Orbitrap-Based Mass and Charge Analysis of Single Molecules.

Native mass spectrometry is nowadays widely used for determining the mass of intact proteins and their noncovalent biomolecular assemblies. While this technology performs well in the mass determination of monodisperse protein assemblies, more real-life heterogeneous protein complexes can pose a significant challenge. Factors such as co-occurring stoichiometries, subcomplexes, and/or post-translational modifications, may especially hamper mass analysis by obfuscating the charge state inferencing that is fundamental to the technique. Moreover, these mass analyses typically require measurement of several million molecules to generate an analyzable mass spectrum, limiting its sensitivity. In 2012, we introduced an Orbitrap-based mass analyzer with extended mass range (EMR) and demonstrated that it could be used to obtain not only high-resolution mass spectra of large protein macromolecular assemblies, but we also showed that single ions generated from these assemblies provided sufficient image current to induce a measurable charge-related signal. Based on these observations, we and others further optimized the experimental conditions necessary for single ion measurements, which led in 2020 to the introduction of single-molecule Orbitrap-based charge detection mass spectrometry (Orbitrap-based CDMS). The introduction of these single molecule approaches has led to the fruition of various innovative lines of research. For example, tracking the behavior of individual macromolecular ions inside the Orbitrap mass analyzer provides unique, fundamental insights into mechanisms of ion dephasing and demonstrated the (astonishingly high) stability of high mass ions. Such fundamental information will help to further optimize the Orbitrap mass analyzer. As another example, the circumvention of traditional charge state inferencing enables Orbitrap-based CDMS to extract mass information from even extremely heterogeneous proteins and protein assemblies (e.g., glycoprotein assemblies, cargo-containing nanoparticles) via single molecule detection, reaching beyond the capabilities of earlier approaches. We so far demonstrated the power of Orbitrap-based CDMS applied to a variety of fascinating systems, assessing for instance the cargo load of recombinant AAV-based gene delivery vectors, the buildup of immune-complexes involved in complement activation, and quite accurate masses of highly glycosylated proteins, such as the SARS-CoV-2 spike trimer proteins. With such widespread applications, the next objective is to make Orbitrap-based CDMS more mainstream, whereby we still will seek to further advance the boundaries in sensitivity and mass resolving power.

xia2.multiplex: a multi-crystal data-analysis pipeline.

In macromolecular crystallography, radiation damage limits the amount of data that can be collected from a single crystal. It is often necessary to merge data sets from multiple crystals; for example, small-wedge data collections from micro-crystals, in situ room-temperature data collections and data collection from membrane proteins in lipidic mesophases. Whilst the indexing and integration of individual data sets may be relatively straightforward with existing software, merging multiple data sets from small wedges presents new challenges. The identification of a consensus symmetry can be problematic, particularly in the presence of a potential indexing ambiguity. Furthermore, the presence of non-isomorphous or poor-quality data sets may reduce the overall quality of the final merged data set. To facilitate and help to optimize the scaling and merging of multiple data sets, a new program, xia2.multiplex, has been developed which takes data sets individually integrated with DIALS and performs symmetry analysis, scaling and merging of multi-crystal data sets. xia2.multiplex also performs analysis of various pathologies that typically affect multi-crystal data sets, including non-isomorphism, radiation damage and preferential orientation. After the description of a number of use cases, the benefit of xia2.multiplex is demonstrated within a wider autoprocessing framework in facilitating a multi-crystal experiment collected as part of in situ room-temperature fragment-screening experiments on the SARS-CoV-2 main protease.

Pre- and Post-publication Verification for Reproducible Data Mining in Macromolecular Crystallography.

Like an article narrative is deemed by an editor and referees to be worthy of being a version of record on acceptance as a publication, so must the underpinning data also be scrutinized before passing it as a version of record. Indeed without the underpinning data, a study and its conclusions cannot be reproduced at any stage of evaluation, pre- or post-publication. Likewise, an independent study without its own underpinning data also cannot be reproduced let alone be considered a replicate of the first study. The PDB is a modern marvel of achievement providing an organized open access to depositor and user of the data held there opening numerous applications. Methods for modeling protein structures and for determination of structures are still improving their precision, and artifacts of the method exist. So their accuracy is realized if they are reproduced by other methods. It is on such foundations that reproducible data mining is based. Data rates are expanding considerably be they at synchrotrons, the X-ray free electron lasers (XFELs), electron cryomicroscopes (cryoEM), or at the neutron facilities. The work of a person as a referee or user with a narrative and its underpinning data may well be complemented in future by artificial intelligence with machine learning, the former for specific refereeing and the latter for the more general validation, both ideally before publication. Examples are described involving rhenium theranostics, the anti-cancer platins and the SARS-CoV-2 main protease.

A method for intuitively extracting macromolecular dynamics from structural disorder.

Macromolecular dynamics manifest as disorder in structure determination, which is subsequently accounted for by displacement parameters (also called temperature factors, or B-factors) or alternate conformations. Though B-factors contain detailed information about structural dynamics, they are the total of multiple sources of disorder, making them difficult to interpret and thus little-used in structural analysis. We report here an analytical approach for decomposing molecular disorder into a parsimonious hierarchical series of contributions, providing an intuitive basis for quantitative structural-dynamics analysis. We demonstrate the decomposition of disorder on example SARS-CoV-2 and STEAP4 structures, from both crystallographic and cryo-electron microscopy data, and reveal how understanding of the macromolecular disorder leads to deeper understanding of molecular motions and flexibility, and suggests hypotheses for molecular mechanisms.

'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.

Assessment of protein-protein interfaces in cryo-EM derived assemblies.

Structures of macromolecular assemblies derived from cryo-EM maps often contain errors that become more abundant with decreasing resolution. Despite efforts in the cryo-EM community to develop metrics for map and atomistic model validation, thus far, no specific scoring metrics have been applied systematically to assess the interface between the assembly subunits. Here, we comprehensively assessed protein-protein interfaces in macromolecular assemblies derived by cryo-EM. To this end, we developed Protein Interface-score (PI-score), a density-independent machine learning-based metric, trained using the features of protein-protein interfaces in crystal structures. We evaluated 5873 interfaces in 1053 PDB-deposited cryo-EM models (including SARS-CoV-2 complexes), as well as the models submitted to CASP13 cryo-EM targets and the EM model challenge. We further inspected the interfaces associated with low-scores and found that some of those, especially in intermediate-to-low resolution (worse than 4 Å) structures, were not captured by density-based assessment scores. A combined score incorporating PI-score and fit-to-density score showed discriminatory power, allowing our method to provide a powerful complementary assessment tool for the ever-increasing number of complexes solved by cryo-EM.

Supramolecular Cylinders Target Bulge Structures in the 5' UTR of the RNA Genome of SARS-CoV-2 and Inhibit Viral Replication*.

The untranslated regions (UTRs) of viral genomes contain a variety of conserved yet dynamic structures crucial for viral replication, providing drug targets for the development of broad spectrum anti-virals. We combine in vitro RNA analysis with molecular dynamics simulations to build the first 3D models of the structure and dynamics of key regions of the 5' UTR of the SARS-CoV-2 genome. Furthermore, we determine the binding of metallo-supramolecular helicates (cylinders) to this RNA structure. These nano-size agents are uniquely able to thread through RNA junctions and we identify their binding to a 3-base bulge and the central cross 4-way junction located in stem loop 5. Finally, we show these RNA-binding cylinders suppress SARS-CoV-2 replication, highlighting their potential as novel anti-viral agents.

Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition.

Cryogenic electron tomography (cryoET) is a powerful method to study the 3D structure of biological samples in a close-to-native state. Current state-of-the-art cryoET combined with subtomogram averaging analysis enables the high-resolution structural determination of macromolecular complexes that are present in multiple copies within tomographic reconstructions. Tomographic experiments usually require a vast amount of tilt series to be acquired by means of high-end transmission electron microscopes with important operational running-costs. Although the throughput and reliability of automated data acquisition routines have constantly improved over the recent years, the process of selecting regions of interest at which a tilt series will be acquired cannot be easily automated and it still relies on the user's manual input. Therefore, the set-up of a large-scale data collection session is a time-consuming procedure that can considerably reduce the remaining microscope time available for tilt series acquisition. Here, the protocol describes the recently developed implementations based on the SerialEM package and the PyEM software that significantly improve the time-efficiency of grid screening and large-scale tilt series data collection. The presented protocol illustrates how to use SerialEM scripting functionalities to fully automate grid mapping, grid square mapping, and tilt series acquisition. Furthermore, the protocol describes how to use PyEM to select additional acquisition targets in off-line mode after automated data collection is initiated. To illustrate this protocol, its application in the context of high-end data collection of Sars-Cov-2 tilt series is described. The presented pipeline is particularly suited to maximizing the time-efficiency of tomography experiments that require a careful selection of acquisition targets and at the same time a large amount of tilt series to be collected.

RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), the US data center for the global PDB archive and a founding member of the Worldwide Protein Data Bank partnership, serves tens of thousands of data depositors in the Americas and Oceania and makes 3D macromolecular structure data available at no charge and without restrictions to millions of RCSB.org users around the world, including >660 000 educators, students and members of the curious public using PDB101.RCSB.org. PDB data depositors include structural biologists using macromolecular crystallography, nuclear magnetic resonance spectroscopy, 3D electron microscopy and micro-electron diffraction. PDB data consumers accessing our web portals include researchers, educators and students studying fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences. During the past 2 years, the research-focused RCSB PDB web portal (RCSB.org) has undergone a complete redesign, enabling improved searching with full Boolean operator logic and more facile access to PDB data integrated with >40 external biodata resources. New features and resources are described in detail using examples that showcase recently released structures of SARS-CoV-2 proteins and host cell proteins relevant to understanding and addressing the COVID-19 global pandemic.

Cryo-EM as a powerful tool for drug discovery.

The recent revolution in cryo-EM has produced an explosion of structures at near-atomic or better resolution. This has allowed cryo-EM structures to provide visualization of bound small-molecule ligands in the macromolecules, and these new structures have provided unprecedented insights into the molecular mechanisms of complex biochemical processes. They have also had a profound impact on drug discovery, defining the binding modes and mechanisms of action of well-known drugs as well as driving the design and development of new compounds. This review will summarize and highlight some of these structures. Most excitingly, the latest cryo-EM technology has produced structures at 1.2 Å resolution, further solidifying cryo-EM as a powerful tool for drug discovery. Therefore, cryo-EM will play an ever-increasing role in drug discovery in the coming years.