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1.
Acta Crystallogr D Struct Biol ; 78(Pt 6): 752-769, 2022 Jun 01.
Article in English | MEDLINE | ID: covidwho-1874079

ABSTRACT

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.


Subject(s)
COVID-19 , Crystallography, X-Ray , Data Analysis , Humans , Macromolecular Substances/chemistry , SARS-CoV-2
2.
Methods Mol Biol ; 2449: 235-261, 2022.
Article in English | MEDLINE | ID: covidwho-1826140

ABSTRACT

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.


Subject(s)
Artificial Intelligence , COVID-19 , Crystallography/methods , Crystallography, X-Ray , Data Mining , Humans , Macromolecular Substances/chemistry , SARS-CoV-2 , Synchrotrons
3.
Nat Commun ; 12(1): 5493, 2021 09 17.
Article in English | MEDLINE | ID: covidwho-1428816

ABSTRACT

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.


Subject(s)
Coronavirus 3C Proteases/chemistry , Macromolecular Substances/chemistry , Molecular Dynamics Simulation , SARS-CoV-2/enzymology , COVID-19 , Cryoelectron Microscopy , Humans , Membrane Proteins/chemistry , Oxidoreductases/chemistry , Protein Conformation
4.
Int J Mol Sci ; 22(13)2021 Jun 25.
Article in English | MEDLINE | ID: covidwho-1304663

ABSTRACT

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.


Subject(s)
Binding Sites , Ligands , Macromolecular Substances/chemistry , Models, Molecular , Proteins/chemistry , Crystallography, X-Ray , Macromolecular Substances/metabolism , Molecular Conformation , Protein Binding , Proteins/metabolism
5.
Nat Commun ; 12(1): 3399, 2021 06 07.
Article in English | MEDLINE | ID: covidwho-1260942

ABSTRACT

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.


Subject(s)
Cryoelectron Microscopy/methods , Macromolecular Substances/chemistry , Protein Interaction Domains and Motifs , Protein Interaction Mapping/methods , Protein Interaction Maps , Proteins/chemistry , Humans , Machine Learning , Macromolecular Substances/metabolism , Macromolecular Substances/ultrastructure , Models, Molecular , Neural Networks, Computer , Protein Conformation , Protein Multimerization , Proteins/metabolism , Proteins/ultrastructure , Support Vector Machine , Viral Nonstructural Proteins/chemistry , Viral Nonstructural Proteins/metabolism , Viral Nonstructural Proteins/ultrastructure
6.
Angew Chem Int Ed Engl ; 60(33): 18144-18151, 2021 08 09.
Article in English | MEDLINE | ID: covidwho-1206743

ABSTRACT

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.


Subject(s)
5' Untranslated Regions , Antiviral Agents/pharmacology , Macromolecular Substances/pharmacology , RNA/metabolism , SARS-CoV-2/drug effects , Virus Replication/drug effects , Animals , Antiviral Agents/chemistry , Antiviral Agents/metabolism , Chlorocebus aethiops , Coordination Complexes/chemistry , Coordination Complexes/metabolism , Coordination Complexes/pharmacology , Genome, Viral/drug effects , Macromolecular Substances/chemistry , Macromolecular Substances/metabolism , Metals, Heavy/chemistry , Molecular Dynamics Simulation , RNA/genetics , SARS-CoV-2/chemistry , Vero Cells
7.
Nucleic Acids Res ; 49(D1): D437-D451, 2021 01 08.
Article in English | MEDLINE | ID: covidwho-936421

ABSTRACT

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.


Subject(s)
Computational Biology/methods , Databases, Protein , Macromolecular Substances/chemistry , Protein Conformation , Proteins/chemistry , Bioengineering/methods , Biomedical Research/methods , Biotechnology/methods , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/virology , Humans , Macromolecular Substances/metabolism , Pandemics , Proteins/genetics , Proteins/metabolism , SARS-CoV-2/genetics , SARS-CoV-2/metabolism , SARS-CoV-2/physiology , Software , Viral Proteins/chemistry , Viral Proteins/genetics , Viral Proteins/metabolism
8.
Bioorg Med Chem Lett ; 30(22): 127524, 2020 11 15.
Article in English | MEDLINE | ID: covidwho-739782

ABSTRACT

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.


Subject(s)
Cryoelectron Microscopy , Drug Discovery , Pharmaceutical Preparations/chemistry , Small Molecule Libraries/chemistry , Humans , Ligands , Macromolecular Substances/chemistry , Models, Molecular , Molecular Structure
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