1. Rigid body matching/fitting in intermediate- low resolution density Agnel Praveen Joseph STFC, Harwell

2. Sample classigication Taxonomy Pfam domains (fitted models) Uniprot ID (text search/Pfam link) Alignment scores, transformation matrix Web-serverDatabase User’s query map/ New Entry User’s query PDB/ New Entry Data organisation & annotation (Work along with the data submission pipeline at EMDB/PDBe and as a development for CCP-EM)

3. Methods Density based 6D search : Fast Translational Matching (COLORES) : Fast Fourier Transform (FFT) driven translational search at each rotation (Chacon and Wriggers, 2002). Cross correlation scores with or without Laplacian filters, are used for matching Author test cases: Simulated maps down to 34Å resolution were used, and correct alignments were obtained down to 25Å resolution using Laplacian correlation filter. Components of microtubule were also assembled successfully in a 20Å experimental map. Fast Rotational Matching (ADP-EM,) : Spherical Harmonics accelerated rotational search at each translation (Garzon et al. 2007, Kovacs et al. 2003). Cross correlation scores with or without Laplacian filters, are used for matching Author test cases: Simulated maps of down to 30Å were used for testing and accurate results were obtained even at 30Å resolution, using higher harmonic bandwidth values. Fitting components on a 23Å experimental map was also successful. Random Sampling (CHIMERA,ModEM): Randomly sample rotation and translation space (Goddard et al. 2007, Topf et al.2005). Overlap and correlation based scores are used for matching. http://3dem.ucsd.edu/SI_Table1_ver2.pdf Villa and Lasker, Finding the right fit: chiseling structures out of cryo-electron microscopy mapsCurr Opin Struct Biol. 2014

4. Reduced representation : Gaussian Mixture Model (GMFIT): Linear combination of N 3D gaussian density (Kawabata, 2008). A gaussian overlap metric is used to score the alignment. Author test cases: With the right choice of the number of GDFs, correct alignments were obtained using simulated maps down to 30Å resolution. Tests on a 23.5Å experimental map also gave ‘near- native’ alignment with respect to a reference. FoldEM : Local density gradients are described as orthogonal feature vectors which are rotationally invariant (represented as vectors covering a set of neighboring grid points: Local Region Descriptors). Graphs are constructed with these descriptors as nodes and a graph-matching technique is applied to detect the maximal sub-graph. The size of the common sub-graph is returned as the score, along with an atom inclusion score from Chimera (Pettersen et al., 2004). Author test cases: Tests were carried out with simulated EM maps down to 20Å resolution and correct fits were obtained with resolutions down to 15Å. Comparison of 11Å ribosome (experimental) maps in two conformational states also gave a good alignment. Methods

5. GMfit Number of 3D gaussians used to approximate the density/model depends on the number of local features/components. Both map and model needs to be converted into gaussian mixture models prior to matching EMD-1056, E-coli 70S, 9ÅEMD-2017, E-coli 30S, 13.5ÅAlignment of gaussian mixtures

6. ADP-EM Spherical harmonics are an infinite set of harmonic functions defined on the sphere. The basis functions are indexed according to two integer constants, the order, l, and the degree, m. As the number of coefficients increases, higher frequency signals can be approximated more accurately. The two arguments l and m break the family of polynomials into bands of functions Option of laplacian filter for gradient detection

7. Atomic structure modeling and processing  If experimentatly determined structures are not available: Fold recognition and Homology modeling  Remove flexible loops. Separate compact domains connected by a hinge/flexible loop.  Check if sub-complexes can be modelled 2631/4umm : 11.6Å cryo-EM structure of palindromic DNA bound USP/EcR nuclear receptor Maletta et al. The palindromic DNA-bound USP/EcR nuclear receptor adopts an asymmetric organization with allosteric domain positioning. Nat comm 2014

8. A case: 1534/2y7c/2y7h 18Å EcoK1 methyltransferase with a bound antirestriction protein T7 phage antirestriction protein ocr ROSETTA(http://robetta. bakerlab.org/) ab-inito model HsdS-ocr complex modeled using guided multi-body docking by HADDOCK (http://haddock.science.uu.nl/services/ HADDOCK2.2/haddock.php) HsdM HsdS

9. Volume processing Shift background peak to zero Some scores to measure fit quality are sensitive to scale of data values e.g: overlap and correlation (not about mean) metrics in Chimera use sum of products of density values. Select a contour threshold Usually subjective. Can be calculated from molecular weight of sample. Calculations on a subset from EMDB shows a peak at 2 sigma A higher contour may be considered for local weak density regions: Contour level suggested by authors (EMD- 5287, 26Å).

10. Search space Probe/target size ratio should be considered unless you are using an exhaustive search method. Target map should be segmented to increase probe/target(segment) size ratio. Gmfit: Random sampling (-I R), segmentation (-I SF) and symmetry based search (-I Y) options are available. adp_em: masking search (-s 2, default): the translational space is limited to positions on which the dimension of the probe (atomic structure) roughly fits inside the experimental EM map. radial search (-s 1): more uniform and useful for structures with holes. exhaustive search (-s 0) Chimera parameter : search N (number of random configurations)

11. Translation and rotation Sampling Depends on resolution/grid spacing – coarse sampling for low resolution maps Size of probe : finer rotation sampling for a larger probe adp_em : higher bandwidth - finer rotational sampling and more accurate harmonic description. 16 default. Bandwidth values correspond to 360/(2*B) degrees of rotation. translational sampling in Å: -t (one/two voxel steps)

12. Try different methods: An example EMD-2631 For intermediate/low resolution fitting: Multiple methods might have to be tried Different solutions might have to be checked (for those that are structurally stable, functionally relevant and supported by experiments) Multiple scores might be required to re-rank the solutions : surface/envelope matching scores are especially useful at low resolutions. TUTORIAL

13. /scratch/ccpem_tutorial/apj_tutorial_22_04/exa mples/2631 module load chimera module load adp_em module load gmfit module load gmconvert

14. Volume matching pipeline (ccp-EM/EMDB-PDBe)

15. Current version under development Database of EMDB volume alignments and PDB model – EMDB volume comparisons (fitting) Web service and software for volume-volume and model- volume alignments Web service to search user model/map in EMDB for similar volumes, volumes from certain taxa and sample categories. Web service and software for 3D analysis of alignments, map feature representations (gaussian mixtures, points), calculate difference maps. Annotation (sequence/interactions/taxonomy) of entries in EMDB

16. Volume pre-processing Feature points Contoured density Gaussian mixture Dusting Segmentation 424.8Å

17. Scores (TEMPy) TEMPy (Farabella et al.) scores used for re-ranking hits obtained. Global scores are influenced by non uniform noise, interpolation and padding effects. Local scores used - maps need to be contoured prior to calculations. If the resolution of the map is very low to be informative (density variation) – Envelope/Surface based scores may be useful. Local cross-correlation, Local mutual information, surface distance score and Overlap score are used for re-ranking solutions

18. Examples E-coli 70S ribosome: 9Å vs E-coli 30S ribosome: 13.5Å Methanococcus maripaludis Mm-cpn chaperone: 4.9Å vs E-coli GroEL/GroES (mut) chaperone: 9.2Å Human Echovirus 12: 16Å vs Human Coxsackievirus A21: 8Å

19. Surface definitions based on a given contour: Partial surface overlap detection 22.0Å Dengue virus9Å 70S E coli vs 6.6Å 80S yeast Surface feature extraction Surface point definitions

20. Release Test version of volume matching software is available at: http://www.ccpem.ac.uk/download.php http://www.ccpem.ac.uk/download.php – Currently full functionalities are not included: multiple scores, user map input, more methods to be added (adp_em, shapeEM) – Fully functional version should be released in the next few months. Web service (EMDB/PDBe) will be also available in the next few months will all functionalities

21. Martyn Winn Maya Topf Ardan Patwardhan Ingvar Lagerstedt Thank You