1
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Dahmani Z, Scott AL, Vénien-Bryan C, Perahia D, Costa MG. MDFF_NM: Improved Molecular Dynamics Flexible Fitting into Cryo-EM Density Maps with a Multireplica Normal Mode-Based Search. J Chem Inf Model 2024; 64:5151-5160. [PMID: 38907694 PMCID: PMC11234365 DOI: 10.1021/acs.jcim.3c02007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 06/17/2024] [Accepted: 06/17/2024] [Indexed: 06/24/2024]
Abstract
Molecular Dynamics Flexible Fitting (MDFF) is a widely used tool to refine high-resolution structures into cryo-EM density maps. Despite many successful applications, MDFF is still limited by its high computational cost, overfitting, accuracy, and performance issues due to entrapment within wrong local minima. Modern ensemble-based MDFF tools have generated promising results in the past decade. In line with these studies, we present MDFF_NM, a stochastic hybrid flexible fitting algorithm combining Normal Mode Analysis (NMA) and simulation-based flexible fitting. Initial tests reveal that, besides accelerating the fitting process, MDFF_NM increases the diversity of fitting routes leading to the target, uncovering ensembles of conformations in closer agreement with experimental data. The potential integration of MDFF_NM with other existing methods and integrative modeling pipelines is also discussed.
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Affiliation(s)
- Zakaria
L. Dahmani
- School
of Medicine, Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch I Bldg, 3420 Forbes Avenue, Pittsburgh, Pennsylvania 15260, United States
- UMR
7590, CNRS, Museum National d’Histoire Naturelle, Institut
de Minéralogie, Physique des Matériaux et Cosmochimie,
IMPMC, Sorbonne Université, 4 place Jussieu, Paris 75005, France
| | - Ana Ligia Scott
- CMCC,
Computational Biophysics and Biology, Universidade Federal do ABC, Avenida dos Estados 5001, São Paulo, Santo André 09210-580, Brazil
- Université
de Strasbourg—IGBMC—Departament de Biologie structurale
integrative, 1 rue Laurent
Fries BP, Illkirch 10142
67404, CEDEX, France
| | - Catherine Vénien-Bryan
- UMR
7590, CNRS, Museum National d’Histoire Naturelle, Institut
de Minéralogie, Physique des Matériaux et Cosmochimie,
IMPMC, Sorbonne Université, 4 place Jussieu, Paris 75005, France
| | - David Perahia
- Laboratoire
de Biologie et Pharmacologie Appliquée, UMR 8113, École
Normale Supérieure Paris-Saclay, Gif-sur-Yvette 91190, France
| | - Mauricio G.S Costa
- UMR
7590, CNRS, Museum National d’Histoire Naturelle, Institut
de Minéralogie, Physique des Matériaux et Cosmochimie,
IMPMC, Sorbonne Université, 4 place Jussieu, Paris 75005, France
- Laboratoire
de Biologie et Pharmacologie Appliquée, UMR 8113, École
Normale Supérieure Paris-Saclay, Gif-sur-Yvette 91190, France
- Programa de Computação Científica,
Vice-Presidência de Educação, Informação
e Comunicação, Fundação Oswaldo Cruz, Av.Brasil 4365, Residência
Oficial, Manguinhos, Rio de Janeiro 21040-900, Brazil
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2
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Beton JG, Mulvaney T, Cragnolini T, Topf M. Cryo-EM structure and B-factor refinement with ensemble representation. Nat Commun 2024; 15:444. [PMID: 38200043 PMCID: PMC10781738 DOI: 10.1038/s41467-023-44593-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 12/20/2023] [Indexed: 01/12/2024] Open
Abstract
Cryo-EM experiments produce images of macromolecular assemblies that are combined to produce three-dimensional density maps. Typically, atomic models of the constituent molecules are fitted into these maps, followed by a density-guided refinement. We introduce TEMPy-ReFF, a method for atomic structure refinement in cryo-EM density maps. Our method represents atomic positions as components of a Gaussian mixture model, utilising their variances as B-factors, which are used to derive an ensemble description. Extensively tested on a substantial dataset of 229 cryo-EM maps from EMDB ranging in resolution from 2.1-4.9 Å with corresponding PDB and CERES atomic models, our results demonstrate that TEMPy-ReFF ensembles provide a superior representation of cryo-EM maps. On a single-model basis, it performs similarly to the CERES re-refinement protocol, although there are cases where it provides a better fit to the map. Furthermore, our method enables the creation of composite maps free of boundary artefacts. TEMPy-ReFF is useful for better interpretation of flexible structures, such as those involving RNA, DNA or ligands.
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Affiliation(s)
- Joseph G Beton
- Leibniz Institute of Virology (LIV) and Universitätsklinikum Hamburg Eppendorf (UKE), Centre for Structural Systems Biology (CSSB), 22607, Hamburg, Germany
| | - Thomas Mulvaney
- Leibniz Institute of Virology (LIV) and Universitätsklinikum Hamburg Eppendorf (UKE), Centre for Structural Systems Biology (CSSB), 22607, Hamburg, Germany
| | - Tristan Cragnolini
- Leibniz Institute of Virology (LIV) and Universitätsklinikum Hamburg Eppendorf (UKE), Centre for Structural Systems Biology (CSSB), 22607, Hamburg, Germany
- Institute of Structural and Molecular Biology, Birkbeck, University of London, London, UK
| | - Maya Topf
- Leibniz Institute of Virology (LIV) and Universitätsklinikum Hamburg Eppendorf (UKE), Centre for Structural Systems Biology (CSSB), 22607, Hamburg, Germany.
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3
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Park J, Joung I, Joo K, Lee J. Application of conformational space annealing to the protein structure modeling using cryo-EM maps. J Comput Chem 2023; 44:2332-2346. [PMID: 37585026 DOI: 10.1002/jcc.27200] [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] [Received: 12/08/2022] [Revised: 04/26/2023] [Accepted: 07/16/2023] [Indexed: 08/17/2023]
Abstract
Conformational space annealing (CSA), a global optimization method, has been applied to various protein structure modeling tasks. In this paper, we applied CSA to the cryo-EM structure modeling task by combining the python subroutine of CSA (PyCSA) and the fast relax (FastRelax) protocol of PyRosetta. Refinement of initial structures generated from two methods, rigid fitting of predicted structures to the Cryo-EM map and de novo protein modeling by tracing the Cryo-EM map, was performed by CSA. In the refinement of the rigid-fitted structures, the final models showed that CSA can generate reliable atomic structures of proteins, even when large movements of protein domains were required. In the de novo modeling case, although the overall structural qualities of the final models were rather dependent on the initial models, the final models generated by CSA showed improved MolProbity scores and cross-correlation coefficients to the maps. These results suggest that CSA can accomplish flexible fitting and refinement together by sampling diverse conformations effectively and thus can be utilized for cryo-EM structure modeling.
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Affiliation(s)
| | | | - Keehyoung Joo
- Center for Advanced Computations, Korea Institute for Advanced Study, Seoul, South Korea
| | - Jooyoung Lee
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul, South Korea
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4
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Cassidy CK, Qin Z, Frosio T, Gosink K, Yang Z, Sansom MSP, Stansfeld PJ, Parkinson JS, Zhang P. Structure of the native chemotaxis core signaling unit from phage E-protein lysed E. coli cells. mBio 2023; 14:e0079323. [PMID: 37772839 PMCID: PMC10653900 DOI: 10.1128/mbio.00793-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 08/09/2023] [Indexed: 09/30/2023] Open
Abstract
IMPORTANCE Bacterial chemotaxis is a ubiquitous behavior that enables cell movement toward or away from specific chemicals. It serves as an important model for understanding cell sensory signal transduction and motility. Characterization of the molecular mechanisms underlying chemotaxis is of fundamental interest and requires a high-resolution structural picture of the sensing machinery, the chemosensory array. In this study, we combine cryo-electron tomography and molecular simulation to present the complete structure of the core signaling unit, the basic building block of chemosensory arrays, from Escherichia coli. Our results provide new insight into previously poorly-resolved regions of the complex and offer a structural basis for designing new experiments to test mechanistic hypotheses.
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Affiliation(s)
- C. Keith Cassidy
- Diamond Light Source, Didcot, United Kingdom
- Department of Physics and Astronomy, University of Missouri-Columbia, Columbia, Missouri, USA
| | - Zhuan Qin
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | | | - Khoosheh Gosink
- School of Biological Sciences, University of Utah, Salt Lake City, Utah, USA
| | | | - Mark S. P. Sansom
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
| | | | - John S. Parkinson
- School of Biological Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Peijun Zhang
- Diamond Light Source, Didcot, United Kingdom
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Chinese Academy of Medical Sciences Oxford Institute, University of Oxford, Oxford, United Kingdom
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5
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Miyashita O, Tama F. Advancing cryo-electron microscopy data analysis through accelerated simulation-based flexible fitting approaches. Curr Opin Struct Biol 2023; 82:102653. [PMID: 37451233 DOI: 10.1016/j.sbi.2023.102653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Revised: 05/30/2023] [Accepted: 06/19/2023] [Indexed: 07/18/2023]
Abstract
Flexible fitting based on molecular dynamics simulation is a technique for structure modeling from cryo-EM data. It has been utilized for nearly two decades, and while cryo-EM resolution has improved significantly, it remains a powerful approach that can provide structural and dynamical insights that are not directly accessible from experimental data alone. Molecular dynamics simulations provide a means to extract atomistic details of conformational changes that are encoded in cryo-EM data and can also assist in improving the quality of structural models. Additionally, molecular dynamics simulations enable the characterization of conformational heterogeneity in cryo-EM data. We will summarize the advancements made in these techniques and highlight recent developments in this field.
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Affiliation(s)
- Osamu Miyashita
- RIKEN Center for Computational Science, 6-7-1, Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.
| | - Florence Tama
- RIKEN Center for Computational Science, 6-7-1, Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; Department of Physics, Graduate School of Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602, Japan; Institute of Transformative Bio-Molecules, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602, Japan.
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6
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Sarkar D, Lee H, Vant JW, Turilli M, Vermaas JV, Jha S, Singharoy A. Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting. J Chem Inf Model 2023; 63:5834-5846. [PMID: 37661856 DOI: 10.1021/acs.jcim.3c00350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Recent advances in cryo-electron microscopy (cryo-EM) have enabled modeling macromolecular complexes that are essential components of the cellular machinery. The density maps derived from cryo-EM experiments are often integrated with manual, knowledge-driven or artificial intelligence-driven and physics-guided computational methods to build, fit, and refine molecular structures. Going beyond a single stationary-structure determination scheme, it is becoming more common to interpret the experimental data with an ensemble of models that contributes to an average observation. Hence, there is a need to decide on the quality of an ensemble of protein structures on-the-fly while refining them against the density maps. We introduce such an adaptive decision-making scheme during the molecular dynamics flexible fitting (MDFF) of biomolecules. Using RADICAL-Cybertools, the new RADICAL augmented MDFF implementation (R-MDFF) is examined in high-performance computing environments for refinement of two prototypical protein systems, adenylate kinase and carbon monoxide dehydrogenase. For these test cases, use of multiple replicas in flexible fitting with adaptive decision making in R-MDFF improves the overall correlation to the density by 40% relative to the refinements of the brute-force MDFF. The improvements are particularly significant at high, 2-3 Å map resolutions. More importantly, the ensemble model captures key features of biologically relevant molecular dynamics that are inaccessible to a single-model interpretation. Finally, the pipeline is applicable to systems of growing sizes, which is demonstrated using ensemble refinement of capsid proteins from the chimpanzee adenovirus. The overhead for decision making remains low and robust to computing environments. The software is publicly available on GitHub and includes a short user guide to install R-MDFF on different computing environments, from local Linux-based workstations to high-performance computing environments.
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Affiliation(s)
- Daipayan Sarkar
- MSU-DOE Plant Research Laboratory, East Lansing, Michigan 48824, United States
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85281, United States
| | - Hyungro Lee
- Pacific Northwest National Laboratory, Richland, Washington 99354, United States
- Electrical & Computer Engineering, Rutgers University, New Brunswick, New Jersey 08854, United States
| | - John W Vant
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85281, United States
| | - Matteo Turilli
- Electrical & Computer Engineering, Rutgers University, New Brunswick, New Jersey 08854, United States
- Computational Science Initiative, Brookhaven National Laboratory, Upton, New York 11973, United States
| | - Josh V Vermaas
- MSU-DOE Plant Research Laboratory, East Lansing, Michigan 48824, United States
| | - Shantenu Jha
- Electrical & Computer Engineering, Rutgers University, New Brunswick, New Jersey 08854, United States
- Computational Science Initiative, Brookhaven National Laboratory, Upton, New York 11973, United States
| | - Abhishek Singharoy
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85281, United States
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7
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Maddhuri Venkata Subramaniya SR, Terashi G, Kihara D. Enhancing cryo-EM maps with 3D deep generative networks for assisting protein structure modeling. Bioinformatics 2023; 39:btad494. [PMID: 37549063 PMCID: PMC10444963 DOI: 10.1093/bioinformatics/btad494] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/28/2023] [Accepted: 08/04/2023] [Indexed: 08/09/2023] Open
Abstract
MOTIVATION The tertiary structures of an increasing number of biological macromolecules have been determined using cryo-electron microscopy (cryo-EM). However, there are still many cases where the resolution is not high enough to model the molecular structures with standard computational tools. If the resolution obtained is near the empirical borderline (3-4.5 Å), improvement in the map quality facilitates structure modeling. RESULTS We report EM-GAN, a novel approach that modifies an input cryo-EM map to assist protein structure modeling. The method uses a 3D generative adversarial network (GAN) that has been trained on high- and low-resolution density maps to learn the density patterns, and modifies the input map to enhance its suitability for modeling. The method was tested extensively on a dataset of 65 EM maps in the resolution range of 3-6 Å and showed substantial improvements in structure modeling using popular protein structure modeling tools. AVAILABILITY AND IMPLEMENTATION https://github.com/kiharalab/EM-GAN, Google Colab: https://tinyurl.com/3ccxpttx.
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Affiliation(s)
| | - Genki Terashi
- Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, United States
| | - Daisuke Kihara
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, United States
- Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, United States
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8
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Chauvier A, Porta JC, Deb I, Ellinger E, Meze K, Frank AT, Ohi MD, Walter NG. Structural basis for control of bacterial RNA polymerase pausing by a riboswitch and its ligand. Nat Struct Mol Biol 2023; 30:902-913. [PMID: 37264140 PMCID: PMC10523900 DOI: 10.1038/s41594-023-01002-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 04/20/2023] [Indexed: 06/03/2023]
Abstract
Folding of nascent transcripts can be modulated by the RNA polymerase (RNAP) that carries out their transcription, and vice versa. A pause of RNAP during transcription of a preQ1 riboswitch (termed que-PEC) is stabilized by a previously characterized template consensus sequence and the ligand-free conformation of the nascent RNA. Ligand binding to the riboswitch induces RNAP pause release and downstream transcription termination; however, the mechanism by which riboswitch folding modulates pausing is unclear. Here, we report single-particle cryo-electron microscopy reconstructions of que-PEC in ligand-free and ligand-bound states. In the absence of preQ1, the RNA transcript is in an unexpected hyper-translocated state, preventing downstream nucleotide incorporation. Strikingly, on ligand binding, the riboswitch rotates around its helical axis, expanding the surrounding RNAP exit channel and repositioning the transcript for elongation. Our study reveals the tight coupling by which nascent RNA structures and their ligands can functionally regulate the macromolecular transcription machinery.
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Affiliation(s)
- Adrien Chauvier
- Single Molecule Analysis Group and Center for RNA Biomedicine, Department of Chemistry, University of Michigan, Ann Arbor, MI, USA
| | - Jason C Porta
- Life Sciences Institute, University of Michigan, Ann Arbor, MI, USA
| | - Indrajit Deb
- Biophysics Program, University of Michigan, Ann Arbor, MI, USA
- Drug Discovery Unit, School of Life Sciences, University of Dundee, Dundee, UK
| | - Emily Ellinger
- Single Molecule Analysis Group and Center for RNA Biomedicine, Department of Chemistry, University of Michigan, Ann Arbor, MI, USA
| | - Katarina Meze
- Single Molecule Analysis Group and Center for RNA Biomedicine, Department of Chemistry, University of Michigan, Ann Arbor, MI, USA
- Life Sciences Institute, University of Michigan, Ann Arbor, MI, USA
| | - Aaron T Frank
- Biophysics Program, University of Michigan, Ann Arbor, MI, USA
- Arrakis Therapeutics, Waltham, MA, USA
| | - Melanie D Ohi
- Life Sciences Institute, University of Michigan, Ann Arbor, MI, USA.
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, USA.
| | - Nils G Walter
- Single Molecule Analysis Group and Center for RNA Biomedicine, Department of Chemistry, University of Michigan, Ann Arbor, MI, USA.
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9
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Lynch DL, Pavlova A, Fan Z, Gumbart JC. Understanding Virus Structure and Dynamics through Molecular Simulations. J Chem Theory Comput 2023. [PMID: 37192279 DOI: 10.1021/acs.jctc.3c00116] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Viral outbreaks remain a serious threat to human and animal populations and motivate the continued development of antiviral drugs and vaccines, which in turn benefits from a detailed understanding of both viral structure and dynamics. While great strides have been made in characterizing these systems experimentally, molecular simulations have proven to be an essential, complementary approach. In this work, we review the contributions of molecular simulations to the understanding of viral structure, functional dynamics, and processes related to the viral life cycle. Approaches ranging from coarse-grained to all-atom representations are discussed, including current efforts at modeling complete viral systems. Overall, this review demonstrates that computational virology plays an essential role in understanding these systems.
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Affiliation(s)
- Diane L Lynch
- School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Anna Pavlova
- School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Zixing Fan
- Interdisciplinary Bioengineering Graduate Program, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - James C Gumbart
- School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
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10
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Wozny MR, Di Luca A, Morado DR, Picco A, Khaddaj R, Campomanes P, Ivanović L, Hoffmann PC, Miller EA, Vanni S, Kukulski W. In situ architecture of the ER-mitochondria encounter structure. Nature 2023:10.1038/s41586-023-06050-3. [PMID: 37165187 DOI: 10.1038/s41586-023-06050-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Accepted: 04/04/2023] [Indexed: 05/12/2023]
Abstract
The endoplasmic reticulum and mitochondria are main hubs of eukaryotic membrane biogenesis that rely on lipid exchange via membrane contact sites1-3, but the underpinning mechanisms remain poorly understood. In yeast, tethering and lipid transfer between the two organelles is mediated by the endoplasmic reticulum-mitochondria encounter structure (ERMES), a four-subunit complex of unresolved stoichiometry and architecture4-6. Here we determined the molecular organization of ERMES within Saccharomyces cerevisiae cells using integrative structural biology by combining quantitative live imaging, cryo-correlative microscopy, subtomogram averaging and molecular modelling. We found that ERMES assembles into approximately 25 discrete bridge-like complexes distributed irregularly across a contact site. Each bridge consists of three synaptotagmin-like mitochondrial lipid binding protein domains oriented in a zig-zag arrangement. Our molecular model of ERMES reveals a pathway for lipids. These findings resolve the in situ supramolecular architecture of a major inter-organelle lipid transfer machinery and provide a basis for the mechanistic understanding of lipid fluxes in eukaryotic cells.
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Affiliation(s)
- Michael R Wozny
- MRC Laboratory of Molecular Biology, Cambridge, UK
- Department of Anatomy and Cell Biology, McGill University, Montreal, Quebec, Canada
| | - Andrea Di Luca
- Department of Biology, University of Fribourg, Fribourg, Switzerland
| | - Dustin R Morado
- MRC Laboratory of Molecular Biology, Cambridge, UK
- SciLifeLab, Solna, Sweden
- Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Andrea Picco
- Department of Biochemistry, University of Geneva, Geneva, Switzerland
| | - Rasha Khaddaj
- Institute of Biochemistry and Molecular Medicine, University of Bern, Bern, Switzerland
| | - Pablo Campomanes
- Department of Biology, University of Fribourg, Fribourg, Switzerland
| | - Lazar Ivanović
- Institute of Biochemistry and Molecular Medicine, University of Bern, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
| | - Patrick C Hoffmann
- MRC Laboratory of Molecular Biology, Cambridge, UK
- Max Planck Institute of Biophysics, Frankfurt am Main, Germany
| | | | - Stefano Vanni
- Department of Biology, University of Fribourg, Fribourg, Switzerland.
| | - Wanda Kukulski
- MRC Laboratory of Molecular Biology, Cambridge, UK.
- Institute of Biochemistry and Molecular Medicine, University of Bern, Bern, Switzerland.
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11
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Dietz L, Ellison CJ, Riechmann C, Cassidy CK, Felfoldi FD, Pinto-Fernández A, Kessler BM, Elliott PR. Structural basis for SMAC-mediated antagonism of caspase inhibition by the giant ubiquitin ligase BIRC6. Science 2023; 379:1112-1117. [PMID: 36758106 DOI: 10.1126/science.ade8840] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 01/31/2023] [Indexed: 02/11/2023]
Abstract
Certain inhibitor of apoptosis (IAP) family members are sentinel proteins that prevent untimely cell death by inhibiting caspases. Antagonists, including second mitochondria-derived activator of caspases (SMAC), regulate IAPs and drive cell death. Baculoviral IAP repeat-containing protein 6 (BIRC6), a giant IAP with dual E2 and E3 ubiquitin ligase activity, regulates programmed cell death through unknown mechanisms. We show that BIRC6 directly restricts executioner caspase-3 and -7 and ubiquitinates caspase-3, -7, and -9, working exclusively with noncanonical E1, UBA6. Notably, we show that SMAC suppresses both mechanisms. Cryo-electron microscopy structures of BIRC6 alone and in complex with SMAC reveal that BIRC6 is an antiparallel dimer juxtaposing the substrate-binding module against the catalytic domain. Furthermore, we discover that SMAC multisite binding to BIRC6 results in a subnanomolar affinity interaction, enabling SMAC to competitively displace caspases, thus antagonizing BIRC6 anticaspase function.
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Affiliation(s)
- Larissa Dietz
- Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK
| | - Cara J Ellison
- Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK
| | - Carlos Riechmann
- Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK
| | - C Keith Cassidy
- Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK
| | - F Daniel Felfoldi
- Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK
| | - Adán Pinto-Fernández
- Target Discovery Institute, Centre for Medicines Discovery, University of Oxford, Oxford, OX3 7FZ, UK
- Chinese Academy for Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7FZ, UK
| | - Benedikt M Kessler
- Target Discovery Institute, Centre for Medicines Discovery, University of Oxford, Oxford, OX3 7FZ, UK
- Chinese Academy for Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7FZ, UK
| | - Paul R Elliott
- Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK
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12
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Terashi G, Wang X, Kihara D. Protein model refinement for cryo-EM maps using AlphaFold2 and the DAQ score. Acta Crystallogr D Struct Biol 2023; 79:10-21. [PMID: 36601803 PMCID: PMC9815095 DOI: 10.1107/s2059798322011676] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 12/06/2022] [Indexed: 12/24/2022] Open
Abstract
As more protein structure models have been determined from cryogenic electron microscopy (cryo-EM) density maps, establishing how to evaluate the model accuracy and how to correct models in cases where they contain errors is becoming crucial to ensure the quality of the structural models deposited in the public database, the PDB. Here, a new protocol is presented for evaluating a protein model built from a cryo-EM map and applying local structure refinement in the case where the model has potential errors. Firstly, model evaluation is performed using a deep-learning-based model-local map assessment score, DAQ, that has recently been developed. The subsequent local refinement is performed by a modified AlphaFold2 procedure, in which a trimmed template model and a trimmed multiple sequence alignment are provided as input to control which structure regions to refine while leaving other more confident regions of the model intact. A benchmark study showed that this protocol, DAQ-refine, consistently improves low-quality regions of the initial models. Among 18 refined models generated for an initial structure, DAQ shows a high correlation with model quality and can identify the best accurate model for most of the tested cases. The improvements obtained by DAQ-refine were on average larger than other existing methods.
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Affiliation(s)
- Genki Terashi
- Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA
| | - Xiao Wang
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Daisuke Kihara
- Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
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13
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Hadjidemetriou K, Kaur S, Cassidy CK, Zhang P. Mechanisms of E. coli chemotaxis signaling pathways visualized using cryoET and computational approaches. Biochem Soc Trans 2022; 50:1595-1605. [PMID: 36421737 PMCID: PMC9788364 DOI: 10.1042/bst20220191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 11/08/2022] [Accepted: 11/11/2022] [Indexed: 11/25/2022]
Abstract
Chemotaxis signaling pathways enable bacteria to sense and respond to their chemical environment and, in some species, are critical for lifestyle processes such as biofilm formation and pathogenesis. The signal transduction underlying chemotaxis behavior is mediated by large, highly ordered protein complexes known as chemosensory arrays. For nearly two decades, cryo-electron tomography (cryoET) has been used to image chemosensory arrays, providing an increasingly detailed understanding of their structure and function. In this mini-review, we provide an overview of the use of cryoET to study chemosensory arrays, including imaging strategies, key results, and outstanding questions. We further discuss the application of molecular modeling and simulation techniques to complement structure determination efforts and provide insight into signaling mechanisms. We close the review with a brief outlook, highlighting promising future directions for the field.
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Affiliation(s)
| | - Satinder Kaur
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, U.K
| | - C. Keith Cassidy
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, U.K
| | - Peijun Zhang
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, U.K
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, U.K
- Chinese Academy of Medical Sciences Oxford Institute, University of Oxford, Oxford OX3 7BN, U.K
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14
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Varricchio C, Mathez G, Pillonel T, Bertelli C, Kaiser L, Tapparel C, Brancale A, Cagno V. Geneticin shows selective antiviral activity against SARS-CoV-2 by interfering with programmed -1 ribosomal frameshifting. Antiviral Res 2022; 208:105452. [PMID: 36341734 PMCID: PMC9617636 DOI: 10.1016/j.antiviral.2022.105452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 10/18/2022] [Accepted: 10/21/2022] [Indexed: 11/21/2022]
Abstract
SARS-CoV-2 is currently causing an unprecedented pandemic. While vaccines are massively deployed, we still lack effective large-scale antiviral therapies. In the quest for antivirals targeting conserved structures, we focused on molecules able to bind viral RNA secondary structures. Aminoglycosides are a class of antibiotics known to interact with the ribosomal RNA of both prokaryotes and eukaryotes and have previously been shown to exert antiviral activities by interacting with viral RNA. Here we show that the aminoglycoside geneticin is endowed with antiviral activity against all tested variants of SARS-CoV-2, in different cell lines and in a respiratory tissue model at non-toxic concentrations. The mechanism of action is an early inhibition of RNA replication and protein expression related to a decrease in the efficiency of the -1 programmed ribosomal frameshift (PRF) signal of SARS-CoV-2. Using in silico modeling, we have identified a potential binding site of geneticin in the pseudoknot of frameshift RNA motif. Moreover, we have selected, through virtual screening, additional RNA binding compounds, interacting with the same site with increased potency.
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Affiliation(s)
- Carmine Varricchio
- Cardiff School of Pharmacy and Pharmaceutical Sciences, Cardiff, King Edward VII Avenue, Cardiff, UK
| | - Gregory Mathez
- Institute of Microbiology, Lausanne University Hospital, University of Lausanne, Switzerland
| | - Trestan Pillonel
- Institute of Microbiology, Lausanne University Hospital, University of Lausanne, Switzerland
| | - Claire Bertelli
- Institute of Microbiology, Lausanne University Hospital, University of Lausanne, Switzerland
| | - Laurent Kaiser
- Laboratory of Virology, Division of Infectious Diseases and Division of Laboratory Medicine, University Hospitals of Geneva, University of Geneva, Geneva, Switzerland; Center for Emerging Viruses, Geneva University Hospitals, 1205, Geneva, Switzerland
| | - Caroline Tapparel
- Department of Microbiology and Molecular Medicine, University of Geneva, 1206, Geneva, Switzerland
| | - Andrea Brancale
- Cardiff School of Pharmacy and Pharmaceutical Sciences, Cardiff, King Edward VII Avenue, Cardiff, UK
| | - Valeria Cagno
- Institute of Microbiology, Lausanne University Hospital, University of Lausanne, Switzerland.
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15
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Ouyang R, Costa AR, Cassidy CK, Otwinowska A, Williams VCJ, Latka A, Stansfeld PJ, Drulis-Kawa Z, Briers Y, Pelt DM, Brouns SJJ, Briegel A. High-resolution reconstruction of a Jumbo-bacteriophage infecting capsulated bacteria using hyperbranched tail fibers. Nat Commun 2022; 13:7241. [PMID: 36433970 PMCID: PMC9700779 DOI: 10.1038/s41467-022-34972-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 11/14/2022] [Indexed: 11/26/2022] Open
Abstract
The Klebsiella jumbo myophage ϕKp24 displays an unusually complex arrangement of tail fibers interacting with a host cell. In this study, we combine cryo-electron microscopy methods, protein structure prediction methods, molecular simulations, microbiological and machine learning approaches to explore the capsid, tail, and tail fibers of ϕKp24. We determine the structure of the capsid and tail at 4.1 Å and 3.0 Å resolution. We observe the tail fibers are branched and rearranged dramatically upon cell surface attachment. This complex configuration involves fourteen putative tail fibers with depolymerase activity that provide ϕKp24 with the ability to infect a broad panel of capsular polysaccharide (CPS) types of Klebsiella pneumoniae. Our study provides structural and functional insight into how ϕKp24 adapts to the variable surfaces of capsulated bacterial pathogens, which is useful for the development of phage therapy approaches against pan-drug resistant K. pneumoniae strains.
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Affiliation(s)
- Ruochen Ouyang
- grid.43169.390000 0001 0599 1243MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter, School of Physics, Xi’an Jiaotong University, Xianning West Road 28, Xi’an, 710049 China ,grid.5132.50000 0001 2312 1970Department of Microbial Sciences, Institute of Biology, Leiden University, Sylviusweg 72, 2333 BE Leiden, The Netherlands
| | - Ana Rita Costa
- grid.5292.c0000 0001 2097 4740Department of Bionanoscience, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, The Netherlands ,grid.5292.c0000 0001 2097 4740Kavli Institute of Nanoscience, Delft, The Netherlands
| | - C. Keith Cassidy
- grid.4991.50000 0004 1936 8948Department of Biochemistry, University of Oxford, Oxford, UK
| | - Aleksandra Otwinowska
- grid.8505.80000 0001 1010 5103Department of Pathogen Biology and Immunology, University of Wroclaw, Przybyszewskiego 63-77, 51-148 Wroclaw, Poland
| | - Vera C. J. Williams
- grid.5132.50000 0001 2312 1970Department of Microbial Sciences, Institute of Biology, Leiden University, Sylviusweg 72, 2333 BE Leiden, The Netherlands
| | - Agnieszka Latka
- grid.8505.80000 0001 1010 5103Department of Pathogen Biology and Immunology, University of Wroclaw, Przybyszewskiego 63-77, 51-148 Wroclaw, Poland ,grid.5342.00000 0001 2069 7798Department of Biotechnology, Ghent University, Valentin Vaerwyckweg 1, 9000 Ghent, Belgium
| | - Phill J. Stansfeld
- grid.7372.10000 0000 8809 1613School of Life Sciences & Department of Chemistry, University of Warwick, Coventry, CV4 7AL UK
| | - Zuzanna Drulis-Kawa
- grid.8505.80000 0001 1010 5103Department of Pathogen Biology and Immunology, University of Wroclaw, Przybyszewskiego 63-77, 51-148 Wroclaw, Poland
| | - Yves Briers
- grid.5342.00000 0001 2069 7798Department of Biotechnology, Ghent University, Valentin Vaerwyckweg 1, 9000 Ghent, Belgium
| | - Daniël M. Pelt
- grid.5132.50000 0001 2312 1970Leiden Institute of Advanced Computer Science, Leiden University, Niels Bohrweg 1, 2333CA Leiden, The Netherlands
| | - Stan J. J. Brouns
- grid.5292.c0000 0001 2097 4740Department of Bionanoscience, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, The Netherlands ,grid.5292.c0000 0001 2097 4740Kavli Institute of Nanoscience, Delft, The Netherlands
| | - Ariane Briegel
- grid.5132.50000 0001 2312 1970Department of Microbial Sciences, Institute of Biology, Leiden University, Sylviusweg 72, 2333 BE Leiden, The Netherlands
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16
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Abstract
To fulfill the cytoskeleton’s diverse functions in cell mechanics and motility, actin networks with specialized architectures are built by cross-linking proteins. How these cross-linkers specify cytoskeletal network geometry is poorly understood at the level of protein structure. Here, we introduce a machine-learning–enabled pipeline for visualizing cross-linkers bridging cytoskeletal filaments with cryogenic electron microscopy (cryo-EM). We apply our method to T-plastin, a member of the evolutionarily conserved plastin/fimbrin family, revealing a sequence of conformational changes that enables T-plastin to bridge pairs of actin filaments in both parallel and antiparallel orientations. This provides a structural framework for understanding how plastins can generate actin networks featuring mixed filament polarity. To orchestrate cell mechanics, trafficking, and motility, cytoskeletal filaments must assemble into higher-order networks whose local subcellular architecture and composition specify their functions. Cross-linking proteins bridge filaments at the nanoscale to control a network’s μm-scale geometry, thereby conferring its mechanical properties and functional dynamics. While these interfilament linkages are key determinants of cytoskeletal function, their structural mechanisms remain poorly understood. Plastins/fimbrins are an evolutionarily ancient family of tandem calponin-homology domain (CHD) proteins required to construct multiple classes of actin networks, which feature diverse geometries specialized to power cytokinesis, microvilli and stereocilia biogenesis, and persistent cell migration. Here, we focus on the structural basis of actin network assembly by human T-plastin, a ubiquitously expressed isoform necessary for the maintenance of stable cellular protrusions generated by actin polymerization forces. By implementing a machine-learning–enabled cryo-electron microscopy pipeline for visualizing cross-linkers bridging multiple filaments, we uncover a sequential bundling mechanism enabling T-plastin to bridge pairs of actin filaments in both parallel and antiparallel orientations. T-plastin populates distinct structural landscapes in these two bridging orientations that are selectively compatible with actin networks featuring divergent architectures and functions. Our structural, biochemical, and cell biological data highlight inter-CHD linkers as key structural elements underlying flexible but stable cross-linking that are likely to be disrupted by T-plastin mutations that cause hereditary bone diseases.
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17
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Asi H, Dasgupta B, Nagai T, Miyashita O, Tama F. A hybrid approach to study large conformational transitions of biomolecules from single particle XFEL diffraction data. Front Mol Biosci 2022; 9:913860. [PMID: 36660427 PMCID: PMC9846856 DOI: 10.3389/fmolb.2022.913860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 07/04/2022] [Indexed: 01/06/2023] Open
Abstract
X-ray free-electron laser (XFEL) is the latest generation of the X-ray source that could become an invaluable technique in structural biology. XFEL has ultrashort pulse duration, extreme peak brilliance, and high spatial coherence, which could enable the observation of the biological molecules in near nature state at room temperature without crystallization. However, for biological systems, due to their low diffraction power and complexity of sample delivery, experiments and data analysis are not straightforward, making it extremely challenging to reconstruct three-dimensional (3D) structures from single particle XFEL data. Given the current limitations to the amount and resolution of the data from such XFEL experiments, we propose a new hybrid approach for characterizing biomolecular conformational transitions by using a single 2D low-resolution XFEL diffraction pattern in combination with another known conformation. In our method, we represent the molecular structure with a coarse-grained model, the Gaussian mixture model, to describe large conformational transitions from low-resolution XFEL data. We obtain plausible 3D structural models that are consistent with the XFEL diffraction pattern by deforming an initial structural model to maximize the similarity between the target pattern and the simulated diffraction patterns from the candidate models. We tested the proposed algorithm on two biomolecules of different sizes with different complexities of conformational transitions, adenylate kinase, and elongation factor 2, using synthetic XFEL data. The results show that, with the proposed algorithm, we can successfully describe the conformational transitions by flexibly fitting the coarse-grained model of one conformation to become consistent with an XFEL diffraction pattern simulated from another conformation. In addition, we showed that the incident beam orientation has some effect on the accuracy of the 3D structure modeling and discussed the reasons for the inaccuracies for certain orientations. The proposed method could serve as an alternative approach for retrieving information on 3D conformational transitions from the XFEL diffraction patterns to interpret experimental data. Since the molecules are represented by Gaussian kernels and no atomic structure is needed in principle, such a method could also be used as a tool to seek initial models for 3D reconstruction algorithms.
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Affiliation(s)
- Han Asi
- Department of Physics, Nagoya University, Nagoya, Japan
| | - Bhaskar Dasgupta
- Division of Biological Data Science, Research Center for Advanced Science and Technology, The University of Tokyo, Meguro City, Japan
| | - Tetsuro Nagai
- Department of Advanced Materials Science, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
| | - Osamu Miyashita
- RIKEN Center for Computational Science, Kobe, Japan,*Correspondence: Osamu Miyashita, ; Florence Tama,
| | - Florence Tama
- Department of Physics, Nagoya University, Nagoya, Japan,RIKEN Center for Computational Science, Kobe, Japan,Institute of Transformative Bio-Molecules, Nagoya University, Nagoya, Japan,*Correspondence: Osamu Miyashita, ; Florence Tama,
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18
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Varricchio C, Mathez G, Pillonel T, Bertelli C, Kaiser L, Tapparel C, Brancale A, Cagno V. Geneticin shows selective antiviral activity against SARS-CoV-2 by interfering with programmed -1 ribosomal frameshifting. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2022:2022.03.08.483429. [PMID: 35291297 PMCID: PMC8923105 DOI: 10.1101/2022.03.08.483429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
SARS-CoV-2 is currently causing an unprecedented pandemic. While vaccines are massively deployed, we still lack effective large-scale antiviral therapies. In the quest for antivirals targeting conserved structures, we focused on molecules able to bind viral RNA secondary structures. Aminoglycosides are a class of antibiotics known to interact with the ribosomal RNA of both prokaryotes and eukaryotes and have previously been shown to exert antiviral activities by interacting with viral RNA. Here we show that the aminoglycoside geneticin is endowed with antiviral activity against all tested variants of SARS-CoV-2, in different cell lines and in a respiratory tissue model at non-toxic concentrations. The mechanism of action is an early inhibition of RNA replication and protein expression related to a decrease in the efficiency of the -1 programmed ribosomal frameshift (PRF) signal of SARS-CoV-2. Using in silico modelling, we have identified a potential binding site of geneticin in the pseudoknot of frameshift RNA motif. Moreover, we have selected, through virtual screening, additional RNA binding compounds, interacting with the same site with increased potency.
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Affiliation(s)
- Carmine Varricchio
- Cardiff School of Pharmacy and Pharmaceutical Sciences, Cardiff, King Edward VII Avenue, Cardiff, UK
| | - Gregory Mathez
- Institute of Microbiology, Lausanne University Hospital, University of Lausanne, Switzerland
| | - Trestan Pillonel
- Institute of Microbiology, Lausanne University Hospital, University of Lausanne, Switzerland
| | - Claire Bertelli
- Institute of Microbiology, Lausanne University Hospital, University of Lausanne, Switzerland
| | - Laurent Kaiser
- Laboratory of Virology, Division of Infectious Diseases and Division of Laboratory Medicine, University Hospitals of Geneva, University of Geneva, Geneva, Switzerland
- Center for Emerging Viruses, Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Caroline Tapparel
- Department of Microbiology and Molecular Medicine, University of Geneva, 1206 Geneva, Switzerland
| | - Andrea Brancale
- Cardiff School of Pharmacy and Pharmaceutical Sciences, Cardiff, King Edward VII Avenue, Cardiff, UK
| | - Valeria Cagno
- Institute of Microbiology, Lausanne University Hospital, University of Lausanne, Switzerland
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19
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Alnabati E, Terashi G, Kihara D. Protein Structural Modeling for Electron Microscopy Maps Using VESPER and MAINMAST. Curr Protoc 2022; 2:e494. [PMID: 35849043 PMCID: PMC9299282 DOI: 10.1002/cpz1.494] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
An increasing number of protein structures are determined by cryo-electron microscopy (cryo-EM) and stored in the Electron Microscopy Data Bank (EMDB). To interpret determined cryo-EM maps, several methods have been developed that model the tertiary structure of biomolecules, particularly proteins. Here we show how to use two such methods, VESPER and MAINMAST, which were developed in our group. VESPER is a method mainly for two purposes: fitting protein structure models into an EM map and aligning two EM maps locally or globally to capture their similarity. VESPER represents each EM map as a set of vectors pointing toward denser points. By considering matching the directions of vectors, in general, VESPER aligns maps better than conventional methods that only consider local densities of maps. MAINMAST is a de novo protein modeling tool designed for EM maps with resolution of 3-5 Å or better. MAINMAST builds a protein main chain directly from a density map by tracing dense points in an EM map and connecting them using a tree-graph structure. This article describes how to use these two tools using three illustrative modeling examples. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Protein structure model fitting using VESPER Alternate Protocol: Atomic model fitting using VESPER web server Basic Protocol 2: Protein de novo modeling using MAINMAST.
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Affiliation(s)
- Eman Alnabati
- Department of Computer SciencePurdue UniversityWest LafayetteIndiana
| | - Genki Terashi
- Department of Biological SciencesPurdue UniversityWest LafayetteIndiana
| | - Daisuke Kihara
- Department of Computer SciencePurdue UniversityWest LafayetteIndiana
- Department of Biological SciencesPurdue UniversityWest LafayetteIndiana
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20
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Zhu Z, Deng Z, Wang Q, Wang Y, Zhang D, Xu R, Guo L, Wen H. Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design. Front Pharmacol 2022; 13:939555. [PMID: 35837274 PMCID: PMC9275593 DOI: 10.3389/fphar.2022.939555] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 06/07/2022] [Indexed: 11/13/2022] Open
Abstract
Ion channels are expressed in almost all living cells, controlling the in-and-out communications, making them ideal drug targets, especially for central nervous system diseases. However, owing to their dynamic nature and the presence of a membrane environment, ion channels remain difficult targets for the past decades. Recent advancement in cryo-electron microscopy and computational methods has shed light on this issue. An explosion in high-resolution ion channel structures paved way for structure-based rational drug design and the state-of-the-art simulation and machine learning techniques dramatically improved the efficiency and effectiveness of computer-aided drug design. Here we present an overview of how simulation and machine learning-based methods fundamentally changed the ion channel-related drug design at different levels, as well as the emerging trends in the field.
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Affiliation(s)
- Zhengdan Zhu
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Beijing Institute of Big Data Research, Beijing, China
| | - Zhenfeng Deng
- DP Technology, Beijing, China
- School of Pharmaceutical Sciences, Peking University, Beijing, China
| | | | | | - Duo Zhang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- DP Technology, Beijing, China
| | - Ruihan Xu
- DP Technology, Beijing, China
- National Engineering Research Center of Visual Technology, Peking University, Beijing, China
| | | | - Han Wen
- DP Technology, Beijing, China
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21
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Liu D, Thélot FA, Piccirilli JA, Liao M, Yin P. Sub-3-Å cryo-EM structure of RNA enabled by engineered homomeric self-assembly. Nat Methods 2022; 19:576-585. [PMID: 35501384 DOI: 10.1038/s41592-022-01455-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 03/09/2022] [Indexed: 12/29/2022]
Abstract
High-resolution structural studies are essential for understanding the folding and function of diverse RNAs. Herein, we present a nanoarchitectural engineering strategy for efficient structural determination of RNA-only structures using single-particle cryogenic electron microscopy (cryo-EM). This strategy-ROCK (RNA oligomerization-enabled cryo-EM via installing kissing loops)-involves installing kissing-loop sequences onto the functionally nonessential stems of RNAs for homomeric self-assembly into closed rings with multiplied molecular weights and mitigated structural flexibility. ROCK enables cryo-EM reconstruction of the Tetrahymena group I intron at 2.98-Å resolution overall (2.85 Å for the core), allowing de novo model building of the complete RNA, including the previously unknown peripheral domains. ROCK is further applied to two smaller RNAs-the Azoarcus group I intron and the FMN riboswitch, revealing the conformational change of the former and the bound ligand in the latter. ROCK holds promise to greatly facilitate the use of cryo-EM in RNA structural studies.
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Affiliation(s)
- Di Liu
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.,Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - François A Thélot
- Department of Cell Biology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | - Joseph A Piccirilli
- Department of Chemistry, the University of Chicago, Chicago, IL, USA.,Department of Biochemistry and Molecular Biology, the University of Chicago, Chicago, IL, USA
| | - Maofu Liao
- Department of Cell Biology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA.
| | - Peng Yin
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA. .,Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
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22
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DeVore K, Chiu PL. Probing Structural Perturbation of Biomolecules by Extracting Cryo-EM Data Heterogeneity. Biomolecules 2022; 12:628. [PMID: 35625556 PMCID: PMC9138638 DOI: 10.3390/biom12050628] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 04/15/2022] [Accepted: 04/18/2022] [Indexed: 02/04/2023] Open
Abstract
Single-particle cryogenic electron microscopy (cryo-EM) has become an indispensable tool to probe high-resolution structural detail of biomolecules. It enables direct visualization of the biomolecules and opens a possibility for averaging molecular images to reconstruct a three-dimensional Coulomb potential density map. Newly developed algorithms for data analysis allow for the extraction of structural heterogeneity from a massive and low signal-to-noise-ratio (SNR) cryo-EM dataset, expanding our understanding of multiple conformational states, or further implications in dynamics, of the target biomolecule. This review provides an overview that briefly describes the workflow of single-particle cryo-EM, including imaging and data processing, and new methods developed for analyzing the data heterogeneity to understand the structural variability of biomolecules.
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Affiliation(s)
| | - Po-Lin Chiu
- School of Molecular Sciences, Biodesign Center for Applied Structural Discovery, Arizona State University, Tempe, AZ 85287, USA;
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23
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Exploring cryo-electron microscopy with molecular dynamics. Biochem Soc Trans 2022; 50:569-581. [PMID: 35212361 DOI: 10.1042/bst20210485] [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: 12/10/2021] [Revised: 01/31/2022] [Accepted: 02/02/2022] [Indexed: 11/17/2022]
Abstract
Single particle analysis cryo-electron microscopy (EM) and molecular dynamics (MD) have been complimentary methods since cryo-EM was first applied to the field of structural biology. The relationship started by biasing structural models to fit low-resolution cryo-EM maps of large macromolecular complexes not amenable to crystallization. The connection between cryo-EM and MD evolved as cryo-EM maps improved in resolution, allowing advanced sampling algorithms to simultaneously refine backbone and sidechains. Moving beyond a single static snapshot, modern inferencing approaches integrate cryo-EM and MD to generate structural ensembles from cryo-EM map data or directly from the particle images themselves. We summarize the recent history of MD innovations in the area of cryo-EM modeling. The merits for the myriad of MD based cryo-EM modeling methods are discussed, as well as, the discoveries that were made possible by the integration of molecular modeling with cryo-EM. Lastly, current challenges and potential opportunities are reviewed.
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24
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Zhang B, Liu D, Zhang Y, Shen HB, Zhang GJ. Accurate flexible refinement for atomic-level protein structure using cryo-EM density maps and deep learning. Brief Bioinform 2022; 23:6526721. [DOI: 10.1093/bib/bbac026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 12/26/2021] [Accepted: 01/17/2022] [Indexed: 11/13/2022] Open
Abstract
Abstract
With the rapid progress of deep learning in cryo-electron microscopy and protein structure prediction, improving the accuracy of the protein structure model by using a density map and predicted contact/distance map through deep learning has become an urgent need for robust methods. Thus, designing an effective protein structure optimization strategy based on the density map and predicted contact/distance map is critical to improving the accuracy of structure refinement. In this article, a protein structure optimization method based on the density map and predicted contact/distance map by deep-learning technology was proposed in accordance with the result of matching between the density map and the initial model. Physics- and knowledge-based energy functions, integrated with Cryo-EM density map data and deep-learning data, were used to optimize the protein structure in the simulation. The dynamic confidence score was introduced to the iterative process for choosing whether it is a density map or a contact/distance map to dominate the movement in the simulation to improve the accuracy of refinement. The protocol was tested on a large set of 224 non-homologous membrane proteins and generated 214 structural models with correct folds, where 4.5% of structural models were generated from structural models with incorrect folds. Compared with other state-of-the-art methods, the major advantage of the proposed methods lies in the skills for using density map and contact/distance map in the simulation, as well as the new energy function in the re-assembly simulations. Overall, the results demonstrated that this strategy is a valuable approach and ready to use for atomic-level structure refinement using cryo-EM density map and predicted contact/distance map.
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Affiliation(s)
- Biao Zhang
- College of Information Engineering, Zhejiang University of Technology
| | - Dong Liu
- College of Information Engineering, Zhejiang University of Technology
| | - Yang Zhang
- Department of Computational Medicine and Bioinformatics, University of Michigan
| | - Hong-Bin Shen
- Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China
| | - Gui-Jun Zhang
- College of Information Engineering, Zhejiang University of Technology
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25
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Lanrezac A, Férey N, Baaden M. Wielding the power of interactive molecular simulations. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1594] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- André Lanrezac
- CNRS, Laboratoire de Biochimie Théorique Université de Paris Paris France
| | - Nicolas Férey
- CNRS, Laboratoire interdisciplinaire des sciences du numérique Université Paris‐Saclay Orsay France
| | - Marc Baaden
- CNRS, Laboratoire de Biochimie Théorique Université de Paris Paris France
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26
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Yan C, Dodd T, Yu J, Leung B, Xu J, Oh J, Wang D, Ivanov I. Mechanism of Rad26-assisted rescue of stalled RNA polymerase II in transcription-coupled repair. Nat Commun 2021; 12:7001. [PMID: 34853308 PMCID: PMC8636621 DOI: 10.1038/s41467-021-27295-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 11/10/2021] [Indexed: 12/22/2022] Open
Abstract
Transcription-coupled repair is essential for the removal of DNA lesions from the transcribed genome. The pathway is initiated by CSB protein binding to stalled RNA polymerase II. Mutations impairing CSB function cause severe genetic disease. Yet, the ATP-dependent mechanism by which CSB powers RNA polymerase to bypass certain lesions while triggering excision of others is incompletely understood. Here we build structural models of RNA polymerase II bound to the yeast CSB ortholog Rad26 in nucleotide-free and bound states. This enables simulations and graph-theoretical analyses to define partitioning of this complex into dynamic communities and delineate how its structural elements function together to remodel DNA. We identify an allosteric pathway coupling motions of the Rad26 ATPase modules to changes in RNA polymerase and DNA to unveil a structural mechanism for CSB-assisted progression past less bulky lesions. Our models allow functional interpretation of the effects of Cockayne syndrome disease mutations.
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Affiliation(s)
- Chunli Yan
- grid.256304.60000 0004 1936 7400Department of Chemistry, Georgia State University, Atlanta, GA USA ,grid.256304.60000 0004 1936 7400Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA USA
| | - Thomas Dodd
- grid.256304.60000 0004 1936 7400Department of Chemistry, Georgia State University, Atlanta, GA USA ,grid.256304.60000 0004 1936 7400Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA USA
| | - Jina Yu
- grid.256304.60000 0004 1936 7400Department of Chemistry, Georgia State University, Atlanta, GA USA ,grid.256304.60000 0004 1936 7400Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA USA
| | - Bernice Leung
- grid.266100.30000 0001 2107 4242Division of Pharmaceutical Sciences, Skaggs School of Pharmacy & Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093 USA
| | - Jun Xu
- grid.266100.30000 0001 2107 4242Division of Pharmaceutical Sciences, Skaggs School of Pharmacy & Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093 USA
| | - Juntaek Oh
- grid.266100.30000 0001 2107 4242Division of Pharmaceutical Sciences, Skaggs School of Pharmacy & Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093 USA
| | - Dong Wang
- Division of Pharmaceutical Sciences, Skaggs School of Pharmacy & Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA. .,Department of Cellular & Molecular Medicine, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA. .,Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA, 92093, USA.
| | - Ivaylo Ivanov
- Department of Chemistry, Georgia State University, Atlanta, GA, USA. .,Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA, USA.
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27
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Liu Y, Bisio H, Toner CM, Jeudy S, Philippe N, Zhou K, Bowerman S, White A, Edwards G, Abergel C, Luger K. Virus-encoded histone doublets are essential and form nucleosome-like structures. Cell 2021; 184:4237-4250.e19. [PMID: 34297924 PMCID: PMC8357426 DOI: 10.1016/j.cell.2021.06.032] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 05/25/2021] [Accepted: 06/25/2021] [Indexed: 12/13/2022]
Abstract
The organization of genomic DNA into defined nucleosomes has long been viewed as a hallmark of eukaryotes. This paradigm has been challenged by the identification of “minimalist” histones in archaea and more recently by the discovery of genes that encode fused remote homologs of the four eukaryotic histones in Marseilleviridae, a subfamily of giant viruses that infect amoebae. We demonstrate that viral doublet histones are essential for viral infectivity, localize to cytoplasmic viral factories after virus infection, and ultimately are found in the mature virions. Cryogenic electron microscopy (cryo-EM) structures of viral nucleosome-like particles show strong similarities to eukaryotic nucleosomes despite the limited sequence identify. The unique connectors that link the histone chains contribute to the observed instability of viral nucleosomes, and some histone tails assume structural roles. Our results further expand the range of “organisms” that require nucleosomes and suggest a specialized function of histones in the biology of these unusual viruses. Marseilleviridae encode proteins that resemble fused histones H4-H3 and H2B-H2A These histone doublets assemble into unstable nucleosome-like particles in vitro Histone doublets localize to the viral factory and are highly abundant in the virus They are essential for viral fitness and infectivity, a first for any virus
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Affiliation(s)
- Yang Liu
- Department of Biochemistry, University of Colorado Boulder, Boulder, CO 80309, USA; Howard Hughes Medical Institute, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Hugo Bisio
- Aix-Marseille University, Centre National de la Recherche Scientifique, Information Génomique & Structurale, Unité Mixte de Recherche 7256 (Institut de Microbiologie de la Méditerranée, FR3479, IM2B), 13288 Marseille Cedex 9, France
| | - Chelsea Marie Toner
- Department of Biochemistry, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Sandra Jeudy
- Aix-Marseille University, Centre National de la Recherche Scientifique, Information Génomique & Structurale, Unité Mixte de Recherche 7256 (Institut de Microbiologie de la Méditerranée, FR3479, IM2B), 13288 Marseille Cedex 9, France
| | - Nadege Philippe
- Aix-Marseille University, Centre National de la Recherche Scientifique, Information Génomique & Structurale, Unité Mixte de Recherche 7256 (Institut de Microbiologie de la Méditerranée, FR3479, IM2B), 13288 Marseille Cedex 9, France
| | - Keda Zhou
- Department of Biochemistry, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Samuel Bowerman
- Department of Biochemistry, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Alison White
- Department of Biochemistry, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Garrett Edwards
- Department of Biochemistry, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Chantal Abergel
- Aix-Marseille University, Centre National de la Recherche Scientifique, Information Génomique & Structurale, Unité Mixte de Recherche 7256 (Institut de Microbiologie de la Méditerranée, FR3479, IM2B), 13288 Marseille Cedex 9, France.
| | - Karolin Luger
- Department of Biochemistry, University of Colorado Boulder, Boulder, CO 80309, USA; Howard Hughes Medical Institute, University of Colorado Boulder, Boulder, CO 80309, USA.
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28
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Wang X, Alnabati E, Aderinwale TW, Maddhuri Venkata Subramaniya SR, Terashi G, Kihara D. Detecting protein and DNA/RNA structures in cryo-EM maps of intermediate resolution using deep learning. Nat Commun 2021; 12:2302. [PMID: 33863902 PMCID: PMC8052361 DOI: 10.1038/s41467-021-22577-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 03/19/2021] [Indexed: 12/21/2022] Open
Abstract
An increasing number of density maps of macromolecular structures, including proteins and DNA/RNA complexes, have been determined by cryo-electron microscopy (cryo-EM). Although lately maps at a near-atomic resolution are routinely reported, there are still substantial fractions of maps determined at intermediate or low resolutions, where extracting structure information is not trivial. Here, we report a new computational method, Emap2sec+, which identifies DNA or RNA as well as the secondary structures of proteins in cryo-EM maps of 5 to 10 Å resolution. Emap2sec+ employs the deep Residual convolutional neural network. Emap2sec+ assigns structural labels with associated probabilities at each voxel in a cryo-EM map, which will help structure modeling in an EM map. Emap2sec+ showed stable and high assignment accuracy for nucleotides in low resolution maps and improved performance for protein secondary structure assignments than its earlier version when tested on simulated and experimental maps.
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Affiliation(s)
- Xiao Wang
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | - Eman Alnabati
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | - Tunde W Aderinwale
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | | | - Genki Terashi
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Daisuke Kihara
- Department of Computer Science, Purdue University, West Lafayette, IN, USA.
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA.
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29
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Vant JW, Sarkar D, Gupta C, Shekhar MS, Mittal S, Singharoy A. Molecular Dynamics Flexible Fitting: All You Want to Know About Resolution Exchange. Methods Mol Biol 2021; 2165:301-315. [PMID: 32621233 DOI: 10.1007/978-1-0716-0708-4_18] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
In recent years, owing to the advances in instrumentation, cryo-EM has emerged as the go-to tool for obtaining high-resolution structures of biomolecular systems. However, building three-dimensional atomic structures of biomolecules from these high-resolution maps remains a concern for the traditional map-guided structure-determination schemes. Recently, we developed a computational tool, Resolution Exchange Molecular Dynamics Flexible Fitting (ReMDFF) to address this problem by re-refining a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution (Wang et al., J Struct Biol 204(2):319-328, 2018). In this chapter, we present a step-by-step outline for preparing, executing, and analyzing ReMDFF refinements of simple proteins and multimeric complexes. The structure determination of carbon monoxide dehydrogenase and Mg2+-channel CorA are employed as case studies. All scripts are provided via GitHub (Vant, Resolution exchange molecular dynamics flexible fitting (ReMDFF) all you want to know about flexible fitting, 2019, https://github.com/jvant/ReMDFF_Singharoy_Group.git ).
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Affiliation(s)
- John W Vant
- The School of Molecular Sciences, Arizona State University, Tempe, AZ, USA
| | - Daipayan Sarkar
- The School of Molecular Sciences, Arizona State University, Tempe, AZ, USA
| | - Chitrak Gupta
- The School of Molecular Sciences, Arizona State University, Tempe, AZ, USA
| | - Mrinal S Shekhar
- Oncology, IMED Biotech Unit, AstraZeneca R&D Boston, Waltham, MA, USA
| | - Sumit Mittal
- Department of Chemistry, VIT Bhopal University, Bhopal, India
| | - Abhishek Singharoy
- The School of Molecular Sciences, Arizona State University, Tempe, AZ, USA.
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30
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Fuchigami S, Niina T, Takada S. Case Report: Bayesian Statistical Inference of Experimental Parameters via Biomolecular Simulations: Atomic Force Microscopy. Front Mol Biosci 2021; 8:636940. [PMID: 33778008 PMCID: PMC7987833 DOI: 10.3389/fmolb.2021.636940] [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: 12/02/2020] [Accepted: 01/25/2021] [Indexed: 11/13/2022] Open
Abstract
The atomic force microscopy (AFM) is a powerful tool for imaging structures of molecules bound on surfaces. To gain high-resolution structural information, one often superimposes structure models on the measured images. Motivated by high flexibility of biomolecules, we previously developed a flexible-fitting molecular dynamics (MD) method that allows protein structural changes upon superimposing. Since the AFM image largely depends on the AFM probe tip geometry, the fitting process requires accurate estimation of the parameters related to the tip geometry. Here, we performed a Bayesian statistical inference to estimate a tip radius of the AFM probe from a given AFM image via flexible-fitting molecular dynamics (MD) simulations. We first sampled conformations of the nucleosome that fit well the reference AFM image by the flexible-fitting with various tip radii. We then estimated an optimal tip parameter by maximizing the conditional probability density of the AFM image produced from the fitted structure.
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Affiliation(s)
- Sotaro Fuchigami
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
| | | | - Shoji Takada
- Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
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31
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Abstract
The sorting nexin (SNX) family of proteins deform the membrane to generate transport carriers in endosomal pathways. Here, we elucidate how a prototypic member, SNX1, acts in this process. Performing cryoelectron microscopy, we find that SNX1 assembles into a protein lattice that consists of helical rows of SNX1 dimers wrapped around tubular membranes in a crosslinked fashion. We also visualize the details of this structure, which provides a molecular understanding of how various parts of SNX1 contribute to its ability to deform the membrane. Moreover, we have compared the SNX1 structure with a previously elucidated structure of an endosomal coat complex formed by retromer coupled to a SNX, which reveals how the molecular organization of the SNX in this coat complex is affected by retromer. The comparison also suggests insight into intermediary stages of assembly that results in the formation of the retromer-SNX coat complex on the membrane.
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32
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Refinement of a cryo-EM structure of hERG: Bridging structure and function. Biophys J 2021; 120:738-748. [PMID: 33476597 DOI: 10.1016/j.bpj.2021.01.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 12/22/2020] [Accepted: 01/11/2021] [Indexed: 01/16/2023] Open
Abstract
The human-ether-a-go-go-related gene (hERG) encodes the voltage-gated potassium channel (KCNH2 or Kv11.1, commonly known as hERG). This channel plays a pivotal role in the stability of phase 3 repolarization of the cardiac action potential. Although a high-resolution cryo-EM structure is available for its depolarized (open) state, the structure surprisingly did not feature many functionally important interactions established by previous biochemical and electrophysiology experiments. Using molecular dynamics flexible fitting (MDFF), we refined the structure and recovered the missing functionally relevant salt bridges in hERG in its depolarized state. We also performed electrophysiology experiments to confirm the functional relevance of a novel salt bridge predicted by our refinement protocol. Our work shows how refinement of a high-resolution cryo-EM structure helps to bridge the existing gap between the structure and function in the voltage-sensing domain (VSD) of hERG.
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33
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Seffernick JT, Lindert S. Hybrid methods for combined experimental and computational determination of protein structure. J Chem Phys 2020; 153:240901. [PMID: 33380110 PMCID: PMC7773420 DOI: 10.1063/5.0026025] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 11/10/2020] [Indexed: 02/04/2023] Open
Abstract
Knowledge of protein structure is paramount to the understanding of biological function, developing new therapeutics, and making detailed mechanistic hypotheses. Therefore, methods to accurately elucidate three-dimensional structures of proteins are in high demand. While there are a few experimental techniques that can routinely provide high-resolution structures, such as x-ray crystallography, nuclear magnetic resonance (NMR), and cryo-EM, which have been developed to determine the structures of proteins, these techniques each have shortcomings and thus cannot be used in all cases. However, additionally, a large number of experimental techniques that provide some structural information, but not enough to assign atomic positions with high certainty have been developed. These methods offer sparse experimental data, which can also be noisy and inaccurate in some instances. In cases where it is not possible to determine the structure of a protein experimentally, computational structure prediction methods can be used as an alternative. Although computational methods can be performed without any experimental data in a large number of studies, inclusion of sparse experimental data into these prediction methods has yielded significant improvement. In this Perspective, we cover many of the successes of integrative modeling, computational modeling with experimental data, specifically for protein folding, protein-protein docking, and molecular dynamics simulations. We describe methods that incorporate sparse data from cryo-EM, NMR, mass spectrometry, electron paramagnetic resonance, small-angle x-ray scattering, Förster resonance energy transfer, and genetic sequence covariation. Finally, we highlight some of the major challenges in the field as well as possible future directions.
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Affiliation(s)
- Justin T. Seffernick
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA
| | - Steffen Lindert
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA
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34
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Vant JW, Sarkar D, Streitwieser E, Fiorin G, Skeel R, Vermaas JV, Singharoy A. Data-guided Multi-Map variables for ensemble refinement of molecular movies. J Chem Phys 2020; 153:214102. [PMID: 33291927 PMCID: PMC7714525 DOI: 10.1063/5.0022433] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 11/09/2020] [Indexed: 12/17/2022] Open
Abstract
Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. Here, the three-dimensional electron density of a protein, as it would be determined by cryo-EM or x-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work employs the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along the chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along the reaction coordinates derived from electron densities can capture conformational transitions between known intermediates. The simulated pathways appear reversible with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution density information coupled to comparatively large structural transitions. Practical considerations for probing the transitions between multiple intermediate density states are also discussed.
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Affiliation(s)
- John W. Vant
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85281, USA
| | | | - Ellen Streitwieser
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85281, USA
| | - Giacomo Fiorin
- Theoretical Molecular Biophysics Laboratory, National Heart, Lung and Blood Institute, National Institutes of Health, 10 Center Drive, Bethesda, Maryland 20814, USA
| | - Robert Skeel
- School of Mathematical and Statistical Sciences, Arizona State University, Tempe, Arizona 85281, USA
| | - Josh V. Vermaas
- Computing and Computational Sciences Directorate, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, USA
| | - Abhishek Singharoy
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85281, USA
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35
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Chang JY, Cui Z, Yang K, Huang J, Minary P, Zhang J. Hierarchical natural move Monte Carlo refines flexible RNA structures into cryo-EM densities. RNA (NEW YORK, N.Y.) 2020; 26:1755-1766. [PMID: 32826323 PMCID: PMC7668250 DOI: 10.1261/rna.071100.119] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 08/15/2020] [Indexed: 06/11/2023]
Abstract
Ribonucleic acids (RNAs) play essential roles in living cells. Many of them fold into defined three-dimensional (3D) structures to perform functions. Recent advances in single-particle cryo-electron microscopy (cryo-EM) have enabled structure determinations of RNA to atomic resolutions. However, most RNA molecules are structurally flexible, limiting the resolution of their structures solved by cryo-EM. In modeling these molecules, several computational methods are limited by the requirement of massive computational resources and/or the low efficiency in exploring large-scale structural variations. Here we use hierarchical natural move Monte Carlo (HNMMC), which takes advantage of collective motions for groups of nucleic acid residues, to refine RNA structures into their cryo-EM maps, preserving atomic details in the models. After validating the method on a simulated density map of tRNA, we applied it to objectively obtain the model of the folding intermediate for the specificity domain of ribonuclease P from Bacillus subtilis and refine a flexible ribosomal RNA (rRNA) expansion segment from the Mycobacterium tuberculosis (Mtb) ribosome in different conformational states. Finally, we used HNMMC to model atomic details and flexibility for two distinct conformations of the complete genomic RNA (gRNA) inside MS2, a single-stranded RNA virus, revealing multiple pathways for its capsid assembly.
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Affiliation(s)
- Jeng-Yih Chang
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas 77843, USA
- Center for Phage Technology, College Station, Texas 77843, USA
| | - Zhicheng Cui
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas 77843, USA
- Center for Phage Technology, College Station, Texas 77843, USA
| | - Kailu Yang
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas 77843, USA
- Center for Phage Technology, College Station, Texas 77843, USA
| | - Jianhua Huang
- Department of Statistics, Texas A&M University, College Station, Texas 77843, USA
| | - Peter Minary
- Department of Computer Science, University of Oxford, Oxford OX1 3QD, United Kingdom
| | - Junjie Zhang
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas 77843, USA
- Center for Phage Technology, College Station, Texas 77843, USA
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36
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Phillips JC, Hardy DJ, Maia JDC, Stone JE, Ribeiro JV, Bernardi RC, Buch R, Fiorin G, Hénin J, Jiang W, McGreevy R, Melo MCR, Radak BK, Skeel RD, Singharoy A, Wang Y, Roux B, Aksimentiev A, Luthey-Schulten Z, Kalé LV, Schulten K, Chipot C, Tajkhorshid E. Scalable molecular dynamics on CPU and GPU architectures with NAMD. J Chem Phys 2020; 153:044130. [PMID: 32752662 PMCID: PMC7395834 DOI: 10.1063/5.0014475] [Citation(s) in RCA: 1353] [Impact Index Per Article: 338.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 07/01/2020] [Indexed: 02/06/2023] Open
Abstract
NAMDis a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.
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Affiliation(s)
| | - David J. Hardy
- NIH Center for Macromolecular Modeling and
Bioinformatics, Theoretical and Computational Biophysics Group, Beckman Institute for
Advanced Science and Technology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Julio D. C. Maia
- NIH Center for Macromolecular Modeling and
Bioinformatics, Theoretical and Computational Biophysics Group, Beckman Institute for
Advanced Science and Technology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61801, USA
| | - John E. Stone
- NIH Center for Macromolecular Modeling and
Bioinformatics, Theoretical and Computational Biophysics Group, Beckman Institute for
Advanced Science and Technology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61801, USA
| | - João V. Ribeiro
- NIH Center for Macromolecular Modeling and
Bioinformatics, Theoretical and Computational Biophysics Group, Beckman Institute for
Advanced Science and Technology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Rafael C. Bernardi
- NIH Center for Macromolecular Modeling and
Bioinformatics, Theoretical and Computational Biophysics Group, Beckman Institute for
Advanced Science and Technology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61801, USA
| | | | - Giacomo Fiorin
- National Heart, Lung and Blood Institute, National
Institutes of Health, Bethesda, Maryland 20814,
USA
| | - Jérôme Hénin
- Laboratoire de Biochimie Théorique UPR 9080, CNRS
and Université de Paris, Paris, France
| | | | - Ryan McGreevy
- NIH Center for Macromolecular Modeling and
Bioinformatics, Theoretical and Computational Biophysics Group, Beckman Institute for
Advanced Science and Technology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61801, USA
| | | | - Brian K. Radak
- NIH Center for Macromolecular Modeling and
Bioinformatics, Theoretical and Computational Biophysics Group, Beckman Institute for
Advanced Science and Technology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Robert D. Skeel
- School of Mathematical and Statistical Sciences,
Arizona State University, Tempe, Arizona 85281,
USA
| | - Abhishek Singharoy
- School of Molecular Sciences, Arizona State
University, Tempe, Arizona 85281, USA
| | - Yi Wang
- Department of Physics, The Chinese University of
Hong Kong, Shatin, Hong Kong, China
| | - Benoît Roux
- Department of Biochemistry, University of
Chicago, Chicago, Illinois 60637, USA
| | | | | | | | | | - Christophe Chipot
- Authors to whom correspondence should be addressed:
and . URL: http://www.ks.uiuc.edu
| | - Emad Tajkhorshid
- Authors to whom correspondence should be addressed:
and . URL: http://www.ks.uiuc.edu
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37
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Gutmann T, Schäfer IB, Poojari C, Brankatschk B, Vattulainen I, Strauss M, Coskun Ü. Cryo-EM structure of the complete and ligand-saturated insulin receptor ectodomain. J Cell Biol 2020; 219:jcb.201907210. [PMID: 31727777 PMCID: PMC7039211 DOI: 10.1083/jcb.201907210] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 09/19/2019] [Accepted: 10/20/2019] [Indexed: 12/20/2022] Open
Abstract
Glucose homeostasis and growth essentially depend on the hormone insulin engaging its receptor. Despite biochemical and structural advances, a fundamental contradiction has persisted in the current understanding of insulin ligand-receptor interactions. While biochemistry predicts two distinct insulin binding sites, 1 and 2, recent structural analyses have resolved only site 1. Using a combined approach of cryo-EM and atomistic molecular dynamics simulation, we present the structure of the entire dimeric insulin receptor ectodomain saturated with four insulin molecules. Complementing the previously described insulin-site 1 interaction, we present the first view of insulin bound to the discrete insulin receptor site 2. Insulin binding stabilizes the receptor ectodomain in a T-shaped conformation wherein the membrane-proximal domains converge and contact each other. These findings expand the current models of insulin binding to its receptor and of its regulation. In summary, we provide the structural basis for a comprehensive description of ligand-receptor interactions that ultimately will inform new approaches to structure-based drug design.
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Affiliation(s)
- Theresia Gutmann
- Paul Langerhans Institute Dresden of the Helmholtz Zentrum Munich at the University Hospital and Faculty of Medicine Carl Gustav Carus of Technische Universität Dresden, Dresden, Germany.,German Center for Diabetes Research, Neuherberg, Germany
| | - Ingmar B Schäfer
- Department of Structural Cell Biology, Max Planck Institute of Biochemistry, Munich, Germany
| | - Chetan Poojari
- Department of Physics, University of Helsinki, Helsinki, Finland
| | - Beate Brankatschk
- Paul Langerhans Institute Dresden of the Helmholtz Zentrum Munich at the University Hospital and Faculty of Medicine Carl Gustav Carus of Technische Universität Dresden, Dresden, Germany.,German Center for Diabetes Research, Neuherberg, Germany
| | - Ilpo Vattulainen
- Department of Physics, University of Helsinki, Helsinki, Finland.,Computational Physics Laboratory, Tampere University, Tampere, Finland
| | - Mike Strauss
- Department of Anatomy & Cell Biology, McGill University, Montreal, Quebec, Canada
| | - Ünal Coskun
- Paul Langerhans Institute Dresden of the Helmholtz Zentrum Munich at the University Hospital and Faculty of Medicine Carl Gustav Carus of Technische Universität Dresden, Dresden, Germany.,German Center for Diabetes Research, Neuherberg, Germany
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38
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Leelananda SP, Lindert S. Using NMR Chemical Shifts and Cryo-EM Density Restraints in Iterative Rosetta-MD Protein Structure Refinement. J Chem Inf Model 2020; 60:2522-2532. [PMID: 31872764 PMCID: PMC7262651 DOI: 10.1021/acs.jcim.9b00932] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Cryo-EM has become one of the prime methods for protein structure elucidation, frequently yielding density maps with near-atomic or medium resolution. If protein structures cannot be deduced unambiguously from the density maps, computational structure refinement tools are needed to generate protein structural models. We have previously developed an iterative Rosetta-MDFF protocol that used cryo-EM densities to refine protein structures. Here we show that, in addition to cryo-EM densities, incorporation of other experimental restraints into the Rosetta-MDFF protocol further improved refined structures. We used NMR chemical shift (CS) data integrated with cryo-EM densities in our hybrid protocol in both the Rosetta step and the molecular dynamics (MD) simulations step. In 15 out of 18 cases for all MD rounds, the refinement results obtained when density maps and NMR chemical shift data were used in combination outperformed those of density map-only refinement. Notably, the improvement in refinement was highest when medium and low-resolution density maps were used. With our hybrid method, the RMSDs of final models obtained were always better than the RMSDs obtained by our previous protocol with just density refinement for both medium (6.9 Å) and low (9 Å) resolution maps. For all the six test proteins with medium resolution density maps (6.9 Å), the final refined structure RMSDs were lower for the hybrid method than for the cryo-EM only refinement. The final refined RMSDs were less than 1.5 Å when our hybrid protocol was used with 4 Å density maps. For four out of the six proteins the final RMSDs were even less than 1 Å. This study demonstrates that by using a combination of cryo-EM and NMR restraints, it is possible to refine structures to atomic resolution, outperforming single restraint refinement. This hybrid protocol will be a valuable tool when only low-resolution cryo-EM density data and NMR chemical shift data are available to refine structures.
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Affiliation(s)
- Sumudu P. Leelananda
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, OH, 43210
| | - Steffen Lindert
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, OH, 43210
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39
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González B, Monroe L, Li K, Yan R, Wright E, Walter T, Kihara D, Weintraub ST, Thomas JA, Serwer P, Jiang W. Phage G Structure at 6.1 Å Resolution, Condensed DNA, and Host Identity Revision to a Lysinibacillus. J Mol Biol 2020; 432:4139-4153. [PMID: 32454153 DOI: 10.1016/j.jmb.2020.05.016] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 05/21/2020] [Accepted: 05/21/2020] [Indexed: 11/16/2022]
Abstract
Phage G has the largest capsid and genome of any known propagated phage. Many aspects of its structure, assembly, and replication have not been elucidated. Herein, we present the dsDNA-packed and empty phage G capsid at 6.1 and 9 Å resolution, respectively, using cryo-EM for structure determination and mass spectrometry for protein identification. The major capsid protein, gp27, is identified and found to share the HK97-fold universally conserved in all previously solved dsDNA phages. Trimers of the decoration protein, gp26, sit on the 3-fold axes and are thought to enhance the interactions of the hexameric capsomeres of gp27, for other phages encoding decoration proteins. Phage G's decoration protein is longer than what has been reported in other phages, and we suspect the extra interaction surface area helps stabilize the capsid. We identified several additional capsid proteins, including a candidate for the prohead protease responsible for processing gp27. Furthermore, cryo-EM reveals a range of partially full, condensed DNA densities that appear to have no contact with capsid shell. Three analyses confirm that the phage G host is a Lysinibacillus, and not Bacillus megaterium: identity of host proteins in our mass spectrometry analyses, genome sequence of the phage G host, and host range of phage G.
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Affiliation(s)
- Brenda González
- Department of Biological Sciences, Hockmeyer Hall of Structural Biology, Purdue University, 240 South Martin Jischke Drive, West Lafayette, IN 47907-1971, USA
| | - Lyman Monroe
- Department of Biological Sciences, Hockmeyer Hall of Structural Biology, Purdue University, 240 South Martin Jischke Drive, West Lafayette, IN 47907-1971, USA
| | - Kunpeng Li
- Department of Biological Sciences, Hockmeyer Hall of Structural Biology, Purdue University, 240 South Martin Jischke Drive, West Lafayette, IN 47907-1971, USA
| | - Rui Yan
- Department of Biological Sciences, Hockmeyer Hall of Structural Biology, Purdue University, 240 South Martin Jischke Drive, West Lafayette, IN 47907-1971, USA
| | - Elena Wright
- Department of Biochemistry and Structural Biology, The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229-3900, USA
| | - Thomas Walter
- Department of Biological Sciences, Hockmeyer Hall of Structural Biology, Purdue University, 240 South Martin Jischke Drive, West Lafayette, IN 47907-1971, USA
| | - Daisuke Kihara
- Department of Biological Sciences, Hockmeyer Hall of Structural Biology, Purdue University, 240 South Martin Jischke Drive, West Lafayette, IN 47907-1971, USA; Department of Computer Science, Purdue University, 305 North University Street, West Lafayette, IN 47907-2107, USA
| | - Susan T Weintraub
- Department of Biochemistry and Structural Biology, The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229-3900, USA
| | - Julie A Thomas
- Gosnell School of Life Sciences, Rochester Institute of Technology, 85 Lomb Memorial Drive, Rochester, NY 14623, USA
| | - Philip Serwer
- Department of Biochemistry and Structural Biology, The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229-3900, USA
| | - Wen Jiang
- Department of Biological Sciences, Hockmeyer Hall of Structural Biology, Purdue University, 240 South Martin Jischke Drive, West Lafayette, IN 47907-1971, USA; Department of Chemistry, Purdue University, 560 Oval Drive, West Lafayette, IN 47907-2084, USA; Purdue Cryo-EM Facility, Purdue University, Hockmeyer Hall of Structural Biology, 240 South Martin Jischke Drive, West Lafayette, IN 47907-1971, USA; Purdue Center for Cancer Research, Purdue University, 201 South University Street, West Lafayette, IN 47907, USA; Purdue Institute for Infectious, Immunology and Inflammatory Diseases, Purdue University, 207 South Martin Jischke Drive, West Lafayette, IN 47907, USA; Purdue Institute for Drug Discovery, Purdue University, 720 Clinic Drive, West Lafayette, IN 47097, USA.
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40
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Costa MGS, Fagnen C, Vénien-Bryan C, Perahia D. A New Strategy for Atomic Flexible Fitting in Cryo-EM Maps by Molecular Dynamics with Excited Normal Modes (MDeNM-EMfit). J Chem Inf Model 2020; 60:2419-2423. [DOI: 10.1021/acs.jcim.9b01148] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Mauricio G. S. Costa
- Fundacao Oswaldo Cruz, Programa de Computação Científica, Vice-Presidência de Educação, Informação e Comunicação, Av. Brasil 4365, Residência Oficial, Manguinhos, 21040-900 Rio de Janeiro, Brazil
- Sorbonne Université, UMR 7590, CNRS, Museum National d’Histoire Naturelle, Institut de Minéralogie, Physique des Matériaux et Cosmochimie, IMPMC, 4 place Jussieu, 75005 Paris, France
- École Normale Supérieure Paris-Saclay, UMR 8113, CNRS, Laboratoire de Biologie et de Pharmacologie Appliquée 61 Av du Président Wilson, 94235 Cachan, France
| | - Charline Fagnen
- Sorbonne Université, UMR 7590, CNRS, Museum National d’Histoire Naturelle, Institut de Minéralogie, Physique des Matériaux et Cosmochimie, IMPMC, 4 place Jussieu, 75005 Paris, France
- École Normale Supérieure Paris-Saclay, UMR 8113, CNRS, Laboratoire de Biologie et de Pharmacologie Appliquée 61 Av du Président Wilson, 94235 Cachan, France
| | - Catherine Vénien-Bryan
- Sorbonne Université, UMR 7590, CNRS, Museum National d’Histoire Naturelle, Institut de Minéralogie, Physique des Matériaux et Cosmochimie, IMPMC, 4 place Jussieu, 75005 Paris, France
| | - David Perahia
- École Normale Supérieure Paris-Saclay, UMR 8113, CNRS, Laboratoire de Biologie et de Pharmacologie Appliquée 61 Av du Président Wilson, 94235 Cachan, France
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41
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Cassidy CK, Himes BA, Sun D, Ma J, Zhao G, Parkinson JS, Stansfeld PJ, Luthey-Schulten Z, Zhang P. Structure and dynamics of the E. coli chemotaxis core signaling complex by cryo-electron tomography and molecular simulations. Commun Biol 2020; 3:24. [PMID: 31925330 PMCID: PMC6954272 DOI: 10.1038/s42003-019-0748-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 12/19/2019] [Indexed: 01/08/2023] Open
Abstract
To enable the processing of chemical gradients, chemotactic bacteria possess large arrays of transmembrane chemoreceptors, the histidine kinase CheA, and the adaptor protein CheW, organized as coupled core-signaling units (CSU). Despite decades of study, important questions surrounding the molecular mechanisms of sensory signal transduction remain unresolved, owing especially to the lack of a high-resolution CSU structure. Here, we use cryo-electron tomography and sub-tomogram averaging to determine a structure of the Escherichia coli CSU at sub-nanometer resolution. Based on our experimental data, we use molecular simulations to construct an atomistic model of the CSU, enabling a detailed characterization of CheA conformational dynamics in its native structural context. We identify multiple, distinct conformations of the critical P4 domain as well as asymmetries in the localization of the P3 bundle, offering several novel insights into the CheA signaling mechanism.
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Affiliation(s)
- C Keith Cassidy
- Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK.
- Department of Physics and Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - Benjamin A Himes
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA
| | - Dapeng Sun
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA
| | - Jun Ma
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA
| | - Gongpu Zhao
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA
| | - John S Parkinson
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Phillip J Stansfeld
- Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK
- School of Life Sciences & Department of Chemistry, University of Warwick, Coventry, CV4 7AL, UK
| | - Zaida Luthey-Schulten
- Department of Physics and Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Chemistry and Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Peijun Zhang
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA.
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK.
- Electron Bio-Imaging Centre, Diamond Light Sources, Harwell Science and Innovation Campus, Didcot, OX11 0DE, UK.
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42
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Abstract
Recent improvements in cryo-electron microscopy (cryo-EM) in the past few years are now allowing to observe molecular complexes at atomic resolution. As a consequence, numerous structures derived from cryo-EM are now available in the Protein Data Bank. However, if for some complexes atomic resolution is reached, this is not true for all. This is also the case in cryo-electron tomography where the achievable resolution is still limited. Furthermore the resolution in a cryo-EM map is not a constant, with often outer regions being of lower resolution, possibly linked to conformational variability. Although those low- to medium-resolution EM maps (or regions thereof) cannot directly provide atomic structure of large molecular complexes, they provide valuable information to model the individual components and their assembly into them. Most approaches for this kind of modeling are performing rigid fitting of the individual components into the EM density map. While this would appear an obvious option, they ignore key aspects of molecular recognition, the energetics and flexibility of the interfaces. Moreover, this often restricts the modeling to a unique source of data, the EM density map.In this chapter, we describe a protocol where an EM map is used as restraint in HADDOCK to guide the modeling process. In the first step, rigid-body fitting is performed with PowerFit in order to identify the most likely locations of the molecules into the map. These are then used as centroids to which distance restraints are defined from the center of mass of the components of the complex for the initial rigid-body docking. The EM density is then directly used as an additional restraint energy term, which can be combined with all the other types of data supported by HADDOCK. This protocol relies on the new version 2.4 of both the HADDOCK webserver and software. Preparation steps consisting of cropping the EM map and rigid-body fitting of the atomic structure are explained. Then, the EM-driven docking protocol using HADDOCK is illustrated.
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Affiliation(s)
- Mikael Trellet
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Faculty of Science-Chemistry, Utrecht University, Utrecht, The Netherlands
| | - Gydo van Zundert
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Faculty of Science-Chemistry, Utrecht University, Utrecht, The Netherlands
| | - Alexandre M J J Bonvin
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Faculty of Science-Chemistry, Utrecht University, Utrecht, The Netherlands.
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43
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Terwilliger TC, Adams PD, Afonine PV, Sobolev OV. Cryo-EM map interpretation and protein model-building using iterative map segmentation. Protein Sci 2020; 29:87-99. [PMID: 31599033 PMCID: PMC6933853 DOI: 10.1002/pro.3740] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 09/30/2019] [Accepted: 10/01/2019] [Indexed: 11/17/2022]
Abstract
A procedure for building protein chains into maps produced by single-particle electron cryo-microscopy (cryo-EM) is described. The procedure is similar to the way an experienced structural biologist might analyze a map, focusing first on secondary structure elements such as helices and sheets, then varying the contour level to identify connections between these elements. Since the high density in a map typically follows the main-chain of the protein, the main-chain connection between secondary structure elements can often be identified as the unbranched path between them with the highest minimum value along the path. This chain-tracing procedure is then combined with finding side-chain positions based on the presence of density extending away from the main path of the chain, allowing generation of a Cα model. The Cα model is converted to an all-atom model and is refined against the map. We show that this procedure is as effective as other existing methods for interpretation of cryo-EM maps and that it is considerably faster and produces models with fewer chain breaks than our previous methods that were based on approaches developed for crystallographic maps.
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Affiliation(s)
- Thomas C. Terwilliger
- Los Alamos National LaboratoryLos AlamosNew Mexico
- New Mexico ConsortiumLos AlamosNew Mexico
| | - Paul D. Adams
- Molecular Biophysics & Integrated Bioimaging DivisionLawrence Berkeley National LaboratoryBerkeleyCalifornia
- Department of BioengineeringUniversity of California BerkeleyBerkeleyCalifornia
| | - Pavel V. Afonine
- Molecular Biophysics & Integrated Bioimaging DivisionLawrence Berkeley National LaboratoryBerkeleyCalifornia
| | - Oleg V. Sobolev
- Molecular Biophysics & Integrated Bioimaging DivisionLawrence Berkeley National LaboratoryBerkeleyCalifornia
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44
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Yang W, Cassidy CK, Ames P, Diebolder CA, Schulten K, Luthey-Schulten Z, Parkinson JS, Briegel A. In Situ Conformational Changes of the Escherichia coli Serine Chemoreceptor in Different Signaling States. mBio 2019; 10:e00973-19. [PMID: 31266867 PMCID: PMC6606802 DOI: 10.1128/mbio.00973-19] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 05/31/2019] [Indexed: 11/20/2022] Open
Abstract
Tsr, the serine chemoreceptor in Escherichia coli, transduces signals from a periplasmic ligand-binding site to its cytoplasmic tip, where it controls the activity of the CheA kinase. To function, Tsr forms trimers of homodimers (TODs), which associate in vivo with the CheA kinase and CheW coupling protein. Together, these proteins assemble into extended hexagonal arrays. Here, we use cryo-electron tomography and molecular dynamics simulation to study Tsr in the context of a near-native array, characterizing its signaling-related conformational changes at both the individual dimer and the trimer level. In particular, we show that individual Tsr dimers within a trimer exhibit asymmetric flexibilities that are a function of the signaling state, highlighting the effect of their different protein interactions at the receptor tips. We further reveal that the dimer compactness of the Tsr trimer changes between signaling states, transitioning at the glycine hinge from a compact conformation in the kinase-OFF state to an expanded conformation in the kinase-ON state. Hence, our results support a crucial role for the glycine hinge: to allow the receptor flexibility necessary to achieve different signaling states while also maintaining structural constraints imposed by the membrane and extended array architecture.IMPORTANCE In Escherichia coli, membrane-bound chemoreceptors, the histidine kinase CheA, and coupling protein CheW form highly ordered chemosensory arrays. In core signaling complexes, chemoreceptor trimers of dimers undergo conformational changes, induced by ligand binding and sensory adaptation, which regulate kinase activation. Here, we characterize by cryo-electron tomography the kinase-ON and kinase-OFF conformations of the E. coli serine receptor in its native array context. We found distinctive structural differences between the members of a receptor trimer, which contact different partners in the signaling unit, and structural differences between the ON and OFF signaling complexes. Our results provide new insights into the signaling mechanism of chemoreceptor arrays and suggest an important functional role for a previously postulated flexible region and glycine hinge in the receptor molecule.
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Affiliation(s)
- Wen Yang
- Institute of Biology, Leiden University, Leiden, The Netherlands
| | - C Keith Cassidy
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
- Department of Physics and Beckman Institute, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - Peter Ames
- School of Biological Sciences, University of Utah, Salt Lake City, Utah, USA
| | | | - Klaus Schulten
- Department of Physics and Beckman Institute, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - Zaida Luthey-Schulten
- Department of Chemistry and Center for the Physics of Living Cells, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - John S Parkinson
- School of Biological Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Ariane Briegel
- Institute of Biology, Leiden University, Leiden, The Netherlands
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45
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Simeon R, Jiang M, Chamoun-Emanuelli AM, Yu H, Zhang Y, Meng R, Peng Z, Jakana J, Zhang J, Feng H, Chen Z. Selection and characterization of ultrahigh potency designed ankyrin repeat protein inhibitors of C. difficile toxin B. PLoS Biol 2019; 17:e3000311. [PMID: 31233493 PMCID: PMC6590788 DOI: 10.1371/journal.pbio.3000311] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Accepted: 05/20/2019] [Indexed: 12/18/2022] Open
Abstract
Clostridium difficile infection (CDI) is a major nosocomial disease associated with significant morbidity and mortality. The pathology of CDI stems primarily from the 2 C. difficile-secreted exotoxins-toxin A (TcdA) and toxin B (TcdB)-that disrupt the tight junctions between epithelial cells leading to the loss of colonic epithelial barrier function. Here, we report the engineering of a series of monomeric and dimeric designed ankyrin repeat proteins (DARPins) for the neutralization of TcdB. The best dimeric DARPin, DLD-4, inhibited TcdB with a half maximal effective concentration (EC50) of 4 pM in vitro, representing an approximately 330-fold higher potency than the Food and Drug Administration (FDA)-approved anti-TcdB monoclonal antibody bezlotoxumab in the same assay. DLD-4 also protected mice from a toxin challenge in vivo. Cryo-electron microscopy (cryo-EM) studies revealed that the 2 constituent DARPins of DLD-4-1.4E and U3-bind the central and C-terminal regions of the delivery domain of TcdB. Competitive enzyme-linked immunosorbent assay (ELISA) studies showed that the DARPins 1.4E and U3 interfere with the interaction between TcdB and its receptors chondroitin sulfate proteoglycan 4 (CSPG4) and frizzled class receptor 2 (FZD2), respectively. Our cryo-EM studies revealed a new conformation of TcdB (both apo- and DARPin-bound at pH 7.4) in which the combined repetitive oligopeptides (CROPS) domain points away from the delivery domain. This conformation of the CROPS domain is in stark contrast to that seen in the negative-stain electron microscopy (EM) structure of TcdA and TcdB at the same pH, in which the CROPS domain bends toward and "kisses" the delivery domain. The ultrapotent anti-TcdB molecules from this study serve as candidate starting points for CDI drug development and provide new biological tools for studying the pathogenicity of C. difficile. The structural insights regarding both the "native" conformation of TcdB and the putative sites of TcdB interaction with the FZD2 receptor, in particular, should help accelerate the development of next-generation anti-C. difficile toxin therapeutics.
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Affiliation(s)
- Rudo Simeon
- Department of Microbial Pathogenesis and Immunology, Texas A&M University Health Science Center, College Station, Texas, United States of America
| | - Mengqiu Jiang
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas, United States of America
| | - Ana M. Chamoun-Emanuelli
- Department of Microbial Pathogenesis and Immunology, Texas A&M University Health Science Center, College Station, Texas, United States of America
| | - Hua Yu
- Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, Maryland, United Sates of America
| | - Yongrong Zhang
- Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, Maryland, United Sates of America
| | - Ran Meng
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas, United States of America
| | - Zeyu Peng
- Department of Microbial Pathogenesis and Immunology, Texas A&M University Health Science Center, College Station, Texas, United States of America
| | - Joanita Jakana
- National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas, United States of America
| | - Junjie Zhang
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas, United States of America
| | - Hanping Feng
- Department of Microbial Pathogenesis, University of Maryland Dental School, Baltimore, Maryland, United Sates of America
| | - Zhilei Chen
- Department of Microbial Pathogenesis and Immunology, Texas A&M University Health Science Center, College Station, Texas, United States of America
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46
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Igaev M, Kutzner C, Bock LV, Vaiana AC, Grubmüller H. Automated cryo-EM structure refinement using correlation-driven molecular dynamics. eLife 2019; 8:e43542. [PMID: 30829573 PMCID: PMC6424565 DOI: 10.7554/elife.43542] [Citation(s) in RCA: 59] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Accepted: 03/03/2019] [Indexed: 12/22/2022] Open
Abstract
We present a correlation-driven molecular dynamics (CDMD) method for automated refinement of atomistic models into cryo-electron microscopy (cryo-EM) maps at resolutions ranging from near-atomic to subnanometer. It utilizes a chemically accurate force field and thermodynamic sampling to improve the real-space correlation between the modeled structure and the cryo-EM map. Our framework employs a gradual increase in resolution and map-model agreement as well as simulated annealing, and allows fully automated refinement without manual intervention or any additional rotamer- and backbone-specific restraints. Using multiple challenging systems covering a wide range of map resolutions, system sizes, starting model geometries and distances from the target state, we assess the quality of generated models in terms of both model accuracy and potential of overfitting. To provide an objective comparison, we apply several well-established methods across all examples and demonstrate that CDMD performs best in most cases.
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Affiliation(s)
- Maxim Igaev
- Department of Theoretical and Computational BiophysicsMax Planck Institute for Biophysical ChemistryGöttingenGermany
| | - Carsten Kutzner
- Department of Theoretical and Computational BiophysicsMax Planck Institute for Biophysical ChemistryGöttingenGermany
| | - Lars V Bock
- Department of Theoretical and Computational BiophysicsMax Planck Institute for Biophysical ChemistryGöttingenGermany
| | - Andrea C Vaiana
- Department of Theoretical and Computational BiophysicsMax Planck Institute for Biophysical ChemistryGöttingenGermany
| | - Helmut Grubmüller
- Department of Theoretical and Computational BiophysicsMax Planck Institute for Biophysical ChemistryGöttingenGermany
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47
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Wang Y, Shekhar M, Thifault D, Williams CJ, McGreevy R, Richardson J, Singharoy A, Tajkhorshid E. Constructing atomic structural models into cryo-EM densities using molecular dynamics - Pros and cons. J Struct Biol 2018; 204:319-328. [PMID: 30092279 PMCID: PMC6394829 DOI: 10.1016/j.jsb.2018.08.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Revised: 07/31/2018] [Accepted: 08/05/2018] [Indexed: 01/11/2023]
Abstract
Accurate structure determination from electron density maps at 3-5 Å resolution necessitates a balance between extensive global and local sampling of atomistic models, yet with the stereochemical correctness of backbone and sidechain geometries. Molecular Dynamics Flexible Fitting (MDFF), particularly through a resolution-exchange scheme, ReMDFF, provides a robust way of achieving this balance for hybrid structure determination. Employing two high-resolution density maps, namely that of β-galactosidase at 3.2 Å and TRPV1 at 3.4 Å, we showcase the quality of ReMDFF-generated models, comparing them against ones submitted by independent research groups for the 2015-2016 Cryo-EM Model Challenge. This comparison offers a clear evaluation of ReMDFF's strengths and shortcomings, and those of data-guided real-space refinements in general. ReMDFF results scored highly on the various metric for judging the quality-of-fit and quality-of-model. However, some systematic discrepancies are also noted employing a Molprobity analysis, that are reproducible across multiple competition entries. A space of key refinement parameters is explored within ReMDFF to observe their impact within the final model. Choice of force field parameters and initial model seem to have the most significant impact on ReMDFF model-quality. To this end, very recently developed CHARMM36m force field parameters provide now more refined ReMDFF models than the ones originally submitted to the Cryo-EM challenge. Finally, a set of good-practices is prescribed for the community to benefit from the MDFF developments.
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Affiliation(s)
- Yuhang Wang
- Center for Biophysics and Quantitative Biology, College of Medicine, Department of Biochemistry, Beckman Institute for Advanced Science and Technology, and University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
| | - Mrinal Shekhar
- Center for Biophysics and Quantitative Biology, College of Medicine, Department of Biochemistry, Beckman Institute for Advanced Science and Technology, and University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
| | - Darren Thifault
- School of Molecular Sciences, Center for Applied Structural Discovery, Arizona State University, Tempe, AZ 85287, United States
| | | | - Ryan McGreevy
- Center for Biophysics and Quantitative Biology, College of Medicine, Department of Biochemistry, Beckman Institute for Advanced Science and Technology, and University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
| | - Jane Richardson
- Department of Biochemistry, Duke University, Durham, NC 27710, United States
| | - Abhishek Singharoy
- School of Molecular Sciences, Center for Applied Structural Discovery, Arizona State University, Tempe, AZ 85287, United States.
| | - Emad Tajkhorshid
- NIH Center for Macromolecular Modeling and Bioinformatics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States; Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States; Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
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Nagai T, Mochizuki Y, Joti Y, Tama F, Miyashita O. Gaussian mixture model for coarse-grained modeling from XFEL. OPTICS EXPRESS 2018; 26:26734-26749. [PMID: 30469754 DOI: 10.1364/oe.26.026734] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Accepted: 09/01/2018] [Indexed: 06/09/2023]
Abstract
We explore the advantage of Gaussian mixture model (GMM) for interpretation of single particle diffraction patterns from X-ray free electron laser (XFEL) experiments. GMM approximates a biomolecular shape by the superposition of Gaussian distributions. As the Fourier transformation of GMM can be quickly performed, we can efficiently simulate XFEL diffraction patterns from approximated structure models. We report that the resolution that GMM can accurately reproduce is proportional to the cubic root of the number of Gaussians used in the modeling. This behavior can be attributed to the correspondence between the number of adjustable parameters in GMM and the amount of sampling points in diffraction space. Furthermore, GMMs can successfully be used to perform angular assignment and to detect conformational variation. These results demonstrate that GMMs serve as useful coarse-grained models for hybrid approach in XFEL single particle experiments.
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49
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Tiwari SP, Tama F, Miyashita O. Searching for 3D structural models from a library of biological shapes using a few 2D experimental images. BMC Bioinformatics 2018; 19:320. [PMID: 30208849 PMCID: PMC6134691 DOI: 10.1186/s12859-018-2358-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Accepted: 09/03/2018] [Indexed: 01/08/2023] Open
Abstract
Background Advancements in biophysical experimental techniques have pushed the limits in terms of the types of phenomena that can be characterized, the amount of data that can be produced and the resolution at which we can visualize them. Single particle techniques such as Electron Microscopy (EM) and X-ray free electron laser (XFEL) scattering require a large number of 2D images collected to resolve three-dimensional (3D) structures. In this study, we propose a quick strategy to retrieve potential 3D shapes, as low-resolution models, from a few 2D experimental images by searching a library of 2D projection images generated from existing 3D structures. Results We developed the protocol to assemble a non-redundant set of 3D shapes for generating the 2D image library, and to retrieve potential match 3D shapes for query images, using EM data as a test. In our strategy, we disregard differences in volume size, giving previously unknown structures and conformations a greater number of 3D biological shapes as possible matches. We tested the strategy using images from three EM models as query images for searches against a library of 22750 2D projection images generated from 250 random EM models. We found that our ability to identify 3D shapes that match the query images depends on how complex the outline of the 2D shapes are and whether they are represented in the search image library. Conclusions Through our computational method, we are able to quickly retrieve a 3D shape from a few 2D projection images. Our approach has the potential for exploring other types of 2D single particle structural data such as from XFEL scattering experiments, for providing a tool to interpret low-resolution data that may be insufficient for 3D reconstruction, and for estimating the mixing of states or conformations that could exist in such experimental data. Electronic supplementary material The online version of this article (10.1186/s12859-018-2358-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sandhya P Tiwari
- Computational Structural Biology Unit, RIKEN Center for Computational Science, Kobe, Japan
| | - Florence Tama
- Computational Structural Biology Unit, RIKEN Center for Computational Science, Kobe, Japan. .,Graduate School of Science, Department of Physics & Institute of Transformative Bio-Molecules (WPI-ITbM), Nagoya University, Nagoya, Japan.
| | - Osamu Miyashita
- Computational Structural Biology Unit, RIKEN Center for Computational Science, Kobe, Japan
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50
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Terashi G, Kihara D. De novo main-chain modeling with MAINMAST in 2015/2016 EM Model Challenge. J Struct Biol 2018; 204:351-359. [PMID: 30075190 PMCID: PMC6179447 DOI: 10.1016/j.jsb.2018.07.013] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Revised: 07/13/2018] [Accepted: 07/19/2018] [Indexed: 11/15/2022]
Abstract
Protein tertiary structure modeling is a critical step for the interpretation of three dimensional (3D) election microscopy density. Our group participated the 2015/2016 EM Model Challenge using the MAINMAST software for a de novo main chain modeling. The software generates local dense points using the mean shifting algorithm, and connects them into Cα models by calculating the minimum spanning tree and the longest path. Subsequently, full atom structure models are generated, which are subject to structural refinement. Here, we summarize the qualities of our submitted models and examine successful and unsuccessful models, including 3D models we did not submit to the Challenge. Our protocol using the MAINMAST software was sometimes able to build correct conformations with 3.4–5.1 Å RMSD. Unsuccessful models had failure of chain traces, however, their Cα positions and some local structures were quite correctly built. For evaluate the quality of the models, the MAINMAST software provides a confidence score for each Cα position from the consensus of top 100 scoring models.
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Affiliation(s)
- Genki Terashi
- Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA
| | - Daisuke Kihara
- Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA; Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA.
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