Enhanced validation of small-molecule ligands and carbohydrates in the Protein Data Bank

Binding Differences of the Peptide-Substrate-Binding Domain of Collagen Prolyl 4-Hydroxylases I and II for Proline- and Hydroxyproline-Rich Peptides

Collagen prolyl 4-hydroxylase (C-P4H) catalyzes the 4-hydroxylation of Y-prolines of the XYG-repeat of procollagen. C-P4Hs are tetrameric α2β2 enzymes. The α-subunit provides the N-terminal dimerization domain, the middle peptide-substrate-binding (PSB) domain, and the C-terminal catalytic (CAT) domain. There are three isoforms of the α-subunit, complexed with a β-subunit that is protein disulfide isomerase, forming C-P4H I-III. The PSB domain of the α-subunit binds proline-rich peptides, but its function with respect to the prolyl hydroxylation mechanism is unknown. An extended mode of binding of proline-rich peptides (PPII, polyproline type-II, conformation) to the PSB-I domain has previously been reported for the PPG-PPG-PPG and P9 peptides. Crystal structures now show that peptides with the motif PxGP (PPG-PRG-PPG, PPG-PAG-PPG) (where x, at Y-position 5, is not a proline) bind to the PSB-I domain differently, more deeply, in the peptide-binding groove. The latter mode of binding has previously been reported for structures of the PSB-II domain complexed with these PxGP-peptides. In addition, it is shown here by crystallographic binding studies that the POG-PAG-POG peptide (with 4-hydroxyprolines at Y-positions 2 and 8) also adopts the PxGP mode of binding to PSB-I as well as to PSB-II. Calorimetric binding studies show that the affinities of these peptides are lower for PSB-I than for PSB-II, with, respectively, KD values of about 70 μM for PSB-I and 20 μM for PSB-II. The importance of these results for understanding the reaction mechanism of C-P4H, in particular concerning the function of the PSB domain, is discussed.

PDBe tools for an in-depth analysis of small molecules in the Protein Data Bank

The Protein Data Bank (PDB) is the primary global repository for experimentally determined 3D structures of biological macromolecules and their complexes with ligands, proteins, and nucleic acids. PDB contains over 47,000 unique small molecules bound to the macromolecules. Despite the extensive data available, the complexity of small-molecule data in the PDB necessitates specialized tools for effective analysis and visualization. PDBe has developed a number of tools, including PDBe CCDUtils (https://github.com/PDBeurope/ccdutils) for accessing and enriching ligand data, PDBe Arpeggio (https://github.com/PDBeurope/arpeggio) for analyzing interactions between ligands and macromolecules, and PDBe RelLig (https://github.com/PDBeurope/rellig) for identifying the functional roles of ligands (such as reactants, cofactors, or drug-like molecules) within protein-ligand complexes. The enhanced ligand annotations and data generated by these tools are presented on the novel PDBe-KB ligand pages, offering a comprehensive overview of small molecules and providing valuable insights into their biological contexts (example page for Imatinib: https://pdbe.org/chem/sti). By improving the standardization of ligand identification, adding various annotations, and offering advanced visualization capabilities, these tools help researchers navigate the complexities of small molecules and their roles in biological systems, facilitating mechanistic understanding of biological functions. The ongoing enhancements to these resources are designed to support the scientific community in gaining valuable insights into ligands and their applications across various fields, including drug discovery, molecular biology, systems biology, structural biology, and pharmacology.

Visualizing and analyzing 3D biomolecular structures using Mol* at RCSB.org: Influenza A H5N1 virus proteome case study

The easiest and often most useful way to work with experimentally determined or computationally predicted structures of biomolecules is by viewing their three-dimensional (3D) shapes using a molecular visualization tool. Mol* was collaboratively developed by RCSB Protein Data Bank (RCSB PDB, RCSB.org) and Protein Data Bank in Europe (PDBe, PDBe.org) as an open-source, web-based, 3D visualization software suite for examination and analyses of biostructures. It is capable of displaying atomic coordinates and related experimental data of biomolecular structures together with a variety of annotations, facilitating basic and applied research, training, education, and information dissemination. Across RCSB.org, the RCSB PDB research-focused web portal, Mol* has been implemented to support single-mouse-click atomic-level visualization of biomolecules (e.g., proteins, nucleic acids, carbohydrates) with bound cofactors, small-molecule ligands, ions, water molecules, or other macromolecules. RCSB.org Mol* can seamlessly display 3D structures from various sources, allowing structure interrogation, superimposition, and comparison. Using influenza A H5N1 virus as a topical case study of an important pathogen, we exemplify how Mol* has been embedded within various RCSB.org tools-allowing users to view polymer sequence and structure-based annotations integrated from trusted bioinformatics data resources, assess patterns and trends in groups of structures, and view structures of any size and compositional complexity. In addition to being linked to every experimentally determined biostructure and Computed Structure Model made available at RCSB.org, Standalone Mol* is freely available for visualizing any atomic-level or multi-scale biostructure at rcsb.org/3d-view.

Anxiogenic-like effects of coumarin, possibly through the GABAkine interaction pathway: Animal studies with in silico approaches

BACKGROUND

Anxiety disorder is the most common mental illness and a major contributor to impairment. Thus, there is an urgent need to find novel lead compounds to mitigate anxiety. It is widely recognized that the neurobiology of anxiety-related behavior involves GABAergic systems.

OBJECTIVES

This research aimed to examine the anxiogenic action of coumarin (CMN), a natural benzopyrone derived from plants, and determine its underlying mechanism through in vivo and in silico investigations.

METHODS

This was accomplished by using a variety of behavioral procedures, including open field, swing, hole cross, and light-dark tests, on male and female Swiss albino mice that had been orally administered three experimental doses of CMN (1, 2, and 4 mg/kg). The CMN group was also examined with the GABAA receptor agonist diazepam (DZP, 2 mg/kg) and flumazenil antagonist (FLU, 0.1 mg/kg). Furthermore, CMN and standards were subjected to a molecular docking analysis to determine their binding affinities for the GABAA receptor subunits (α1, α4, β2, γ2, and δ). Several software programs were used to visualize the ligand-receptor interaction and analyze the pharmacokinetic profile.

RESULTS

Compared to typical treatments, our results show that CMN (1 mg/kg) significantly (p < 0.05) increases the locomotor activity of animals. Furthermore, CMN exerted the highest binding affinity (-6.5 kcal/mol) with the GABA-α1 receptor compared to conventional DZP. Along with FLU, CMN displayed several hydrophobic and hydrogen bonds with GABAA receptor subunits. The pharmacokinetic and drug-like properties of CMN are also remarkable. In animal studies, CMN worked synergistically with FLU to provide anxiogenic-like effects.

CONCLUSION

We conclude that, based on in vivo and in silico data, CMN, alone or in combination with FLU, may be employed in future neurological clinical studies. However, further research is needed to confirm this behavioral activity and elucidate the possible mechanism of action.

Q - score as a reliability measure for protein, nucleic acid, and small molecule atomic coordinate models derived from 3DEM density maps

Atomic coordinate models are important in the interpretation of 3D maps produced with cryoEM and sub-tomogram averaging in cryoET, or more generically, 3D electron microscopy (3DEM). In addition to visual inspection of such maps and models, quantitative metrics convey the reliability of the atomic coordinates, in particular how well the model is supported by the experimentally determined 3DEM map. A recently introduced metric, Q - score , was shown to correlate well with the reported resolution of the map for well-fitted models. Here we present new statistical analyses of Q - scores based on its application to ∼ 10,000 maps and models archived in EMDB and PDB. Further we introduce two new metrics based on Q - score : Q - relative - all and Q - relative - resolution to compare a map and model to all entries in the EMDB and those with similar resolution respectively. We also explore through illustrative examples of proteins, nucleic acids, and small molecules how Q - scores can indicate whether the atomic coordinates are well-fitted to 3DEM maps and whether some parts of a map may be poorly resolved due to factors such as molecular flexibility, radiation damage, and/or conformational heterogeneity. Lastly, we show examples of how Q - scores can effectively be converted to atomic B - factors . These analyses provide a basis for how Q - scores can be interpreted effectively to evaluate 3DEM maps and atomic coordinate models prior to publication and archiving.

Functional implications of glycans and their curation: insights from the workshop held at the 16th Annual International Biocuration Conference in Padua, Italy

Dynamic changes in protein glycosylation impact human health and disease progression. However, current resources that capture disease and phenotype information focus primarily on the macromolecules within the central dogma of molecular biology (DNA, RNA, proteins). To gain a better understanding of organisms, there is a need to capture the functional impact of glycans and glycosylation on biological processes. A workshop titled "Functional impact of glycans and their curation" was held in conjunction with the 16th Annual International Biocuration Conference to discuss ongoing worldwide activities related to glycan function curation. This workshop brought together subject matter experts, tool developers, and biocurators from over 20 projects and bioinformatics resources. Participants discussed four key topics for each of their resources: (i) how they curate glycan function-related data from publications and other sources, (ii) what type of data they would like to acquire, (iii) what data they currently have, and (iv) what standards they use. Their answers contributed input that provided a comprehensive overview of state-of-the-art glycan function curation and annotations. This report summarizes the outcome of discussions, including potential solutions and areas where curators, data wranglers, and text mining experts can collaborate to address current gaps in glycan and glycosylation annotations, leveraging each other's work to improve their respective resources and encourage impactful data sharing among resources. Database URL: https://wiki.glygen.org/Glycan_Function_Workshop_2023.

Crystallographic fragment-binding studies of the Mycobacterium tuberculosis trifunctional enzyme suggest binding pockets for the tails of the acyl-CoA substrates at its active sites and a potential substrate-channeling path between them

The Mycobacterium tuberculosis trifunctional enzyme (MtTFE) is an α2β2 tetrameric enzyme in which the α-chain harbors the 2E-enoyl-CoA hydratase (ECH) and 3S-hydroxyacyl-CoA dehydrogenase (HAD) active sites, and the β-chain provides the 3-ketoacyl-CoA thiolase (KAT) active site. Linear, medium-chain and long-chain 2E-enoyl-CoA molecules are the preferred substrates of MtTFE. Previous crystallographic binding and modeling studies identified binding sites for the acyl-CoA substrates at the three active sites, as well as the NAD binding pocket at the HAD active site. These studies also identified three additional CoA binding sites on the surface of MtTFE that are different from the active sites. It has been proposed that one of these additional sites could be of functional relevance for the substrate channeling (by surface crawling) of reaction intermediates between the three active sites. Here, 226 fragments were screened in a crystallographic fragment-binding study of MtTFE crystals, resulting in the structures of 16 MtTFE-fragment complexes. Analysis of the 121 fragment-binding events shows that the ECH active site is the `binding hotspot' for the tested fragments, with 41 binding events. The mode of binding of the fragments bound at the active sites provides additional insight into how the long-chain acyl moiety of the substrates can be accommodated at their proposed binding pockets. In addition, the 20 fragment-binding events between the active sites identify potential transient binding sites of reaction intermediates relevant to the possible channeling of substrates between these active sites. These results provide a basis for further studies to understand the functional relevance of the latter binding sites and to identify substrates for which channeling is crucial.

Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge

The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein-nucleic acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: Escherichia coli beta-galactosidase with inhibitor, SARS-CoV-2 virus RNA-dependent RNA polymerase with covalently bound nucleotide analog and SARS-CoV-2 virus ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. The quality of submitted ligand models and surrounding atoms were analyzed by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics and contact scores. A composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

Restraint validation of biomolecular structures determined by NMR in the Protein Data Bank

Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NEF and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints. Using these restraint formats, a standardized validation system for assessing structural models of biopolymers against restraints has been developed and implemented in the wwPDB OneDep data deposition-validation-biocuration system. The resulting wwPDB restraint violation report provides a model vs. data assessment of biomolecule structures determined using distance and dihedral restraints, with extensions to other restraint types currently being implemented. These tools are useful for assessing NMR models, as well as for assessing biomolecular structure predictions based on distance restraints.

Outcomes of the EMDataResource Cryo-EM Ligand Modeling Challenge

The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein/nucleic-acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: E. coli beta-galactosidase with inhibitor, SARS-CoV-2 RNA-dependent RNA polymerase with covalently bound nucleotide analog, and SARS-CoV-2 ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. We found that (1) the quality of submitted ligand models and surrounding atoms varied, as judged by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics, and contact scores, and (2) a composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

Restraint Validation of Biomolecular Structures Determined by NMR in the Protein Data Bank

Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NMR exchange (NEF) and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints. Using these restraint formats, a standardized validation system for assessing structural models of biopolymers against restraints has been developed and implemented in the wwPDB OneDep data deposition-validation-biocuration system. The resulting wwPDB Restraint Violation Report provides a model vs. data assessment of biomolecule structures determined using distance and dihedral restraints, with extensions to other restraint types currently being implemented. These tools are useful for assessing NMR models, as well as for assessing biomolecular structure predictions based on distance restraints.

EMDB-the Electron Microscopy Data Bank

The Electron Microscopy Data Bank (EMDB) is the global public archive of three-dimensional electron microscopy (3DEM) maps of biological specimens derived from transmission electron microscopy experiments. As of 2021, EMDB is managed by the Worldwide Protein Data Bank consortium (wwPDB; wwpdb.org) as a wwPDB Core Archive, and the EMDB team is a core member of the consortium. Today, EMDB houses over 30 000 entries with maps containing macromolecules, complexes, viruses, organelles and cells. Herein, we provide an overview of the rapidly growing EMDB archive, including its current holdings, recent updates, and future plans.

Announcing the launch of Protein Data Bank China as an Associate Member of the Worldwide Protein Data Bank Partnership

The Protein Data Bank (PDB) is the single global archive of atomic-level, three-dimensional structures of biological macromolecules experimentally determined by macromolecular crystallography, nuclear magnetic resonance spectroscopy or three-dimensional cryo-electron microscopy. The PDB is growing continuously, with a recent rapid increase in new structure depositions from Asia. In 2022, the Worldwide Protein Data Bank (wwPDB; https://www.wwpdb.org/) partners welcomed Protein Data Bank China (PDBc; https://www.pdbc.org.cn) to the organization as an Associate Member. PDBc is based in the National Facility for Protein Science in Shanghai which is associated with the Shanghai Advanced Research Institute of Chinese Academy of Sciences, the Shanghai Institute for Advanced Immunochemical Studies and the iHuman Institute of ShanghaiTech University. This letter describes the history of the wwPDB, recently established mechanisms for adding new wwPDB data centers and the processes developed to bring PDBc into the partnership.

Worldwide Glycoscience Informatics Infrastructure: The GlySpace Alliance

The GlySpace Alliance was formed in 2018 among the principal investigators of three major glycoscience portals: Glyco@Expasy, GlyCosmos, and GlyGen, representing Europe, Asia, and the United States, respectively. While each of these portals has its unique user interface, the aim is to provide the same basic data set of glycan-related omics data. These portals will be introduced with the aim to enable users to find their target information in the most efficient manner, in particular, in terms of the chemical structures of glycans and their functions.

RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), founding member of the Worldwide Protein Data Bank (wwPDB), is the US data center for the open-access PDB archive. As wwPDB-designated Archive Keeper, RCSB PDB is also responsible for PDB data security. Annually, RCSB PDB serves >10 000 depositors of three-dimensional (3D) biostructures working on all permanently inhabited continents. RCSB PDB delivers data from its research-focused RCSB.org web portal to many millions of PDB data consumers based in virtually every United Nations-recognized country, territory, etc. This Database Issue contribution describes upgrades to the research-focused RCSB.org web portal that created a one-stop-shop for open access to ∼200 000 experimentally-determined PDB structures of biological macromolecules alongside >1 000 000 incorporated Computed Structure Models (CSMs) predicted using artificial intelligence/machine learning methods. RCSB.org is a 'living data resource.' Every PDB structure and CSM is integrated weekly with related functional annotations from external biodata resources, providing up-to-date information for the entire corpus of 3D biostructure data freely available from RCSB.org with no usage limitations. Within RCSB.org, PDB structures and the CSMs are clearly identified as to their provenance and reliability. Both are fully searchable, and can be analyzed and visualized using the full complement of RCSB.org web portal capabilities.

RCSB Protein Data bank: Tools for visualizing and understanding biological macromolecules in 3D

Now in its 52nd year of continuous operations, the Protein Data Bank (PDB) is the premiere open-access global archive housing three-dimensional (3D) biomolecular structure data. It is jointly managed by the Worldwide Protein Data Bank (wwPDB) partnership. The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is funded by the National Science Foundation, National Institutes of Health, and US Department of Energy and serves as the US data center for the wwPDB. RCSB PDB is also responsible for the security of PDB data in its role as wwPDB-designated Archive Keeper. Every year, RCSB PDB serves tens of thousands of depositors of 3D macromolecular structure data (coming from macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction). The RCSB PDB research-focused web portal (RCSB.org) makes PDB data available at no charge and without usage restrictions to many millions of PDB data consumers around the world. The RCSB PDB training, outreach, and education web portal (PDB101.RCSB.org) serves nearly 700 K educators, students, and members of the public worldwide. This invited Tools Issue contribution describes how RCSB PDB (i) is organized; (ii) works with wwPDB partners to process new depositions; (iii) serves as the wwPDB-designated Archive Keeper; (iv) enables exploration and 3D visualization of PDB data via RCSB.org; and (v) supports training, outreach, and education via PDB101.RCSB.org. New tools and features at RCSB.org are presented using examples drawn from high-resolution structural studies of proteins relevant to treatment of human cancers by targeting immune checkpoints.

Assessing PDB macromolecular crystal structure confidence at the individual amino acid residue level

Approximately 87% of the more than 190,000 atomic-level three-dimensional (3D) biostructures in the PDB were determined using macromolecular crystallography (MX). Agreement between 3D atomic coordinates and experimental data for >100 million individual amino acid residues occurring within ∼150,000 PDB MX structures was analyzed in detail. The real-space correlation coefficient (RSCC) calculated using the 3D atomic coordinates for each residue and experimental-data-derived electron density enables outlier detection of unreliable atomic coordinates (particularly important for poorly resolved side-chain atoms) and ready evaluation of local structure quality by PDB users. For human protein MX structures in PDB, comparisons of the per-residue RSCC metric with AlphaFold2-computed structure model confidence (pLDDT-predicted local distance difference test) document (1) that RSCC values and pLDDT scores are correlated (median correlation coefficient ∼0.41), and (2) that experimentally determined MX structures (3.5 Å resolution or better) are more reliable than AlphaFold2-computed structure models and should be used preferentially whenever possible.

Protein Data Bank: A Comprehensive Review of 3D Structure Holdings and Worldwide Utilization by Researchers, Educators, and Students

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the United States National Science Foundation, National Institutes of Health, and Department of Energy, supports structural biologists and Protein Data Bank (PDB) data users around the world. The RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, serves as the US data center for the global PDB archive housing experimentally-determined three-dimensional (3D) structure data for biological macromolecules. As the wwPDB-designated Archive Keeper, RCSB PDB is also responsible for the security of PDB data and weekly update of the archive. RCSB PDB serves tens of thousands of data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) annually working on all permanently inhabited continents. RCSB PDB makes PDB data available from its research-focused web portal at no charge and without usage restrictions to many millions of PDB data consumers around the globe. It also provides educators, students, and the general public with an introduction to the PDB and related training materials through its outreach and education-focused web portal. This review article describes growth of the PDB, examines evolution of experimental methods for structure determination viewed through the lens of the PDB archive, and provides a detailed accounting of PDB archival holdings and their utilization by researchers, educators, and students worldwide.

Analysis of protein structures containing HEPES and MES molecules

X‐ray crystallography is the main experimental method behind ligand–macromolecule complexes found in the Protein Data Bank (PDB). Applying bioinformatics methods to such structural data can fuel drug discovery, albeit under the condition that the information is correct. Regrettably, a small number of structures in the PDB are of suboptimal quality due to incorrectly identified and modeled ligands in protein–ligand complexes. In this paper, we combine a theoretical‐graph approach, nuclear density estimates, bioinformatics methods, and prior chemical knowledge to analyze two non‐physiological ligands, HEPES and MES, that are frequent components of crystallization and purifications buffers. Our analysis includes quantum mechanics calculations and Cambridge Structure Database (CSD) queries to define the ideal conformation of these ligands, geometry analysis of PDB deposits regarding several quality factors, and a search for homologous structures to identify other small molecules that could bind in place of the parasitic ligand. Our results highlight the need for careful refinement of macromolecule–ligand complexes and better validation tools that integrate results from all relevant resources.

PDB Code(s): 3K4L, 3PYI, 5T6L, 6BB0, 1PJX, 3O4P, 6WCF, 3DKE, 3E10, 6G38, 4E8R, 4Z91, 3E9F, 1MOS, 1MOQ, 2ESB, 1VHR, 4P66 and 6NNI;

Exploring protein symmetry at the RCSB Protein Data Bank

The symmetry of biological molecules has fascinated structural biologists ever since the structure of hemoglobin was determined. The Protein Data Bank (PDB) archive is the central global archive of three-dimensional (3D), atomic-level structures of biomolecules, providing open access to the results of structural biology research with no limitations on usage. Roughly 40% of the structures in the archive exhibit some type of symmetry, including formal global symmetry, local symmetry, or pseudosymmetry. The Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank (founding member of the Worldwide Protein Data Bank partnership that jointly manages, curates, and disseminates the archive) provides a variety of tools to assist users interested in exploring the symmetry of biological macromolecules. These tools include multiple modalities for searching and browsing the archive, turnkey methods for biomolecular visualization, documentation, and outreach materials for exploring functional biomolecular symmetry.

How molecular modelling can better broaden the understanding of glycosylations

Glycosylations are among the most ubiquitous post-translational modifications (PTMs) in proteins, and the effects of their perturbations are seen in various diseases such as cancers, diabetes and arthritis to name a few. Yet they remain one of the most enigmatic aspects of protein structure and function. On the other hand, molecular modelling techniques have been rapidly bridging this knowledge gap since the last decade. In this review, we discuss how these techniques have proven to be indispensable for a better understanding of the role of glycosylations in glycoprotein structure and function.

Carbohydrate structure database (CSDB) oligosaccharide conformation tool

Population analysis in terms of glycosidic torsion angles is frequently used to reveal preferred conformers of glycans. However, due to high structural diversity and flexibility of carbohydrates, conformational characterization of complex glycans can be a challenging task. Herein we present a conformation module of oligosaccharide fragments occurring in natural glycan structures developed on the platform of the Carbohydrate Structure Database (CSDB). Currently, this module deposits free energy surface and conformer abundance maps plotted as a function of glycosidic torsions for 194 inter-residue bonds. Data are automatically and continuously derived from explicit-solvent molecular dynamics (MD) simulations. The module was also supplemented with high-temperature MD data of saccharides (2403 maps) provided by GlycoMapsDB (hosted by GLYCOSCIENCES.de project). Conformational data defined by up to four torsional degrees of freedom can be freely explored using a web interface of the module available at http://csdb.glycoscience.ru/database/core/search_conf.html.

pyFoldX: enabling biomolecular analysis and engineering along structural ensembles

SUMMARY

Recent years have seen an increase in the number of structures available, not only for new proteins but also for the same protein crystallized with different molecules and proteins. While protein design software has proven to be successful in designing and modifying proteins, they can also be overly sensitive to small conformational differences between structures of the same protein. To cope with this, we introduce here pyFoldX, a python library that allows the integrative analysis of structures of the same protein using FoldX, an established forcefield and modelling software. The library offers new functionalities for handling different structures of the same protein, an improved molecular parametrization module and an easy integration with the data analysis ecosystem of the python programming language.

AVAILABILITY AND IMPLEMENTATION

pyFoldX rely on the FoldX software for energy calculations and modelling, which can be downloaded upon registration in http://foldxsuite.crg.eu/ and its licence is free of charge for academics. The pyFoldX library is open-source. Full details on installation, tutorials covering the library functionality and the scripts used to generate the data and figures presented in this paper are available at https://github.com/leandroradusky/pyFoldX.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Simplified quality assessment for small-molecule ligands in the Protein Data Bank

More than 70% of the experimentally determined macromolecular structures in the Protein Data Bank (PDB) contain small-molecule ligands. Quality indicators of ∼643,000 ligands present in ∼106,000 PDB X-ray crystal structures have been analyzed. Ligand quality varies greatly with regard to goodness of fit between ligand structure and experimental data, deviations in bond lengths and angles from known chemical structures, and inappropriate interatomic clashes between the ligand and its surroundings. Based on principal component analysis, correlated quality indicators of ligand structure have been aggregated into two largely orthogonal composite indicators measuring goodness of fit to experimental data and deviation from ideal chemical structure. Ranking of the composite quality indicators across the PDB archive enabled construction of uniformly distributed composite ranking score. This score is implemented at RCSB.org to compare chemically identical ligands in distinct PDB structures with easy-to-interpret two-dimensional ligand quality plots, allowing PDB users to quickly assess ligand structure quality and select the best exemplars.

Towards Consistency in Geometry Restraints for Carbohydrates in the Pyranose form: Modern Dictionary Generators Reviewed

Macromolecular restrained refinement is nowadays the most used method for improving the agreement between an atomic structural model and experimental data. Restraint dictionaries, a key tool behind the success of the method, allow fine-tuning geometric properties such as distances and angles between atoms beyond simplistic expectations. Dictionary generators can provide restraint target estimates derived from different sources, from fully theoretical to experimental and any combination in between. Carbohydrates are stereochemically complex biomolecules and, in their pyranose form, have clear conformational preferences. As such, they pose unique problems to dictionary generators and in the course of this study, require special attention from software developers. Functional differences between restraint generators will be discussed, as well as the process of achieving consistent results with different software designs. The study will conclude a set of practical considerations, as well as recommendations for the generation of new restraint dictionaries, using the improved software alternatives discussed.

RCSB Protein Data Bank: Celebrating 50 years of the PDB with new tools for understanding and visualizing biological macromolecules in 3D

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the US National Science Foundation, National Institutes of Health, and Department of Energy, has served structural biologists and Protein Data Bank (PDB) data consumers worldwide since 1999. RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, is the US data center for the global PDB archive housing biomolecular structure data. RCSB PDB is also responsible for the security of PDB data, as the wwPDB-designated Archive Keeper. Annually, RCSB PDB serves tens of thousands of three-dimensional (3D) macromolecular structure data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) from all inhabited continents. RCSB PDB makes PDB data available from its research-focused RCSB.org web portal at no charge and without usage restrictions to millions of PDB data consumers working in every nation and territory worldwide. In addition, RCSB PDB operates an outreach and education PDB101.RCSB.org web portal that was used by more than 800,000 educators, students, and members of the public during calendar year 2020. This invited Tools Issue contribution describes (i) how the archive is growing and evolving as new experimental methods generate ever larger and more complex biomolecular structures; (ii) the importance of data standards and data remediation in effective management of the archive and facile integration with more than 50 external data resources; and (iii) new tools and features for 3D structure analysis and visualization made available during the past year via the RCSB.org web portal.

Functions of Glycosylation and Related Web Resources for Its Prediction

Glycosylation involves the attachment of carbohydrate sugar chains, or glycans, onto an amino acid residue of a protein. These glycans are often branched structures and serve to modulate the function of proteins. Glycans are synthesized through a complex process of enzymatic reactions that occur in the Golgi apparatus in mammalian systems. Because there is currently no sequencer for glycans, technologies such as mass spectrometry is used to characterize glycans in a biological sample to ascertain its glycome. This is a tedious process that requires high levels of expertise and equipment. Thus, the enzymes that work on glycans, called glycogenes or glycoenzymes, have been studied to better understand glycan function. With the development of glycan-related databases and a glycan repository, bioinformatics approaches have attempted to predict the glycosylation pathway and the glycosylation sites on proteins. This chapter introduces these methods and related Web resources for understanding glycan function.

Modernized uniform representation of carbohydrate molecules in the Protein Data Bank

Since 1971, the Protein Data Bank (PDB) has served as the single global archive for experimentally determined 3D structures of biological macromolecules made freely available to the global community according to the FAIR principles of Findability-Accessibility-Interoperability-Reusability. During the first 50 years of continuous PDB operations, standards for data representation have evolved to better represent rich and complex biological phenomena. Carbohydrate molecules present in more than 14,000 PDB structures have recently been reviewed and remediated to conform to a new standardized format. This machine-readable data representation for carbohydrates occurring in the PDB structures and the corresponding reference data improves the findability, accessibility, interoperability and reusability of structural information pertaining to these molecules. The PDB Exchange MacroMolecular Crystallographic Information File data dictionary now supports (i) standardized atom nomenclature that conforms to International Union of Pure and Applied Chemistry-International Union of Biochemistry and Molecular Biology (IUPAC-IUBMB) recommendations for carbohydrates, (ii) uniform representation of branched entities for oligosaccharides, (iii) commonly used linear descriptors of carbohydrates developed by the glycoscience community and (iv) annotation of glycosylation sites in proteins. For the first time, carbohydrates in PDB structures are consistently represented as collections of standardized monosaccharides, which precisely describe oligosaccharide structures and enable improved carbohydrate visualization, structure validation, robust quantitative and qualitative analyses, search for dendritic structures and classification. The uniform representation of carbohydrate molecules in the PDB described herein will facilitate broader usage of the resource by the glycoscience community and researchers studying glycoproteins.

'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.

Open-access data: A cornerstone for artificial intelligence approaches to protein structure prediction

The Protein Data Bank (PDB) was established in 1971 to archive three-dimensional (3D) structures of biological macromolecules as a public good. Fifty years later, the PDB is providing millions of data consumers around the world with open access to more than 175,000 experimentally determined structures of proteins and nucleic acids (DNA, RNA) and their complexes with one another and small-molecule ligands. PDB data users are working, teaching, and learning in fundamental biology, biomedicine, bioengineering, biotechnology, and energy sciences. They also represent the fields of agriculture, chemistry, physics and materials science, mathematics, statistics, computer science, and zoology, and even the social sciences. The enormous wealth of 3D structure data stored in the PDB has underpinned significant advances in our understanding of protein architecture, culminating in recent breakthroughs in protein structure prediction accelerated by artificial intelligence approaches and deep or machine learning methods.

Impact of structural biologists and the Protein Data Bank on small-molecule drug discovery and development

The Protein Data Bank (PDB) is an international core data resource central to fundamental biology, biomedicine, bioenergy, and biotechnology/bioengineering. Now celebrating its 50th anniversary, the PDB houses >175,000 experimentally determined atomic structures of proteins, nucleic acids, and their complexes with one another and small molecules and drugs. The importance of three-dimensional (3D) biostructure information for research and education obtains from the intimate link between molecular form and function evident throughout biology. Among the most prolific consumers of PDB data are biomedical researchers, who rely on the open access resource as the authoritative source of well-validated, expertly curated biostructures. This review recounts how the PDB grew from just seven protein structures to contain more than 49,000 structures of human proteins that have proven critical for understanding their roles in human health and disease. It then describes how these structures are used in academe and industry to validate drug targets, assess target druggability, characterize how tool compounds and other small-molecules bind to drug targets, guide medicinal chemistry optimization of binding affinity and selectivity, and overcome challenges during preclinical drug development. Three case studies drawn from oncology exemplify how structural biologists and open access to PDB structures impacted recent regulatory approvals of antineoplastic drugs.