1
|
van Raaij MJ. Private glycan investigations and public video content. Acta Crystallogr F Struct Biol Commun 2024; 80:28-29. [PMID: 38305784 PMCID: PMC10836427 DOI: 10.1107/s2053230x2400102x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024] Open
Abstract
Acta Cryst. F - Structural Biology Communications plans to introduce more video content to articles and Dialpuri et al. [(2024). Acta Cryst. F80, 30-35] provide an early example.
Collapse
Affiliation(s)
- Mark J. van Raaij
- Dpto de Estructura de Macromoleculas, lab 20B, Centro Nacional de Biotecnologia - CSIC, calle Darwin 3, E-28049, Madrid, Spain
| |
Collapse
|
2
|
Niazi SK. A Critical Analysis of the FDA's Omics-Driven Pharmacodynamic Biomarkers to Establish Biosimilarity. Pharmaceuticals (Basel) 2023; 16:1556. [PMID: 38004421 PMCID: PMC10675618 DOI: 10.3390/ph16111556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 09/25/2023] [Accepted: 09/29/2023] [Indexed: 11/26/2023] Open
Abstract
Demonstrating biosimilarity entails comprehensive analytical assessment, clinical pharmacology profiling, and efficacy testing in patients for at least one medical indication, as required by the U.S. Biologics Price Competition and Innovation Act (BPCIA). The efficacy testing can be waived if the drug has known pharmacodynamic (PD) markers, leaving most therapeutic proteins out of this concession. To overcome this, the FDA suggests that biosimilar developers discover PD biomarkers using omics technologies such as proteomics, glycomics, transcriptomics, genomics, epigenomics, and metabolomics. This approach is redundant since the mode-action-action biomarkers of approved therapeutic proteins are already available, as compiled in this paper for the first time. Other potential biomarkers are receptor binding and pharmacokinetic profiling, which can be made more relevant to ensure biosimilarity without requiring biosimilar developers to conduct extensive research, for which they are rarely qualified.
Collapse
Affiliation(s)
- Sarfaraz K Niazi
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Illinois, Chicago, IL 60612, USA
| |
Collapse
|
3
|
Atanasova M, Nicholls RA, Joosten RP, Agirre J. Updated restraint dictionaries for carbohydrates in the pyranose form. Acta Crystallogr D Struct Biol 2022; 78:455-465. [PMID: 35362468 PMCID: PMC8972801 DOI: 10.1107/s2059798322001103] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Accepted: 01/31/2022] [Indexed: 11/10/2022] Open
Abstract
Restraint dictionaries are used during macromolecular structure refinement to encapsulate intramolecular connectivity and geometric information. These dictionaries allow previously determined `ideal' values of features such as bond lengths, angles and torsions to be used as restraint targets. During refinement, restraints influence the model to adopt a conformation that agrees with prior observation. This is especially important when refining crystal structures of glycosylated proteins, as their resolutions tend to be worse than those of nonglycosylated proteins. Pyranosides, the overwhelming majority component in all forms of protein glycosylation, often display conformational errors in crystal structures. Whilst many of these flaws usually relate to model building, refinement issues may also have their root in suboptimal restraint dictionaries. In order to avoid subsequent misinterpretation and to improve the quality of all pyranose monosaccharide entries in the CCP4 Monomer Library, new dictionaries with improved ring torsion restraints, coordinates reflecting the lowest-energy ring pucker and updated geometry have been produced and evaluated. These new dictionaries are now part of the CCP4 Monomer Library and will be released with CCP4 version 8.0.
Collapse
Affiliation(s)
- Mihaela Atanasova
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| | - Robert A. Nicholls
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Robbie P. Joosten
- Biochemistry Department, Netherlands Cancer Institute, Amsterdam, The Netherlands
- Oncode Institute, The Netherlands
| | - Jon Agirre
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| |
Collapse
|
4
|
Scherbinina SI, Frank M, Toukach PV. Carbohydrate structure database (CSDB) oligosaccharide conformation tool. Glycobiology 2022; 32:460-468. [PMID: 35275211 DOI: 10.1093/glycob/cwac011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Revised: 02/17/2022] [Accepted: 03/04/2022] [Indexed: 11/13/2022] Open
Abstract
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.
Collapse
Affiliation(s)
- S I Scherbinina
- Higher Chemical College, D. Mendeleev University of Chemical Technology of Russia, Miusskaya Square 9, 125047 Moscow, Russia
| | - M Frank
- Biognos AB, Box 8963, 40274 Göteborg, Sweden
| | - P V Toukach
- N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Science, Leninsky prospect 47, 119991 Moscow, Russia
| |
Collapse
|
5
|
Joosten RP, Nicholls RA, Agirre J. Towards consistency in geometry restraints for carbohydrates in the pyranose form: modern dictionary generators reviewed. Curr Med Chem 2021; 29:1193-1207. [PMID: 34477506 PMCID: PMC7612510 DOI: 10.2174/0929867328666210902140754] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 08/03/2021] [Accepted: 08/07/2021] [Indexed: 11/23/2022]
Abstract
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.
Collapse
Affiliation(s)
- Robbie P Joosten
- Oncode Institute and Division of Biochemistry, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam. Netherlands
| | - Robert A Nicholls
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH. United Kingdom
| | - Jon Agirre
- York Structural Biology Laboratory, Department of Chemistry, University of York, YO10 5DD. United Kingdom
| |
Collapse
|
6
|
Scherbinina SI, Toukach PV. Three-Dimensional Structures of Carbohydrates and Where to Find Them. Int J Mol Sci 2020; 21:E7702. [PMID: 33081008 PMCID: PMC7593929 DOI: 10.3390/ijms21207702] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Revised: 10/15/2020] [Accepted: 10/16/2020] [Indexed: 02/06/2023] Open
Abstract
Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.
Collapse
Affiliation(s)
- Sofya I. Scherbinina
- N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Science, Leninsky prospect 47, 119991 Moscow, Russia
- Higher Chemical College, D. Mendeleev University of Chemical Technology of Russia, Miusskaya Square 9, 125047 Moscow, Russia
| | - Philip V. Toukach
- N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Science, Leninsky prospect 47, 119991 Moscow, Russia
| |
Collapse
|
7
|
Bagdonas H, Ungar D, Agirre J. Leveraging glycomics data in glycoprotein 3D structure validation with Privateer. Beilstein J Org Chem 2020; 16:2523-2533. [PMID: 33093930 PMCID: PMC7554661 DOI: 10.3762/bjoc.16.204] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Accepted: 10/06/2020] [Indexed: 12/20/2022] Open
Abstract
The heterogeneity, mobility and complexity of glycans in glycoproteins have been, and currently remain, significant challenges in structural biology. These aspects present unique problems to the two most prolific techniques: X-ray crystallography and cryo-electron microscopy. At the same time, advances in mass spectrometry have made it possible to get deeper insights on precisely the information that is most difficult to recover by structure solution methods: the full-length glycan composition, including linkage details for the glycosidic bonds. The developments have given rise to glycomics. Thankfully, several large scale glycomics initiatives have stored results in publicly available databases, some of which can be accessed through API interfaces. In the present work, we will describe how the Privateer carbohydrate structure validation software has been extended to harness results from glycomics projects, and its use to greatly improve the validation of 3D glycoprotein structures.
Collapse
Affiliation(s)
- Haroldas Bagdonas
- York Structural Biology Laboratory, Department of Chemistry, University of York, Wentworth Way, York, YO10 5DD, UK
| | - Daniel Ungar
- Department of Biology, University of York, Wentworth Way, York, YO10 5DD, UK
| | - Jon Agirre
- York Structural Biology Laboratory, Department of Chemistry, University of York, Wentworth Way, York, YO10 5DD, UK
| |
Collapse
|
8
|
Hendrickx J, Tran V, Sanejouand YH. Numerous severely twisted N-acetylglucosamine conformations found in the protein databank. Proteins 2020; 88:1376-1383. [PMID: 32506721 DOI: 10.1002/prot.25957] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 05/12/2020] [Accepted: 05/27/2020] [Indexed: 11/11/2022]
Abstract
Taking advantage of the known planarity of the N-acetyl group of N-acetylglucosamine, an analysis of the quality of carbohydrate structures found in the protein databank was performed. Few obvious defects of the local geometry of the carbonyl group were observed. However, the N-acetyl group was often found in the less favorable cis conformation (12% of the cases). It was also found severely twisted in numerous instances, especially in structures with a resolution poorer than 1.9 Å determined between 2000 and 2015. Though the automated PDB-REDO procedure has proved able to improve nearly 85% of the structural models deposited to the PDB, and does prove able to cure most severely twisted conformations of the N-acetyl group, it fails to correct its high rate of cis conformations. More generally, for structures with a resolution poorer than 1.6 Å, it produces N-acetylglucosamine models in slightly poorer agreement with experimental data, as measured using real-space correlation coefficients. Significant improvements are thus still needed, at least as far as this carbohydrate structure is concerned.
Collapse
Affiliation(s)
| | - Vinh Tran
- UFIP, UMR CNRS 6286, Université de Nantes, Nantes, France
| | | |
Collapse
|
9
|
Atanasova M, Bagdonas H, Agirre J. Structural glycobiology in the age of electron cryo-microscopy. Curr Opin Struct Biol 2020; 62:70-78. [DOI: 10.1016/j.sbi.2019.12.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Revised: 11/20/2019] [Accepted: 12/02/2019] [Indexed: 01/05/2023]
|
10
|
Böhm M, Bohne-Lang A, Frank M, Loss A, Rojas-Macias MA, Lütteke T. Glycosciences.DB: an annotated data collection linking glycomics and proteomics data (2018 update). Nucleic Acids Res 2020; 47:D1195-D1201. [PMID: 30357361 PMCID: PMC6323918 DOI: 10.1093/nar/gky994] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Accepted: 10/12/2018] [Indexed: 12/21/2022] Open
Abstract
Glycosciences.DB, the glycan structure database of the Glycosciences.de portal, collects various kinds of data on glycan structures, including carbohydrate moieties from worldwide Protein Data Bank (wwPDB) structures. This way it forms a bridge between glycomics and proteomics resources. A major update of this database combines a redesigned web interface with a series of new functions. These include separate entry pages not only for glycan structures but also for literature references and wwPDB entries, improved substructure search options, a newly available keyword search covering all types of entries in one query, and new types of information that is added to glycan structures. These new features are described in detail in this article, and options how users can provide information to the database are discussed as well. Glycosciences.DB is available at http://www.glycosciences.de/database/ and can be freely accessed.
Collapse
Affiliation(s)
- Michael Böhm
- Institute of Veterinary Physiology and Biochemistry, Justus-Liebig University Giessen, Frankfurter Str. 100, 35392 Giessen, Germany
| | - Andreas Bohne-Lang
- Medical Faculty Mannheim, University Heidelberg, Ludolf-Krehl-Str. 13-17, 68167 Mannheim, Germany
| | - Martin Frank
- Biognos AB, Generatorsgatan 1, Box 8963, 40274 Göteborg, Sweden
| | - Alexander Loss
- Gebrüder Gerstenberg GmbH & Co. KG, EDV, Rathausstraße 18-20, 31134 Hildesheim, Germany
| | - Miguel A Rojas-Macias
- Institute of Veterinary Physiology and Biochemistry, Justus-Liebig University Giessen, Frankfurter Str. 100, 35392 Giessen, Germany
| | - Thomas Lütteke
- Institute of Veterinary Physiology and Biochemistry, Justus-Liebig University Giessen, Frankfurter Str. 100, 35392 Giessen, Germany
| |
Collapse
|
11
|
Copoiu L, Malhotra S. The current structural glycome landscape and emerging technologies. Curr Opin Struct Biol 2020; 62:132-139. [PMID: 32006784 DOI: 10.1016/j.sbi.2019.12.020] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Revised: 12/23/2019] [Accepted: 12/24/2019] [Indexed: 11/19/2022]
Abstract
Carbohydrates represent one of the building blocks of life, along with nucleic acids, proteins and lipids. Although glycans are involved in a wide range of processes from embryogenesis to protein trafficking and pathogen infection, we are still a long way from deciphering the glycocode. In this review, we aim to present a few of the challenges that researchers working in the area of glycobiology can encounter and what strategies can be utilised to overcome them. Our goal is to paint a comprehensive picture of the current saccharide landscape available in the Protein Data Bank (PDB). We also review recently updated repositories relevant to the topic proposed, the impact of software development on strategies to structurally solve carbohydrate moieties, and state-of-the-art molecular and cellular biology methods that can shed some light on the function and structure of glycans.
Collapse
Affiliation(s)
- Liviu Copoiu
- Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge CB2 1GA, United Kingdom
| | - Sony Malhotra
- Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck College, University of London, Malet Street, London WC1E 7HX, United Kingdom.
| |
Collapse
|
12
|
de Meirelles JL, Nepomuceno FC, Peña-García J, Schmidt RR, Pérez-Sánchez H, Verli H. Current Status of Carbohydrates Information in the Protein Data Bank. J Chem Inf Model 2020; 60:684-699. [PMID: 31961683 DOI: 10.1021/acs.jcim.9b00874] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Carbohydrates are well known for their physicochemical, biological, functional, and therapeutic characteristics. Unfortunately, their chemical nature imposes severe challenges for the structural elucidation of these phenomena, impairing not only the depth of our understanding of carbohydrates but also the development of new biotechnological and therapeutic applications based on these molecules. In the recent past, the amount of structural information, obtained mainly from X-ray crystallography, has increased progressively, as well as its quality. In this context, the current work presents a global analysis of the carbohydrate information available in the Protein Data Bank (PDB). From high quality structures, it is clear that most of the data are highly concentrated on a few sets of residue types, on their monosaccharidic forms, and connected by a small diversity of glycosidic linkages. The geometries of these linkages can be mostly associated with the types of linkages instead of residues, while the level of puckering distortion was characterized, quantified, and located in a pseudorotational equilibrium landscape, not only to local minima but also to transitional states. These qualitative and quantitative analyses offer a global picture of the carbohydrate structural content in the PDB, potentially supporting the building of new models for carbohydrate-related biological phenomena at the atomistic level, including new developments on force field parameters.
Collapse
Affiliation(s)
- João L de Meirelles
- Programa de Pos-Graduacao em Biologia Celular e Molecular (PPGBCM), Centro de Biotecnologia , Universidade Federal do Rio Grande do Sul (UFRGS) , Av. Bento Goncalves, 9500 , Porto Alegre , Brazil 91509-900
| | - Felipe C Nepomuceno
- Programa de Pos-Graduacao em Biologia Celular e Molecular (PPGBCM), Centro de Biotecnologia , Universidade Federal do Rio Grande do Sul (UFRGS) , Av. Bento Goncalves, 9500 , Porto Alegre , Brazil 91509-900
| | - Jorge Peña-García
- Bioinformatics and High Performance Computing Research Group (BIO-HPC), Computer Engineering Department , Universidad Católica de Murcia (UCAM) , Murcia , Spain 30107
| | - Ricardo Rodríguez Schmidt
- Bioinformatics and High Performance Computing Research Group (BIO-HPC), Computer Engineering Department , Universidad Católica de Murcia (UCAM) , Murcia , Spain 30107
| | - Horacio Pérez-Sánchez
- Bioinformatics and High Performance Computing Research Group (BIO-HPC), Computer Engineering Department , Universidad Católica de Murcia (UCAM) , Murcia , Spain 30107
| | - Hugo Verli
- Programa de Pos-Graduacao em Biologia Celular e Molecular (PPGBCM), Centro de Biotecnologia , Universidade Federal do Rio Grande do Sul (UFRGS) , Av. Bento Goncalves, 9500 , Porto Alegre , Brazil 91509-900
| |
Collapse
|
13
|
van Beusekom B, Wezel N, Hekkelman ML, Perrakis A, Emsley P, Joosten RP. Building and rebuilding N-glycans in protein structure models. Acta Crystallogr D Struct Biol 2019; 75:416-425. [PMID: 30988258 PMCID: PMC6465985 DOI: 10.1107/s2059798319003875] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 03/20/2019] [Indexed: 01/16/2023] Open
Abstract
N-Glycosylation is one of the most common post-translational modifications and is implicated in, for example, protein folding and interaction with ligands and receptors. N-Glycosylation trees are complex structures of linked carbohydrate residues attached to asparagine residues. While carbohydrates are typically modeled in protein structures, they are often incomplete or have the wrong chemistry. Here, new tools are presented to automatically rebuild existing glycosylation trees, to extend them where possible, and to add new glycosylation trees if they are missing from the model. The method has been incorporated in the PDB-REDO pipeline and has been applied to build or rebuild 16 452 carbohydrate residues in 11 651 glycosylation trees in 4498 structure models, and is also available from the PDB-REDO web server. With better modeling of N-glycosylation, the biological function of this important modification can be better and more easily understood.
Collapse
Affiliation(s)
- Bart van Beusekom
- Department of Biochemistry, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Natasja Wezel
- Department of Biochemistry, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Maarten L. Hekkelman
- Department of Biochemistry, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Anastassis Perrakis
- Department of Biochemistry, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Paul Emsley
- MRC Laboratory for Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge CB2 0QH, England
| | - Robbie P. Joosten
- Department of Biochemistry, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| |
Collapse
|
14
|
Abstract
The representation of carbohydrates in 3D space using symbols is a powerful visualization method, but such representations are lacking in currently available visualization software. The work presented here allows researchers to display carbohydrate 3D structures as 3D-SNFG symbols using LiteMol from a web browser (e.g., v.litemol.org/?loadFromCS=5T3X ). Any PDB ID can be substituted at the end of the URL. Alternatively, the user may enter a PDB ID or upload a structure. LiteMol is available at https://v.litemol.org and automatically depicts any carbohydrate residues as 3D-SNFG symbols. To embed LiteMol in a webpage, visit https://github.com/dsehnal/LiteMol .
Collapse
Affiliation(s)
- David Sehnal
- CEITEC - Central European Institute of Technology , Masaryk University Brno , Kamenice 5 , 625 00 Brno-Bohunice , Czech Republic.,National Centre for Biomolecular Research , Faculty of Science , Kamenice 5 , 625 00 Brno-Bohunice , Czech Republic.,Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory , European Bioinformatics Institute (EMBL-EBI) , Wellcome Genome Campus , Hinxton , Cambridgeshire CB10 1SD , United Kingdom
| | - Oliver C Grant
- Complex Carbohydrate Research Center , University of Georgia , Athens , Georgia 30602 , United States
| |
Collapse
|
15
|
Abstract
Complex carbohydrates are ubiquitous in nature, and together with proteins and nucleic acids they comprise the building blocks of life. But unlike proteins and nucleic acids, carbohydrates form nonlinear polymers, and they are not characterized by robust secondary or tertiary structures but rather by distributions of well-defined conformational states. Their molecular flexibility means that oligosaccharides are often refractory to crystallization, and nuclear magnetic resonance (NMR) spectroscopy augmented by molecular dynamics (MD) simulation is the leading method for their characterization in solution. The biological importance of carbohydrate-protein interactions, in organismal development as well as in disease, places urgency on the creation of innovative experimental and theoretical methods that can predict the specificity of such interactions and quantify their strengths. Additionally, the emerging realization that protein glycosylation impacts protein function and immunogenicity places the ability to define the mechanisms by which glycosylation impacts these features at the forefront of carbohydrate modeling. This review will discuss the relevant theoretical approaches to studying the three-dimensional structures of this fascinating class of molecules and interactions, with reference to the relevant experimental data and techniques that are key for validation of the theoretical predictions.
Collapse
Affiliation(s)
- Robert J Woods
- Complex Carbohydrate Research Center and Department of Biochemistry and Molecular Biology , University of Georgia , 315 Riverbend Road , Athens , Georgia 30602 , United States
| |
Collapse
|
16
|
van Beusekom B, Lütteke T, Joosten RP. Making glycoproteins a little bit sweeter with PDB-REDO. Acta Crystallogr F Struct Biol Commun 2018; 74:463-472. [PMID: 30084395 PMCID: PMC6096482 DOI: 10.1107/s2053230x18004016] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Accepted: 03/07/2018] [Indexed: 02/04/2023] Open
Abstract
Glycosylation is one of the most common forms of protein post-translational modification, but is also the most complex. Dealing with glycoproteins in structure model building, refinement, validation and PDB deposition is more error-prone than dealing with nonglycosylated proteins owing to limitations of the experimental data and available software tools. Also, experimentalists are typically less experienced in dealing with carbohydrate residues than with amino-acid residues. The results of the reannotation and re-refinement by PDB-REDO of 8114 glycoprotein structure models from the Protein Data Bank are analyzed. The positive aspects of 3620 reannotations and subsequent refinement, as well as the remaining challenges to obtaining consistently high-quality carbohydrate models, are discussed.
Collapse
Affiliation(s)
- Bart van Beusekom
- Division of Biochemistry, Netherlands Cancer Insitute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Thomas Lütteke
- Institute of Veterinary Physiology and Biochemistry, Justus-Liebig-University Giessen, Frankfurter Strasse 100, 35392 Giessen, Germany
| | - Robbie P. Joosten
- Division of Biochemistry, Netherlands Cancer Insitute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| |
Collapse
|
17
|
Park SJ, Lee J, Patel DS, Ma H, Lee HS, Jo S, Im W. Glycan Reader is improved to recognize most sugar types and chemical modifications in the Protein Data Bank. Bioinformatics 2018; 33:3051-3057. [PMID: 28582506 DOI: 10.1093/bioinformatics/btx358] [Citation(s) in RCA: 82] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2017] [Accepted: 05/31/2017] [Indexed: 11/12/2022] Open
Abstract
Motivation Glycans play a central role in many essential biological processes. Glycan Reader was originally developed to simplify the reading of Protein Data Bank (PDB) files containing glycans through the automatic detection and annotation of sugars and glycosidic linkages between sugar units and to proteins, all based on atomic coordinates and connectivity information. Carbohydrates can have various chemical modifications at different positions, making their chemical space much diverse. Unfortunately, current PDB files do not provide exact annotations for most carbohydrate derivatives and more than 50% of PDB glycan chains have at least one carbohydrate derivative that could not be correctly recognized by the original Glycan Reader. Results Glycan Reader has been improved and now identifies most sugar types and chemical modifications (including various glycolipids) in the PDB, and both PDB and PDBx/mmCIF formats are supported. CHARMM-GUI Glycan Reader is updated to generate the simulation system and input of various glycoconjugates with most sugar types and chemical modifications. It also offers a new functionality to edit the glycan structures through addition/deletion/modification of glycosylation types, sugar types, chemical modifications, glycosidic linkages, and anomeric states. The simulation system and input files can be used for CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Glycan Fragment Database in GlycanStructure.Org is also updated to provide an intuitive glycan sequence search tool for complex glycan structures with various chemical modifications in the PDB. Availability and implementation http://www.charmm-gui.org/input/glycan and http://www.glycanstructure.org. Contact wonpil@lehigh.edu. Supplementary information Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Sang-Jun Park
- Department of Biological Sciences and Bioengineering Program, Lehigh University, Bethlehem, PA, USA
| | - Jumin Lee
- Department of Biological Sciences and Bioengineering Program, Lehigh University, Bethlehem, PA, USA
| | - Dhilon S Patel
- Department of Biological Sciences and Bioengineering Program, Lehigh University, Bethlehem, PA, USA
| | - Hongjing Ma
- Department of Biological Sciences and Bioengineering Program, Lehigh University, Bethlehem, PA, USA
| | - Hui Sun Lee
- Department of Biological Sciences and Bioengineering Program, Lehigh University, Bethlehem, PA, USA
| | - Sunhwan Jo
- Leadership Computing Facility, Argonne National Laboratory, Argonne, IL, USA
| | - Wonpil Im
- Department of Biological Sciences and Bioengineering Program, Lehigh University, Bethlehem, PA, USA
| |
Collapse
|
18
|
Emsley P, Crispin M. Structural analysis of glycoproteins: building N-linked glycans with Coot. Acta Crystallogr D Struct Biol 2018; 74:256-263. [PMID: 29652253 PMCID: PMC5892875 DOI: 10.1107/s2059798318005119] [Citation(s) in RCA: 76] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2017] [Accepted: 03/29/2018] [Indexed: 12/22/2022] Open
Abstract
Coot is a graphics application that is used to build or manipulate macromolecular models; its particular forte is manipulation of the model at the residue level. The model-building tools of Coot have been combined and extended to assist or automate the building of N-linked glycans. The model is built by the addition of monosaccharides, placed by variation of internal coordinates. The subsequent model is refined by real-space refinement, which is stabilized with modified and additional restraints. It is hoped that these enhanced building tools will help to reduce building errors of N-linked glycans and improve our knowledge of the structures of glycoproteins.
Collapse
Affiliation(s)
- Paul Emsley
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge CB2 0QH, England
| | - Max Crispin
- Centre for Biological Sciences and the Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, England
| |
Collapse
|
19
|
van Beusekom B, Touw WG, Tatineni M, Somani S, Rajagopal G, Luo J, Gilliland GL, Perrakis A, Joosten RP. Homology-based hydrogen bond information improves crystallographic structures in the PDB. Protein Sci 2018; 27:798-808. [PMID: 29168245 PMCID: PMC5818736 DOI: 10.1002/pro.3353] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Revised: 11/16/2017] [Accepted: 11/16/2017] [Indexed: 01/06/2023]
Abstract
The Protein Data Bank (PDB) is the global archive for structural information on macromolecules, and a popular resource for researchers, teachers, and students, amassing more than one million unique users each year. Crystallographic structure models in the PDB (more than 100,000 entries) are optimized against the crystal diffraction data and geometrical restraints. This process of crystallographic refinement typically ignored hydrogen bond (H-bond) distances as a source of information. However, H-bond restraints can improve structures at low resolution where diffraction data are limited. To improve low-resolution structure refinement, we present methods for deriving H-bond information either globally from well-refined high-resolution structures from the PDB-REDO databank, or specifically from on-the-fly constructed sets of homologous high-resolution structures. Refinement incorporating HOmology DErived Restraints (HODER), improves geometrical quality and the fit to the diffraction data for many low-resolution structures. To make these improvements readily available to the general public, we applied our new algorithms to all crystallographic structures in the PDB: using massively parallel computing, we constructed a new instance of the PDB-REDO databank (https://pdb-redo.eu). This resource is useful for researchers to gain insight on individual structures, on specific protein families (as we demonstrate with examples), and on general features of protein structure using data mining approaches on a uniformly treated dataset.
Collapse
Affiliation(s)
- Bart van Beusekom
- Department of BiochemistryNetherlands Cancer Institute, Plesmanlaan 121Amsterdam1066 CXThe Netherlands
| | - Wouter G. Touw
- Department of BiochemistryNetherlands Cancer Institute, Plesmanlaan 121Amsterdam1066 CXThe Netherlands
| | - Mahidhar Tatineni
- San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman DriveLa JollaCalifornia92093‐0505
| | - Sandeep Somani
- Discovery Sciences, Janssen R&D LLCSpring HousePennsylvania
| | | | - Jinquan Luo
- Janssen BioTherapeutics, Janssen R&D LLCSpring HousePennsylvania
| | | | - Anastassis Perrakis
- Department of BiochemistryNetherlands Cancer Institute, Plesmanlaan 121Amsterdam1066 CXThe Netherlands
| | - Robbie P. Joosten
- Department of BiochemistryNetherlands Cancer Institute, Plesmanlaan 121Amsterdam1066 CXThe Netherlands
| |
Collapse
|
20
|
Delbart F, Brams M, Gruss F, Noppen S, Peigneur S, Boland S, Chaltin P, Brandao-Neto J, von Delft F, Touw WG, Joosten RP, Liekens S, Tytgat J, Ulens C. An allosteric binding site of the α7 nicotinic acetylcholine receptor revealed in a humanized acetylcholine-binding protein. J Biol Chem 2017; 293:2534-2545. [PMID: 29237730 PMCID: PMC5818190 DOI: 10.1074/jbc.m117.815316] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Revised: 10/24/2017] [Indexed: 11/06/2022] Open
Abstract
Nicotinic acetylcholine receptors (nAChRs) belong to the family of pentameric ligand-gated ion channels and mediate fast excitatory transmission in the central and peripheral nervous systems. Among the different existing receptor subtypes, the homomeric α7 nAChR has attracted considerable attention because of its possible implication in several neurological and psychiatric disorders, including cognitive decline associated with Alzheimer's disease or schizophrenia. Allosteric modulators of ligand-gated ion channels are of particular interest as therapeutic agents, as they modulate receptor activity without affecting normal fluctuations of synaptic neurotransmitter release. Here, we used X-ray crystallography and surface plasmon resonance spectroscopy of α7-acetylcholine-binding protein (AChBP), a humanized chimera of a snail AChBP, which has 71% sequence similarity with the extracellular ligand-binding domain of the human α7 nAChR, to investigate the structural determinants of allosteric modulation. We extended previous observations that an allosteric site located in the vestibule of the receptor offers an attractive target for receptor modulation. We introduced seven additional humanizing mutations in the vestibule-located binding site of AChBP to improve its suitability as a model for studying allosteric binding. Using a fragment-based screening approach, we uncovered an allosteric binding site located near the β8-β9 loop, which critically contributes to coupling ligand binding to channel opening in human α7 nAChR. This work expands our understanding of the topology of allosteric binding sites in AChBP and, by extrapolation, in the human α7 nAChR as determined by electrophysiology measurements. Our insights pave the way for drug design strategies targeting nAChRs involved in ion channel-mediated disorders.
Collapse
Affiliation(s)
- Florian Delbart
- From the Department of Cellular and Molecular Medicine, Laboratory of Structural Neurobiology, Faculty of Medicine, KU Leuven, 3000 Leuven, Belgium
| | - Marijke Brams
- From the Department of Cellular and Molecular Medicine, Laboratory of Structural Neurobiology, Faculty of Medicine, KU Leuven, 3000 Leuven, Belgium
| | - Fabian Gruss
- From the Department of Cellular and Molecular Medicine, Laboratory of Structural Neurobiology, Faculty of Medicine, KU Leuven, 3000 Leuven, Belgium
| | - Sam Noppen
- the Department of Microbiology and Immunology, Laboratory of Virology and Chemotherapy, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium
| | - Steve Peigneur
- the Laboratory of Toxicology and Pharmacology, Faculty of Pharmaceutical Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Sandro Boland
- the Center for Innovation and Stimulation of Drug Discovery Leuven, Cistim Leuven vzw, 3001 Heverlee, Belgium
| | - Patrick Chaltin
- the Center for Innovation and Stimulation of Drug Discovery Leuven, Cistim Leuven vzw, 3001 Heverlee, Belgium.,the Center for Innovation and Stimulation of Drug Discovery Leuven and Center for Drug Design and Discovery, KU Leuven, 3001 Heverlee, Belgium
| | - Jose Brandao-Neto
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0QX, United Kingdom, and
| | - Frank von Delft
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0QX, United Kingdom, and
| | - Wouter G Touw
- the Division of Biochemistry, Netherlands Cancer Institute, 1066CX Amsterdam, The Netherlands
| | - Robbie P Joosten
- the Division of Biochemistry, Netherlands Cancer Institute, 1066CX Amsterdam, The Netherlands
| | - Sandra Liekens
- the Department of Microbiology and Immunology, Laboratory of Virology and Chemotherapy, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium
| | - Jan Tytgat
- the Laboratory of Toxicology and Pharmacology, Faculty of Pharmaceutical Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Chris Ulens
- From the Department of Cellular and Molecular Medicine, Laboratory of Structural Neurobiology, Faculty of Medicine, KU Leuven, 3000 Leuven, Belgium,
| |
Collapse
|
21
|
Agirre J, Davies GJ, Wilson KS, Cowtan KD. Carbohydrate structure: the rocky road to automation. Curr Opin Struct Biol 2016; 44:39-47. [PMID: 27940408 DOI: 10.1016/j.sbi.2016.11.011] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Revised: 10/26/2016] [Accepted: 11/10/2016] [Indexed: 11/29/2022]
Abstract
With the introduction of intuitive graphical software, structural biologists who are not experts in crystallography are now able to build complete protein or nucleic acid models rapidly. In contrast, carbohydrates are in a wholly different situation: scant automation exists, with manual building attempts being sometimes toppled by incorrect dictionaries or refinement problems. Sugars are the most stereochemically complex family of biomolecules and, as pyranose rings, have clear conformational preferences. Despite this, all refinement programs may produce high-energy conformations at medium to low resolution, without any support from the electron density. This problem renders the affected structures unusable in glyco-chemical terms. Bringing structural glycobiology up to 'protein standards' will require a total overhaul of the methodology. Time is of the essence, as the community is steadily increasing the production rate of glycoproteins, and electron cryo-microscopy has just started to image them in precisely that resolution range where crystallographic methods falter most.
Collapse
Affiliation(s)
- Jon Agirre
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, UK.
| | - Gideon J Davies
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, UK
| | - Keith S Wilson
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, UK
| | - Kevin D Cowtan
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, UK.
| |
Collapse
|