1
|
Yamamori Y, Tomii K. Application of Homology Modeling by Enhanced Profile-Profile Alignment and Flexible-Fitting Simulation to Cryo-EM Based Structure Determination. Int J Mol Sci 2022; 23:ijms23041977. [PMID: 35216093 PMCID: PMC8879198 DOI: 10.3390/ijms23041977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 02/07/2022] [Accepted: 02/09/2022] [Indexed: 12/03/2022] Open
Abstract
Application of cryo-electron microscopy (cryo-EM) is crucially important for ascertaining the atomic structure of large biomolecules such as ribosomes and protein complexes in membranes. Advances in cryo-EM technology and software have made it possible to obtain data with near-atomic resolution, but the method is still often capable of producing only a density map with up to medium resolution, either partially or entirely. Therefore, bridging the gap separating the density map and the atomic model is necessary. Herein, we propose a methodology for constructing atomic structure models based on cryo-EM maps with low-to-medium resolution. The method is a combination of sensitive and accurate homology modeling using our profile–profile alignment method with a flexible-fitting method using molecular dynamics simulation. As described herein, this study used benchmark applications to evaluate the model constructions of human two-pore channel 2 (one target protein in CASP13 with its structure determined using cryo-EM data) and the overall structure of Enterococcus hirae V-ATPase complex.
Collapse
Affiliation(s)
- Yu Yamamori
- Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan;
| | - Kentaro Tomii
- Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan;
- AIST-Tokyo Tech Real World Big-Data Computation Open Innovation Laboratory (RWBC-OIL), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan
- Correspondence:
| |
Collapse
|
2
|
Kulik M, Mori T, Sugita Y. Multi-Scale Flexible Fitting of Proteins to Cryo-EM Density Maps at Medium Resolution. Front Mol Biosci 2021; 8:631854. [PMID: 33842541 PMCID: PMC8025875 DOI: 10.3389/fmolb.2021.631854] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Accepted: 01/26/2021] [Indexed: 11/13/2022] Open
Abstract
Structure determination using cryo-electron microscopy (cryo-EM) medium-resolution density maps is often facilitated by flexible fitting. Avoiding overfitting, adjusting force constants driving the structure to the density map, and emulating complex conformational transitions are major concerns in the fitting. To address them, we develop a new method based on a three-step multi-scale protocol. First, flexible fitting molecular dynamics (MD) simulations with coarse-grained structure-based force field and replica-exchange scheme between different force constants replicas are performed. Second, fitted Cα atom positions guide the all-atom structure in targeted MD. Finally, the all-atom flexible fitting refinement in implicit solvent adjusts the positions of the side chains in the density map. Final models obtained via the multi-scale protocol are significantly better resolved and more reliable in comparison with long all-atom flexible fitting simulations. The protocol is useful for multi-domain systems with intricate structural transitions as it preserves the secondary structure of single domains.
Collapse
Affiliation(s)
- Marta Kulik
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako-shi, Japan
| | - Takaharu Mori
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako-shi, Japan
| | - Yuji Sugita
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako-shi, Japan.,RIKEN Center for Computational Science, Kobe, Japan.,RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| |
Collapse
|
3
|
Kidmose RT, Juhl J, Nissen P, Boesen T, Karlsen JL, Pedersen BP. Namdinator - automatic molecular dynamics flexible fitting of structural models into cryo-EM and crystallography experimental maps. IUCrJ 2019; 6:526-531. [PMID: 31316797 PMCID: PMC6608625 DOI: 10.1107/s2052252519007619] [Citation(s) in RCA: 189] [Impact Index Per Article: 37.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2019] [Accepted: 05/25/2019] [Indexed: 05/20/2023]
Abstract
Model building into experimental maps is a key element of structural biology, but can be both time consuming and error prone for low-resolution maps. Here we present Namdinator, an easy-to-use tool that enables the user to run a molecular dynamics flexible fitting simulation followed by real-space refinement in an automated manner through a pipeline system. Namdinator will modify an atomic model to fit within cryo-EM or crystallography density maps, and can be used advantageously for both the initial fitting of models, and for a geometrical optimization step to correct outliers, clashes and other model problems. We have benchmarked Namdinator against 39 deposited cryo-EM models and maps, and observe model improvements in 34 of these cases (87%). Clashes between atoms were reduced, and the model-to-map fit and overall model geometry were improved, in several cases substantially. We show that Namdinator is able to model large-scale conformational changes compared to the starting model. Namdinator is a fast and easy tool for structural model builders at all skill levels. Namdinator is available as a web service (https://namdinator.au.dk), or it can be run locally as a command-line tool.
Collapse
Affiliation(s)
- Rune Thomas Kidmose
- Centre for Structural Biology, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10C, Aarhus, DK-8000, Denmark
| | - Jonathan Juhl
- Centre for Structural Biology, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10C, Aarhus, DK-8000, Denmark
| | - Poul Nissen
- Centre for Structural Biology, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10C, Aarhus, DK-8000, Denmark
| | - Thomas Boesen
- Centre for Structural Biology, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10C, Aarhus, DK-8000, Denmark
| | - Jesper Lykkegaard Karlsen
- Centre for Structural Biology, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10C, Aarhus, DK-8000, Denmark
- Correspondence e-mail: ,
| | - Bjørn Panyella Pedersen
- Centre for Structural Biology, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10C, Aarhus, DK-8000, Denmark
- Correspondence e-mail: ,
| |
Collapse
|
4
|
Mori T, Kulik M, Miyashita O, Jung J, Tama F, Sugita Y. Acceleration of cryo-EM Flexible Fitting for Large Biomolecular Systems by Efficient Space Partitioning. Structure 2018; 27:161-174.e3. [PMID: 30344106 DOI: 10.1016/j.str.2018.09.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Revised: 06/22/2018] [Accepted: 09/18/2018] [Indexed: 01/21/2023]
Abstract
Flexible fitting is a powerful technique to build the 3D structures of biomolecules from cryoelectron microscopy (cryo-EM) density maps. One popular method is a cross-correlation coefficient-based approach, where the molecular dynamics (MD) simulation is carried out with the biasing potential that includes the cross-correlation coefficient between the experimental and simulated density maps. Here, we propose efficient parallelization schemes for the calculation of the cross-correlation coefficient to accelerate flexible fitting. Our schemes are tested for small, medium, and large biomolecules using CPU and hybrid CPU + GPU architectures. The scheme for the atomic decomposition MD is suitable for small proteins such as Ca2+-ATPase with the all-atom Go model, while that for the domain decomposition MD is better for larger systems such as ribosome with the all-atom Go or the all-atom explicit solvent models. Our methods allow flexible fitting for various biomolecules with reasonable computational cost. This approach also connects high-resolution structure refinements with investigation of protein structure-function relationship.
Collapse
Affiliation(s)
- Takaharu Mori
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
| | - Marta Kulik
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
| | - Osamu Miyashita
- RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Jaewoon Jung
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan; RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Florence Tama
- RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; Department of Physics, Graduate School of Science, and Institute of Transformative Bio-Molecules, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602, Japan
| | - Yuji Sugita
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan; RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; RIKEN Center for Biosystems Dynamics Research, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.
| |
Collapse
|
5
|
Zheng W, Sachs F. Investigating the structural dynamics of the PIEZO1 channel activation and inactivation by coarse-grained modeling. Proteins 2017; 85:2198-2208. [PMID: 28905417 DOI: 10.1002/prot.25384] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Revised: 08/22/2017] [Accepted: 09/10/2017] [Indexed: 01/07/2023]
Abstract
The PIEZO channels, a family of mechanosensitive channels in vertebrates, feature a fast activation by mechanical stimuli (eg, membrane tension) followed by a slower inactivation. Although a medium-resolution structure of the trimeric form of PIEZO1 was solved by cryo-electron microscopy (cryo-EM), key structural changes responsible for the channel activation and inactivation are still unknown. Toward decrypting the structural mechanism of the PIEZO1 activation and inactivation, we performed systematic coarse-grained modeling using an elastic network model and related modeling/analysis tools (ie, normal mode analysis, flexibility and hotspot analysis, correlation analysis, and cryo-EM-based hybrid modeling and flexible fitting). We identified four key motional modes that may drive the tension-induced activation and inactivation, with fast and slow relaxation time, respectively. These modes allosterically couple the lateral and vertical motions of the peripheral domains to the opening and closing of the intra-cellular vestibule, enabling external mechanical forces to trigger, and regulate the activation/inactivation transitions. We also calculated domain-specific flexibility profiles, and predicted hotspot residues at key domain-domain interfaces and hinges. Our results offer unprecedented structural and dynamic information, which is consistent with the literature on mutational and functional studies of the PIEZO channels, and will guide future studies of this important family of mechanosensitive channels.
Collapse
Affiliation(s)
- Wenjun Zheng
- Department of Physics, State University of New York at Buffalo, Buffalo, New York
| | - Frederick Sachs
- Department of Physiology and Biophysics, State University of New York at Buffalo, Buffalo, New York
| |
Collapse
|
6
|
Singharoy A, Teo I, McGreevy R, Stone JE, Zhao J, Schulten K. Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps. eLife 2016; 5. [PMID: 27383269 PMCID: PMC4990421 DOI: 10.7554/elife.16105] [Citation(s) in RCA: 108] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Accepted: 07/06/2016] [Indexed: 12/12/2022] Open
Abstract
Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services. DOI:http://dx.doi.org/10.7554/eLife.16105.001 To understand the roles that proteins and other large molecules play inside cells, it is important to determine their structures. One of the techniques that researchers can use to do this is called cryo-electron microscopy (cryo-EM), which rapidly freezes molecules to fix them in position before imaging them in fine detail. The cryo-EM images are like maps that show the approximate position of atoms. These images must then be processed in order to build a three-dimensional model of the protein that shows how its atoms are arranged relative to each other. One computational approach called Molecular Dynamics Flexible Fitting (MDFF) works by flexibly fitting possible atomic structures into cryo-EM maps. Although this approach works well with relatively undetailed (or ‘low resolution’) cryo-EM images, it struggles to handle the high-resolution cryo-EM maps now being generated. Singharoy, Teo, McGreevy et al. have now developed two MDFF methods – called cascade MDFF and resolution exchange MDFF – that help to resolve atomic models of biological molecules from cryo-EM images. Each method can refine poorly guessed models into ones that are consistent with the high-resolution experimental images. The refinement is achieved by interpreting a range of images that starts with a ‘fuzzy’ image. The contrast of the image is then progressively improved until an image is produced that has a resolution that is good enough to almost distinguish individual atoms. The method works because each cryo-EM image shows not just one, but a collection of atomic structures that the molecule can take on, with the fuzzier parts of the image representing the more flexible parts of the molecule. By taking into account this flexibility, the large-scale features of the protein structure can be determined first from the fuzzier images, and increasing the contrast of the images allows smaller-scale refinements to be made to the structure. The MDFF tools have been designed to be easy to use and are available to researchers at low cost through cloud computing platforms. They can now be used to unravel the structure of many different proteins and protein complexes including those involved in photosynthesis, respiration and protein synthesis. DOI:http://dx.doi.org/10.7554/eLife.16105.002
Collapse
Affiliation(s)
- Abhishek Singharoy
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Ivan Teo
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Ryan McGreevy
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States
| | - John E Stone
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Jianhua Zhao
- Department of Biochemistry and Biophysics, University of California San Francisco School of Medicine, San Francisco, United States
| | - Klaus Schulten
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, United States
| |
Collapse
|
7
|
Goh BC, Hadden JA, Bernardi RC, Singharoy A, McGreevy R, Rudack T, Cassidy CK, Schulten K. Computational Methodologies for Real-Space Structural Refinement of Large Macromolecular Complexes. Annu Rev Biophys 2016; 45:253-78. [PMID: 27145875 DOI: 10.1146/annurev-biophys-062215-011113] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The rise of the computer as a powerful tool for model building and refinement has revolutionized the field of structure determination for large biomolecular systems. Despite the wide availability of robust experimental methods capable of resolving structural details across a range of spatiotemporal resolutions, computational hybrid methods have the unique ability to integrate the diverse data from multimodal techniques such as X-ray crystallography and electron microscopy into consistent, fully atomistic structures. Here, commonly employed strategies for computational real-space structural refinement are reviewed, and their specific applications are illustrated for several large macromolecular complexes: ribosome, virus capsids, chemosensory array, and photosynthetic chromatophore. The increasingly important role of computational methods in large-scale structural refinement, along with current and future challenges, is discussed.
Collapse
Affiliation(s)
- Boon Chong Goh
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Jodi A Hadden
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Rafael C Bernardi
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Abhishek Singharoy
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Ryan McGreevy
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Till Rudack
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - C Keith Cassidy
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Klaus Schulten
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801;
| |
Collapse
|
8
|
Abstract
Single-particle cryo-EM is a powerful approach to determine the structure of large macromolecules and assemblies thereof in many cases at subnanometer resolution. It has become popular to refine or flexibly fit atomic models into density maps derived from cryo-EM experiments. These density maps are typically significantly lower in resolution than electron density maps obtained from X-ray diffraction experiments, such that the number of parameters that need to be determined is much larger than the number of experimental observables. Overfitting and misinterpretation of the density, thus, become a serious problem. For diffraction data, a cross-validation approach was introduced almost 20 y ago; however, no such approach has been described yet for structure refinement against cryo-EM density maps, although the overfitting problem is, because of the lower resolution, significantly larger. We present a cross-validation approach for real-space refinement against cryo-EM density maps in analogy to cross-validation typically used in crystallography. Our approach is able to detect overfitting and allows for optimizing the choice of restraints used in the refinement. The approach is shown on three protein structures with simulated data and experimental data of the rotavirus double-layer particle. Because cross-validation requires splitting the dataset into at least two independent sets, we further present an approach to quantify correlations between the structure factor sets. This analysis is also helpful for other cross-validation applications, such as refinements against diffraction data or 3D reconstructions of cryo-EM density maps.
Collapse
|
9
|
Armache JP, Jarasch A, Anger AM, Villa E, Becker T, Bhushan S, Jossinet F, Habeck M, Dindar G, Franckenberg S, Marquez V, Mielke T, Thomm M, Berninghausen O, Beatrix B, Söding J, Westhof E, Wilson DN, Beckmann R. Localization of eukaryote-specific ribosomal proteins in a 5.5-Å cryo-EM map of the 80S eukaryotic ribosome. Proc Natl Acad Sci U S A 2010; 107:19754-9. [PMID: 20974910 PMCID: PMC2993421 DOI: 10.1073/pnas.1010005107] [Citation(s) in RCA: 116] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Protein synthesis in all living organisms occurs on ribonucleoprotein particles, called ribosomes. Despite the universality of this process, eukaryotic ribosomes are significantly larger in size than their bacterial counterparts due in part to the presence of 80 r proteins rather than 54 in bacteria. Using cryoelectron microscopy reconstructions of a translating plant (Triticum aestivum) 80S ribosome at 5.5-Å resolution, together with a 6.1-Å map of a translating Saccharomyces cerevisiae 80S ribosome, we have localized and modeled 74/80 (92.5%) of the ribosomal proteins, encompassing 12 archaeal/eukaryote-specific small subunit proteins as well as the complete complement of the ribosomal proteins of the eukaryotic large subunit. Near-complete atomic models of the 80S ribosome provide insights into the structure, function, and evolution of the eukaryotic translational apparatus.
Collapse
Affiliation(s)
- Jean-Paul Armache
- Gene Center and Center for integrated Protein Science Munich, Department of Biochemistry, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany
| | - Alexander Jarasch
- Gene Center and Center for integrated Protein Science Munich, Department of Biochemistry, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany
| | - Andreas M. Anger
- Gene Center and Center for integrated Protein Science Munich, Department of Biochemistry, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany
| | - Elizabeth Villa
- Department of Molecular Structural Biology, Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Thomas Becker
- Gene Center and Center for integrated Protein Science Munich, Department of Biochemistry, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany
| | - Shashi Bhushan
- Gene Center and Center for integrated Protein Science Munich, Department of Biochemistry, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany
| | - Fabrice Jossinet
- Université de Strasbourg, Institut de Biologie Moléculaire et Cellulaire du Centre National de la Recherche Scientifique, 15 Rue René Descartes, 67084 Strasbourg, France
| | - Michael Habeck
- Department of Empirical Inference, Max Planck Institute for Biological Cybernetics, Spemannstrasse 38, 72076 Tübingen, Germany
- Department of Protein Evolution, Max Planck Institute for Developmental Biology, Spemannstrasse 35, 72076 Tübingen, Germany
| | - Gülcin Dindar
- Gene Center and Center for integrated Protein Science Munich, Department of Biochemistry, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany
| | - Sibylle Franckenberg
- Gene Center and Center for integrated Protein Science Munich, Department of Biochemistry, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany
| | - Viter Marquez
- Gene Center and Center for integrated Protein Science Munich, Department of Biochemistry, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany
| | - Thorsten Mielke
- UltraStrukturNetzwerk, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany
- Institut für Medizinische Physik und Biophysik, Charité, Ziegelstrasse 5-8, 10117 Berlin, Germany; and
| | - Michael Thomm
- Universität Regensburg, Lehrstuhl für Mikrobiologie, Universitätstrasse 31, 93053 Regensburg, Germany
| | - Otto Berninghausen
- Gene Center and Center for integrated Protein Science Munich, Department of Biochemistry, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany
| | - Birgitta Beatrix
- Gene Center and Center for integrated Protein Science Munich, Department of Biochemistry, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany
| | - Johannes Söding
- Gene Center and Center for integrated Protein Science Munich, Department of Biochemistry, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany
| | - Eric Westhof
- Université de Strasbourg, Institut de Biologie Moléculaire et Cellulaire du Centre National de la Recherche Scientifique, 15 Rue René Descartes, 67084 Strasbourg, France
| | - Daniel N. Wilson
- Gene Center and Center for integrated Protein Science Munich, Department of Biochemistry, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany
| | - Roland Beckmann
- Gene Center and Center for integrated Protein Science Munich, Department of Biochemistry, Ludwig-Maximilians-Universität München, Feodor-Lynen-Strasse 25, 81377 Munich, Germany
| |
Collapse
|
10
|
Trabuco LG, Villa E, Schreiner E, Harrison CB, Schulten K. Molecular dynamics flexible fitting: a practical guide to combine cryo-electron microscopy and X-ray crystallography. Methods 2009; 49:174-80. [PMID: 19398010 PMCID: PMC2753685 DOI: 10.1016/j.ymeth.2009.04.005] [Citation(s) in RCA: 256] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2009] [Revised: 04/03/2009] [Accepted: 04/04/2009] [Indexed: 11/26/2022] Open
Abstract
Hybrid computational methods for combining structural data from different sources and resolutions are becoming an essential part of structural biology, especially as the field moves toward the study of large macromolecular assemblies. We have developed the molecular dynamics flexible fitting (MDFF) method for combining high-resolution atomic structures with cryo-electron microscopy (cryo-EM) maps, that results in atomic models representing the conformational state captured by cryo-EM. The method has been applied successfully to the ribosome, a ribonucleoprotein complex responsible for protein synthesis. MDFF involves a molecular dynamics simulation in which a guiding potential, based on the cryo-EM map, is added to the standard force field. Forces proportional to the gradient of the density map guide an atomic structure, available from X-ray crystallography, into high-density regions of a cryo-EM map. In this paper we describe the necessary steps to set up, run, and analyze MDFF simulations and the software packages that implement the corresponding functionalities.
Collapse
Affiliation(s)
- Leonardo G. Trabuco
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Elizabeth Villa
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Eduard Schreiner
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Christopher B. Harrison
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Klaus Schulten
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| |
Collapse
|
11
|
Topf M, Lasker K, Webb B, Wolfson H, Chiu W, Sali A. Protein structure fitting and refinement guided by cryo-EM density. Structure 2008; 16:295-307. [PMID: 18275820 PMCID: PMC2409374 DOI: 10.1016/j.str.2007.11.016] [Citation(s) in RCA: 263] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2007] [Revised: 11/20/2007] [Accepted: 11/26/2007] [Indexed: 11/23/2022]
Abstract
For many macromolecular assemblies, both a cryo-electron microscopy map and atomic structures of its component proteins are available. Here we describe a method for fitting and refining a component structure within its map at intermediate resolution (<15 A). The atomic positions are optimized with respect to a scoring function that includes the crosscorrelation coefficient between the structure and the map as well as stereochemical and nonbonded interaction terms. A heuristic optimization that relies on a Monte Carlo search, a conjugate-gradients minimization, and simulated annealing molecular dynamics is applied to a series of subdivisions of the structure into progressively smaller rigid bodies. The method was tested on 15 proteins of known structure with 13 simulated maps and 3 experimentally determined maps. At approximately 10 A resolution, Calpha rmsd between the initial and final structures was reduced on average by approximately 53%. The method is automated and can refine both experimental and predicted atomic structures.
Collapse
Affiliation(s)
- Maya Topf
- School of Crystallography, Birkbeck College, University of London, Malet Street, London WC1E 7HX, United Kingdom.
| | | | | | | | | | | |
Collapse
|