167). These were characterized by differential scanning calorimetry, thermogravimetric analysis, Raman and Infrared spectroscopy, as well as powder and single crystal X-ray diffraction. The results obtained from the thermal analysis revealed that MBQ-167 form II undergoes an exothermic phase transition to form I, making this the thermodynamically stable form. An examination of the Burger-Ramberger rules for assigning thermodynamic relationships in polymorphic pairs indicate that this system is monotropic. The structure elucidation reveals that these forms crystallize in the orthorhombic (Pbca) and monoclinic (P2₁/n) space groups. A conformational analysis shows that the metastable form (form II) presents the most planar conformation along the significant torsion angles identified. Hirshfeld surface analysis confirms that van der Waals contacts are the primary interactions and only subtle differences in short contacts help differentiate each form. These findings support the notion that polymorphism is prevalent in organic molecules and that one should invest time and money probing possible polymorphs, particularly in early development as in the case of MBQ-167.

Molecular coevolution of nuclear and nucleolar localization signals inside basic domain of HIV-1 Tat

During evolution, viruses had to adapt to an increasingly complex environment of eukaryotic cells. Viral proteins that need to enter the cell nucleus or associate with nucleoli possess nuclear localization signals (NLSs) and nucleolar localization signals (NoLSs) for nuclear and nucleolar accumulation, respectively. As viral proteins are relatively small, acquisition of novel sequences seems to be a more complicated task for viruses than for eukaryotes. Here, we carried out a comprehensive analysis of the basic domain (BD) of HIV-1 Tat to show how viral proteins might evolve with NLSs and NoLSs without an increase in protein size. The HIV-1 Tat BD is involved in several functions, the most important being the transactivation of viral transcription. The BD also functions as an NLS, although it is substantially longer than a typical NLS. It seems that different regions in the BD could function as NLSs due to its enrichment with positively charged amino acids. Additionally, the high positive net charge inevitably causes the BD to function as an NoLS through a charge-specific mechanism. The integration of NLSs and NoLSs into functional domains enriched with positively charged amino acids might be a mechanism that allows the condensation of different functional sequences in small protein regions and, as a result, to reduce protein size, influencing the origin and evolution of NLSs and NoLSs in viruses. IMPORTANCE Here, we investigated the molecular mechanism of NLS and NoLS integration into the basic domain of HIV-1 Tat (⁴⁹RKKRRQRRR⁵⁷), and found that these two supplementary functions (i.e., function of NLS and NoLS) are embedded in the basic domain amino acid sequence. The integration of NLSs and NoLSs into functional domains of viral proteins enriched with positively charged amino acids is a mechanism that allows the concentration of different functions within small protein regions. Integration of NLS and NoLS into functional protein domains might have influenced the viral evolution, as this could prevent an increase in the protein size.

High-resolution structure of the amino acid transporter AdiC reveals insights into the role of water molecules and networks in oligomerization and substrate binding

Background

The L-arginine/agmatine transporter AdiC is part of the arginine-dependent extreme acid resistance system of the bacterium Escherichia coli and its pathogenic varieties such as strain E. coli O157:H7. At the present time, there is a lack of knowledge concerning the role of water molecules and networks for the structure and function of AdiC, and solute transporters in general.

Results

The structure of the L-arginine/agmatine transporter AdiC was determined at 1.7 Å resolution by X-ray crystallography. This high resolution allowed for the identification of numerous water molecules buried in the structure. In combination with molecular dynamics (MD) simulations, we demonstrate that water molecules play an important role for stabilizing the protein and key residues, and act as placeholders for atoms of the AdiC substrates L-arginine and agmatine. MD simulations unveiled flexibility and restrained mobility of gating residues W202 and W293, respectively. Furthermore, a water-filled cavity was identified at the dimer interface of AdiC. The two monomers formed bridging interactions through water-mediated hydrogen bonds. The accessibility and presence of water molecules in this cavity was confirmed with MD simulations. Point mutations disrupting the interfacial water network validated the importance of water molecules for dimer stabilization.

Conclusions

This work gives new insights into the role and importance of water molecules in the L-arginine/agmatine transporter AdiC for protein stabilization and substrate-binding site shaping and as placeholders of substrate atoms. Furthermore, and based on the observed flexibility and restrained mobility of gating residues, a mechanistic role of the gate flexibility in the transport cycle was proposed. Finally, we identified a water-filled cavity at the dimeric interface that contributes to the stability of the amino acid transporter oligomer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01102-4.

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.

Structural Analysis of Strigolactone-Related Gene Products

Structural knowledge of biological macromolecules is essential for understanding their function and for modifying that function by engineering. Protein crystallography is a powerful method for elucidating molecular structures of proteins, but it is essential that the investigator has a basic knowledge of good practices and of the major pitfalls in the technique. Here we describe issues specific for the case of structural studies of strigolactone (SL) receptor structure and function, and in particular the difficulties associated with capturing complexes of SL receptors with the SL hormone ligand in the crystal.

Analysis methods and quality criteria for investigating muscle physiology using x-ray diffraction

X-ray diffraction studies of muscle have been tremendously powerful in providing fundamental insights into the structures of, for example, the myosin and actin filaments in a variety of muscles and the physiology of the cross-bridge mechanism during the contractile cycle. However, interpretation of x-ray diffraction patterns is far from trivial, and if modeling of the observed diffraction intensities is required it needs to be performed carefully with full knowledge of the possible pitfalls. Here, we discuss (1) how x-ray diffraction can be used as a tool to monitor various specific muscle properties and (2) how to get the most out of the rest of the observed muscle x-ray diffraction patterns by modeling where the reliability of the modeling conclusions can be objectively tested. In other x-ray diffraction methods, such as protein crystallography, the reliability of every step of the process is estimated and quoted in published papers. In this way, the quality of the structure determination can be properly assessed. To be honest with ourselves in the muscle field, we need to do as near to the same as we can, within the limitations of the techniques that we are using. We discuss how this can be done. We also use test cases to reveal the dos and don’ts of using x-ray diffraction to study muscle physiology.

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.

Detecting anomalies in X-ray diffraction images using convolutional neural networks

Our understanding of life is based upon the interpretation of macromolecular structures and their dynamics. Almost 90% of currently known macromolecular models originated from electron density maps constructed using X-ray diffraction images. Even though diffraction images are critical for structure determination, due to their vast amounts and noisy, non-intuitive nature, their quality is rarely inspected. In this paper, we use recent advances in machine learning to automatically detect seven types of anomalies in X-ray diffraction images. For this purpose, we utilize a novel X-ray beam center detection algorithm, propose three different image representations, and compare the predictive performance of general-purpose classifiers and deep convolutional neural networks (CNNs). In benchmark tests on a set of 6,311 X-ray diffraction images, the proposed CNN achieved between 87% and 99% accuracy depending on the type of anomaly. Experimental results show that the proposed anomaly detection system can be considered suitable for early detection of sub-optimal data collection conditions and malfunctions at X-ray experimental stations.

'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.

Use of molecular docking computational tools in drug discovery

Molecular docking has become an important component of the drug discovery process. Since first being developed in the 1980s, advancements in the power of computer hardware and the increasing number of and ease of access to small molecule and protein structures have contributed to the development of improved methods, making docking more popular in both industrial and academic settings. Over the years, the modalities by which docking is used to assist the different tasks of drug discovery have changed. Although initially developed and used as a standalone method, docking is now mostly employed in combination with other computational approaches within integrated workflows. Despite its invaluable contribution to the drug discovery process, molecular docking is still far from perfect. In this chapter we will provide an introduction to molecular docking and to the different docking procedures with a focus on several considerations and protocols, including protonation states, active site waters and consensus, that can greatly improve the docking results.

Structural basis of SARS-CoV-2 spike protein induced by ACE2

Motivation

The recent emergence of the novel SARS-coronavirus 2 (SARS-CoV-2) and its international spread pose a global health emergency. The spike (S) glycoprotein binds ACE2 and promotes SARS-CoV-2 entry into host cells. The trimeric S protein binds the receptor using the receptor-binding domain (RBD) causing conformational changes in S protein that allow priming by host cell proteases. Unraveling the dynamic structural features used by SARS-CoV-2 for entry might provide insights into viral transmission and reveal novel therapeutic targets. Using structures determined by X-ray crystallography and cryo-EM, we performed structural analysis and atomic comparisons of the different conformational states adopted by the SARS-CoV-2-RBD.

Results

Here, we determined the key structural components induced by the receptor and characterized their intramolecular interactions. We show that κ-helix (polyproline-II) is a predominant structure in the binding interface and in facilitating the conversion to the active form of the S protein. We demonstrate a series of conversions between switch-like κ-helix and β-strand, and conformational variations in a set of short α-helices which affect the hinge region. These conformational changes lead to an alternating pattern in conserved disulfide bond configurations positioned at the hinge, indicating a possible disulfide exchange, an important allosteric switch implicated in viral entry of various viruses, including HIV and murine coronavirus. The structural information presented herein enables to inspect and understand the important dynamic features of SARS-CoV-2-RBD and propose a novel potential therapeutic strategy to block viral entry. Overall, this study provides guidance for the design and optimization of structure-based intervention strategies that target SARS-CoV-2.

Availability

We have implemented the proposed methods in an R package freely available at https://github.com/Grantlab/bio3d

Supplementary information

Supplementary data are available at Bioinformatics online.

MD simulations reveal the basis for dynamic assembly of Hfq-RNA complexes

The conserved protein Hfq is a key factor in the RNA-mediated control of gene expression in most known bacteria. The transient intermediates Hfq forms with RNA support intricate and robust regulatory networks. In Pseudomonas, Hfq recognizes repeats of adenine–purine–any nucleotide (ARN) in target mRNAs via its distal binding side, and together with the catabolite repression control (Crc) protein, assembles into a translation–repression complex. Earlier experiments yielded static, ensemble-averaged structures of the complex, but details of its interface dynamics and assembly pathway remained elusive. Using explicit solvent atomistic molecular dynamics simulations, we modeled the extensive dynamics of the Hfq–RNA interface and found implications for the assembly of the complex. We predict that syn/anti flips of the adenine nucleotides in each ARN repeat contribute to a dynamic recognition mechanism between the Hfq distal side and mRNA targets. We identify a previously unknown binding pocket that can accept any nucleotide and propose that it may serve as a ‘status quo’ staging point, providing nonspecific binding affinity, until Crc engages the Hfq–RNA binary complex. The dynamical components of the Hfq–RNA recognition can speed up screening of the pool of the surrounding RNAs, participate in rapid accommodation of the RNA on the protein surface, and facilitate competition among different RNAs. The register of Crc in the ternary assembly could be defined by the recognition of a guanine-specific base–phosphate interaction between the first and last ARN repeats of the bound RNA. This dynamic substrate recognition provides structural rationale for the stepwise assembly of multicomponent ribonucleoprotein complexes nucleated by Hfq–RNA binding.

Hierarchical Self-Assembly of Nanowires on the Surface by Metallo-Supramolecular Truncated Cuboctahedra

Parastichy, the spiral arrangement of plant organs, is an example of the long-range apparent order seen in biological systems. These ordered arrangements provide scientists with both an aesthetic challenge and a mathematical inspiration. Synthetic efforts to replicate the regularity of parastichy may allow for molecular-scale control over particle arrangement processes. Here we report the packing of a supramolecular truncated cuboctahedron (TCO) into double-helical (DH) nanowires on a graphite surface with a non-natural parastichy pattern ascribed to the symmetry of the TCOs and interactions between TCOs. Such a study is expected to advance our understanding of the design inputs needed to create complex, but precisely controlled, hierarchical materials. It is also one of the few reported helical packing structures based on Platonic or Archimedean solids since the discovery of the Boerdijk-Coxeter helix. As such, it may provide experimental support for studies of packing theory at the molecular level.

Comparison of cellooligosaccharide conformations in complexes with proteins with energy maps for cellobiose

Shapes (conformations) of cellulose molecules are described by their glycosidic linkage torsion angles ϕ and ψ. Although the torsions are known for cellulose in crystals, amorphous shapes are also interesting for understanding reactivity and physical properties. ϕ and ψ determination for unorganized matter is difficult; one approach is to study their range in many related molecules. For example, linkage torsions of cellulose should be similar to those in cellobiose. Herein, torsions were measured for cellooligosaccharides and lactose moieties complexed with proteins in the Protein Data Bank (PDB). These torsions were compared with ϕ/ψ maps based on quantum mechanics energies for solvated cellobiose and analogs lacking hydroxyl groups. Most PDB conformations corresponded to low map energies. Amorphous cellulose should be generally extended with individual linkages that would give 2- to 3-fold helices. The map for an analog lacking hydrogen bonding ability was more predictive for PDB linkages than the cellobiose map.

NMR Structure Determinations of Small Proteins Using only One Fractionally 20% 13C- and Uniformly 100% 15N-Labeled Sample

Uniformly ¹³C- and ¹⁵N-labeled samples ensure fast and reliable nuclear magnetic resonance (NMR) assignments of proteins and are commonly used for structure elucidation by NMR. However, the preparation of uniformly labeled samples is a labor-intensive and expensive step. Reducing the portion of ¹³C-labeled glucose by a factor of five using a fractional 20% ¹³C- and 100% ¹⁵N-labeling scheme could lower the total chemical costs, yet retaining sufficient structural information of uniformly [¹³C, ¹⁵N]-labeled sample as a result of the improved sensitivity of NMR instruments. Moreover, fractional ¹³C-labeling can facilitate reliable resonance assignments of sidechains because of the biosynthetic pathways of each amino-acid. Preparation of only one [20% ¹³C, 100% ¹⁵N]-labeled sample for small proteins (<15 kDa) could also eliminate redundant sample preparations of 100% ¹⁵N-labeled and uniformly 100% [¹³C, ¹⁵N]-labeled samples of proteins. We determined the NMR structures of a small alpha-helical protein, the C domain of IgG-binding protein A from Staphylococcus aureus (SpaC), and a small beta-sheet protein, CBM64 module using [20% ¹³C, 100% ¹⁵N]-labeled sample and compared with the crystal structures and the NMR structures derived from the 100% [¹³C, ¹⁵N]-labeled sample. Our results suggest that one [20% ¹³C, 100% ¹⁵N]-labeled sample of small proteins could be routinely used as an alternative to conventional 100% [¹³C, ¹⁵N]-labeling for backbone resonance assignments, NMR structure determination, ¹⁵N-relaxation analysis, and ligand–protein interaction.

Macromolecular room temperature crystallography

X-ray crystallography enables detailed structural studies of proteins to understand and modulate their function. Conducting crystallographic experiments at cryogenic temperatures has practical benefits but potentially limits the identification of functionally important alternative protein conformations that can be revealed only at room temperature (RT). This review discusses practical aspects of preparing, acquiring, and analyzing X-ray crystallography data at RT to demystify preconceived impracticalities that freeze progress of routine RT data collection at synchrotron sources. Examples are presented as conceptual and experimental templates to enable the design of RT-inspired studies; they illustrate the diversity and utility of gaining novel insights into protein conformational landscapes. An integrative view of protein conformational dynamics enables opportunities to advance basic and biomedical research.

When are two hydrogen bonds better than one? Accurate first-principles models explain the balance of hydrogen bond donors and acceptors found in proteins

Hydrogen bonds (HBs) play an essential role in the structure and catalytic action of enzymes, but a complete understanding of HBs in proteins challenges the resolution of modern structural (i.e., X-ray diffraction) techniques and mandates computationally demanding electronic structure methods from correlated wavefunction theory for predictive accuracy. Numerous amino acid sidechains contain functional groups (e.g., hydroxyls in Ser/Thr or Tyr and amides in Asn/Gln) that can act as either HB acceptors or donors (HBA/HBD) and even form simultaneous, ambifunctional HB interactions. To understand the relative energetic benefit of each interaction, we characterize the potential energy surfaces of representative model systems with accurate coupled cluster theory calculations. To reveal the relationship of these energetics to the balance of these interactions in proteins, we curate a set of 4000 HBs, of which >500 are ambifunctional HBs, in high-resolution protein structures. We show that our model systems accurately predict the favored HB structural properties. Differences are apparent in HBA/HBD preference for aromatic Tyr versus aliphatic Ser/Thr hydroxyls because Tyr forms significantly stronger O–H⋯O HBs than N–H⋯O HBs in contrast to comparable strengths of the two for Ser/Thr. Despite this residue-specific distinction, all models of residue pairs indicate an energetic benefit for simultaneous HBA and HBD interactions in an ambifunctional HB. Although the stabilization is less than the additive maximum due both to geometric constraints and many-body electronic effects, a wide range of ambifunctional HB geometries are more favorable than any single HB interaction.

Correlated wavefunction theory predicts and high-resolution crystal structure analysis confirms the important, stabilizing effect of simultaneous hydrogen bond donor and acceptor interactions in proteins.