1
|
Joseph AP, Lagerstedt I, Patwardhan A, Topf M, Winn M. Improved metrics for comparing structures of macromolecular assemblies determined by 3D electron-microscopy. J Struct Biol 2017; 199:12-26. [PMID: 28552721 PMCID: PMC5479444 DOI: 10.1016/j.jsb.2017.05.007] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2016] [Revised: 05/19/2017] [Accepted: 05/23/2017] [Indexed: 11/28/2022]
Abstract
Recent developments in 3-dimensional electron microcopy (3D-EM) techniques and a concomitant drive to look at complex molecular structures, have led to a rapid increase in the amount of volume data available for biomolecules. This creates a demand for better methods to analyse the data, including improved scores for comparison, classification and integration of data at different resolutions. To this end, we developed and evaluated a set of scoring functions that compare 3D-EM volumes. To test our scores we used a benchmark set of volume alignments derived from the Electron Microscopy Data Bank. We find that the performance of different scores vary with the map-type, resolution and the extent of overlap between volumes. Importantly, adding the overlap information to the local scoring functions can significantly improve their precision and accuracy in a range of resolutions. A combined score involving the local mutual information and overlap (LMI_OV) performs best overall, irrespective of the map category, resolution or the extent of overlap, and we recommend this score for general use. The local mutual information score itself is found to be more discriminatory than cross-correlation coefficient for intermediate-to-low resolution maps or when the map size and density distribution differ significantly. For comparing map surfaces, we implemented two filters to detect the surface points, including one based on the 'extent of surface exposure'. We show that scores that compare surfaces are useful at low resolutions and for maps with evident surface features. All the scores discussed are implemented in TEMPy (http://tempy.ismb.lon.ac.uk/).
Collapse
Affiliation(s)
- Agnel Praveen Joseph
- Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck College, University of London, Malet Street, London WC1E 7HX, United Kingdom; Scientific Computing Department, Science and Technology Facilities Council, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom
| | - Ingvar Lagerstedt
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom; Computational Chemistry and Cheminformatics, Lilly UK, Windlesham GU20 6PH, United Kingdom
| | - Ardan Patwardhan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Maya Topf
- Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck College, University of London, Malet Street, London WC1E 7HX, United Kingdom.
| | - Martyn Winn
- Scientific Computing Department, Science and Technology Facilities Council, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom.
| |
Collapse
|
2
|
Rakesh R, Srinivasan N. Improving the Accuracy of Fitted Atomic Models in Cryo-EM Density Maps of Protein Assemblies Using Evolutionary Information from Aligned Homologous Proteins. Methods Mol Biol 2016; 1415:193-209. [PMID: 27115634 DOI: 10.1007/978-1-4939-3572-7_10] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Cryo-Electron Microscopy (cryo-EM) has become an important technique to obtain structural insights into large macromolecular assemblies. However the resolution of the density maps do not allow for its interpretation at atomic level. Hence they are combined with high resolution structures along with information from other experimental or bioinformatics techniques to obtain pseudo-atomic models. Here, we describe the use of evolutionary conservation of residues as obtained from protein structures and alignments of homologous proteins to detect errors in the fitting of atomic structures as well as improve accuracy of the protein-protein interfacial regions in the cryo-EM density maps.
Collapse
Affiliation(s)
- Ramachandran Rakesh
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, 560012, India
| | | |
Collapse
|
3
|
Borkotoky S, Meena CK, Khan MW, Murali A. Three dimensional electron microscopy and in silico tools for macromolecular structure determination. EXCLI JOURNAL 2013; 12:335-46. [PMID: 27092033 PMCID: PMC4827587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2013] [Accepted: 04/14/2013] [Indexed: 12/02/2022]
Abstract
Recently, structural biology witnessed a major tool - electron microscopy - in solving the structures of macromolecules in addition to the conventional techniques, X-ray crystallography and nuclear magnetic resonance (NMR). Three dimensional transmission electron microscopy (3DTEM) is one of the most sophisticated techniques for structure determination of molecular machines. Known to give the 3-dimensional structures in its native form with literally no upper limit on size of the macromolecule, this tool does not need the crystallization of the protein. Combining the 3DTEM data with in silico tools, one can have better refined structure of a desired complex. In this review we are discussing about the recent advancements in three dimensional electron microscopy and tools associated with it.
Collapse
Affiliation(s)
- Subhomoi Borkotoky
- Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry-605014, India
| | - Chetan Kumar Meena
- Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry-605014, India
| | - Mohammad Wahab Khan
- Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry-605014, India
| | - Ayaluru Murali
- Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry-605014, India,*To whom correspondence should be addressed: Ayaluru Murali, Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry-605014, India, E-mail:
| |
Collapse
|
4
|
Whitford PC, Blanchard SC, Cate JHD, Sanbonmatsu KY. Connecting the kinetics and energy landscape of tRNA translocation on the ribosome. PLoS Comput Biol 2013; 9:e1003003. [PMID: 23555233 PMCID: PMC3605090 DOI: 10.1371/journal.pcbi.1003003] [Citation(s) in RCA: 68] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2012] [Accepted: 02/04/2013] [Indexed: 12/27/2022] Open
Abstract
Functional rearrangements in biomolecular assemblies result from diffusion across an underlying energy landscape. While bulk kinetic measurements rely on discrete state-like approximations to the energy landscape, single-molecule methods can project the free energy onto specific coordinates. With measures of the diffusion, one may establish a quantitative bridge between state-like kinetic measurements and the continuous energy landscape. We used an all-atom molecular dynamics simulation of the 70S ribosome (2.1 million atoms; 1.3 microseconds) to provide this bridge for specific conformational events associated with the process of tRNA translocation. Starting from a pre-translocation configuration, we identified sets of residues that collectively undergo rotary rearrangements implicated in ribosome function. Estimates of the diffusion coefficients along these collective coordinates for translocation were then used to interconvert between experimental rates and measures of the energy landscape. This analysis, in conjunction with previously reported experimental rates of translocation, provides an upper-bound estimate of the free-energy barriers associated with translocation. While this analysis was performed for a particular kinetic scheme of translocation, the quantitative framework is general and may be applied to energetic and kinetic descriptions that include any number of intermediates and transition states.
Collapse
Affiliation(s)
- Paul C Whitford
- Department of Physics, Northeastern University, Boston, Massachusetts, United States of America.
| | | | | | | |
Collapse
|
5
|
de Vries SJ, Zacharias M. ATTRACT-EM: a new method for the computational assembly of large molecular machines using cryo-EM maps. PLoS One 2012; 7:e49733. [PMID: 23251350 PMCID: PMC3522670 DOI: 10.1371/journal.pone.0049733] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2012] [Accepted: 10/17/2012] [Indexed: 11/23/2022] Open
Abstract
Many of the most important functions in the cell are carried out by proteins organized in large molecular machines. Cryo-electron microscopy (cryo-EM) is increasingly being used to obtain low resolution density maps of these large assemblies. A new method, ATTRACT-EM, for the computational assembly of molecular assemblies from their components has been developed. Based on concepts from the protein-protein docking field, it utilizes cryo-EM density maps to assemble molecular subunits at near atomic detail, starting from millions of initial subunit configurations. The search efficiency was further enhanced by recombining partial solutions, the inclusion of symmetry information, and refinement using a molecular force field. The approach was tested on the GroES-GroEL system, using an experimental cryo-EM map at 23.5 Å resolution, and on several smaller complexes. Inclusion of experimental information on the symmetry of the systems and the application of a new gradient vector matching algorithm allowed the efficient identification of docked assemblies in close agreement with experiment. Application to the GroES-GroEL complex resulted in a top ranked model with a deviation of 4.6 Å (and a 2.8 Å model within the top 10) from the GroES-GroEL crystal structure, a significant improvement over existing methods.
Collapse
Affiliation(s)
- Sjoerd J de Vries
- Physik-Department T38, Technische Universität München, Garching, Germany.
| | | |
Collapse
|
6
|
Saha M, Morais MC. FOLD-EM: automated fold recognition in medium- and low-resolution (4-15 Å) electron density maps. ACTA ACUST UNITED AC 2012; 28:3265-73. [PMID: 23131460 DOI: 10.1093/bioinformatics/bts616] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
MOTIVATION Owing to the size and complexity of large multi-component biological assemblies, the most tractable approach to determining their atomic structure is often to fit high-resolution radiographic or nuclear magnetic resonance structures of isolated components into lower resolution electron density maps of the larger assembly obtained using cryo-electron microscopy (cryo-EM). This hybrid approach to structure determination requires that an atomic resolution structure of each component, or a suitable homolog, is available. If neither is available, then the amount of structural information regarding that component is limited by the resolution of the cryo-EM map. However, even if a suitable homolog cannot be identified using sequence analysis, a search for structural homologs should still be performed because structural homology often persists throughout evolution even when sequence homology is undetectable, As macromolecules can often be described as a collection of independently folded domains, one way of searching for structural homologs would be to systematically fit representative domain structures from a protein domain database into the medium/low resolution cryo-EM map and return the best fits. Taken together, the best fitting non-overlapping structures would constitute a 'mosaic' backbone model of the assembly that could aid map interpretation and illuminate biological function. RESULT Using the computational principles of the Scale-Invariant Feature Transform (SIFT), we have developed FOLD-EM-a computational tool that can identify folded macromolecular domains in medium to low resolution (4-15 Å) electron density maps and return a model of the constituent polypeptides in a fully automated fashion. As a by-product, FOLD-EM can also do flexible multi-domain fitting that may provide insight into conformational changes that occur in macromolecular assemblies.
Collapse
Affiliation(s)
- Mitul Saha
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, 301 University Boulevard, Galveston, TX 7555-0647, USA.
| | | |
Collapse
|
7
|
Henderson R, Sali A, Baker ML, Carragher B, Devkota B, Downing KH, Egelman EH, Feng Z, Frank J, Grigorieff N, Jiang W, Ludtke SJ, Medalia O, Penczek PA, Rosenthal PB, Rossmann MG, Schmid MF, Schröder GF, Steven AC, Stokes DL, Westbrook JD, Wriggers W, Yang H, Young J, Berman HM, Chiu W, Kleywegt GJ, Lawson CL. Outcome of the first electron microscopy validation task force meeting. Structure 2012; 20:205-14. [PMID: 22325770 PMCID: PMC3328769 DOI: 10.1016/j.str.2011.12.014] [Citation(s) in RCA: 361] [Impact Index Per Article: 30.1] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2011] [Revised: 12/29/2011] [Accepted: 12/29/2011] [Indexed: 11/10/2022]
Abstract
This Meeting Review describes the proceedings and conclusions from the inaugural meeting of the Electron Microscopy Validation Task Force organized by the Unified Data Resource for 3DEM (http://www.emdatabank.org) and held at Rutgers University in New Brunswick, NJ on September 28 and 29, 2010. At the workshop, a group of scientists involved in collecting electron microscopy data, using the data to determine three-dimensional electron microscopy (3DEM) density maps, and building molecular models into the maps explored how to assess maps, models, and other data that are deposited into the Electron Microscopy Data Bank and Protein Data Bank public data archives. The specific recommendations resulting from the workshop aim to increase the impact of 3DEM in biology and medicine.
Collapse
Affiliation(s)
- Richard Henderson
- MRC Laboratory of Molecular Biology, Hills Road, Cambridge CB2 0QH, UK
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
8
|
Xu M, Beck M, Alber F. Template-free detection of macromolecular complexes in cryo electron tomograms. ACTA ACUST UNITED AC 2011; 27:i69-76. [PMID: 21685103 PMCID: PMC3117359 DOI: 10.1093/bioinformatics/btr207] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Motivation: Cryo electron tomography (CryoET) produces 3D density maps of biological specimen in its near native states. Applied to small cells, cryoET produces 3D snapshots of the cellular distributions of large complexes. However, retrieving this information is non-trivial due to the low resolution and low signal-to-noise ratio in tomograms. Current pattern recognition methods identify complexes by matching known structures to the cryo electron tomogram. However, so far only a small fraction of all protein complexes have been structurally resolved. It is, therefore, of great importance to develop template-free methods for the discovery of previously unknown protein complexes in cryo electron tomograms. Results: Here, we have developed an inference method for the template-free discovery of frequently occurring protein complexes in cryo electron tomograms. We provide a first proof-of-principle of the approach and assess its applicability using realistically simulated tomograms, allowing for the inclusion of noise and distortions due to missing wedge and electron optical factors. Our method is a step toward the template-free discovery of the shapes, abundance and spatial distributions of previously unknown macromolecular complexes in whole cell tomograms. Contact:alber@usc.edu Supplementary information:Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Min Xu
- Program in Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | | | | |
Collapse
|
9
|
Vasishtan D, Topf M. Scoring functions for cryoEM density fitting. J Struct Biol 2011; 174:333-43. [PMID: 21296161 DOI: 10.1016/j.jsb.2011.01.012] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2010] [Revised: 01/22/2011] [Accepted: 01/31/2011] [Indexed: 10/18/2022]
Abstract
In fitting atomic structures into cryoEM density maps of macromolecular assemblies, the cross-correlation function (CCF) is the most prevalent method of scoring the goodness-of-fit. However, there are still many possible, less studied ways of scoring fits. In this paper, we introduce four scores new to cryoEM fitting and compare their performance to three known scores. Our benchmark consists of (a) 4 protein assemblies with simulated maps at 5-20 Å resolution, including the heptameric ring of GroEL; and (b) 4 experimental maps of GroEL at ∼6-23 Å resolution with corresponding fitted atomic models. We perturb each fit 1000 times and assess each new fit with each score. The correlation between a score and the Cα RMSD of each fit from the "correctly" fitted structure shows that the CCF is one of the best scores, but in certain situations could be augmented or even replaced by other scores. For instance, our implementation of a score based on mutual information outperforms or is comparable to the CCF in almost all test cases, and our new "envelope score" works as well as the CCF at sub-nanometer resolution but is an order of magnitude faster to calculate. The results also suggest that the width of the Gaussian function used to blur the atomic structure into a density map can significantly affect the fitting process. Finally, we show that our score-testing method, when combined with the Laplacian CCF or the mutual information scores, can be used as a statistical tool for improving cryoEM density fitting.
Collapse
Affiliation(s)
- Daven Vasishtan
- Institute of Structural and Molecular Biology, Crystallography, Department of Biological Sciences, Birkbeck College, University of London, London WC1E7HX, UK
| | | |
Collapse
|