Standards for hybrid and integrative methods Jill Trewhella, The University of Sydney Structural & biophysical methods for biological macromolecules in solution Sungkyunkwan University, Suwon Korea, June 19-26, 2016
SAS as a constraint in hybrid modelling Challenge of validation of hybrid models SAXS/NMR and SAXS/docking – demonstrably successful hybrid marriages The different regions of the SAS curve and what we need to pay attention to Accurate molecular mass determination as an important validation step; different methods Current state of draft publication guidelines The SAS Biological Data Base (SASBDB)
3D modeling from SAS (especially SAXS) data is becoming automated wwPDB SAStf Meeting report, Trewhella et al, Structure 21 , 875, 2013 a global repository is needed that holds standard format SAS data that is searchable and freely accessible for download; criteria need to be agreed upon for assessment of the quality of deposited SAS data and the accuracy of SAS-derived models, as well as the extent to which a given model fits the SAS data; increasing diversity of structural biology data and models calls for archiving options for models derived from diverse data; and need for definition of what to archive in the PDB and what complementary archives might be needed (taking into account both scientific needs and funding). wwPDB SAS task force
Outcome of the First wwPDB Hybrid / Integrative Methods Task Force Workshop (at EBI UK, Oct. 2014) A. Sali, H.M. Berman, T. Schwede, J. Trewhella, G. Kleywegt, S. K. Burley, J. Markley, H. Nakamura, P. Adams, A.M.J.J. Bonvin , W. Chiu, M. Dal Peraro, F. Di Maio, T.E. Ferrin, K. Grünewald, A. Gutmanas, R. Henderson, G. Hummer, K. Iwasaki, G. Johnson, C.L. Lawson, J. Meiler, M.A. Marti-Renom, G.T. Montelione, M. Nilges, R. Nussinov, A. Patwardhan, J. Rappsilber, R.J. Read, H. Saibil, G.F. Schröder, C. Schwieters, C.A.M. Seidel, D. Svergun, M. Topf, E.L. Ulrich, S. Velankar, and J.D. Westbrook Structure 23 , 1156-1167, 2015 Models with all relevant experimental data and metadata, as well as experimental and computational protocols should be archived; inclusivity is key. A flexible model representation needs to be developed, allowing for multi-scale models, multi-state models, ensembles of models, and models related by time or other order. Procedures for estimating the uncertainty of integrative models should be developed, validated, and adopted. A federated system of model and data archives should be created. Publication standards for integrative models should be established.
Structural information Method X-ray/neutron Xtalography, NMR, 3DEM, comparative modeling, Atomic structures of components molecular docking 3D maps and 2D images Electron microscopy and tomography NMR, FRET, DEER, EPR, other spectroscopic techniques; chemical crosslinks/mass spectrometry, disulfide bonds/ gel Atomic and protein distances electrophoresis Binding site mapping NMR spectroscopy, mutagenesis, FRET SAS Size, shape, P ( r ) Atomic force microscopy, ion mobility mass spec., fluorescence Shape and size correlation spectroscopy and fluorescence anisotropy Component positions Super-resolution optical microscopy, FRET imaging Co-purification, native mass spectrometry, genetic methods, Physical proximity and gene/protein sequence covariance Footprinting methods, e.g. H/D exchange by mass spec. or Solvent accessibility NMR, functional consequences of point mutations Proximity of genome segments Chromosome Conformation Capture and other data Propensities for different interaction Molecular mechanics force fields, potentials of mean force, modes statistical potentials, and sequence co-variation
Comparison of structures for 82 kDa Malate Synthase G from NMR-only data and joint fit of SAXS-NMR data NMR only SAXS-NMR 3.05 NMR 1.01 Xtal 0.97 NMR/SAXS NMR/SAXS refinement improves backbone rmsd values with respect to the crystal structure from 4.5 to 3.3 Å, largely due to more accurate translational positioning of domains The mid- q scattering range had most influence Grishaev et al. J.Biomol. NMR 376 , 95, 2008
SAS/NMR co-refinement has been fully implemented in Xplor-NIH Implemented for both X-ray and neutron scattering Test examples for proteins, DNA and flexible systems detailed in: Schwieters and Clore (2014) Using small- angle solution scattering data in Xplor-NIH structure calacutions. Prog. Nucl. Magn. Reson. Spectrosc. 80 , 1-11
Lysozyme example Figure 2: Schwieters and Clore (2014) Prog. Nucl. Magn. Reson. Spectrosc. 80 , 1 Red lines depict backbone coordinates of the lowest energy 10 structures calculated omitting SAXS/WAXS data (Panel A) and including SAXS/WAXS data (panel B). Blue cartoon is representation of the X-ray structure from PDB ID 193L.
Figure 3 from Schwieters and Clore (2014) Prog. Nucl. Magn. Reson. Spectrosc. 80 , 1. Comparison of SAXS/WAXS curves for lysozyme. Panels depicting the agreement to experiment of the SAXS/WAXS curves associated with the 10 lowest energy structures calculated without (panel A) and with (panel B) SAXS/WAXS data, respectively. The experimental data is shown in black with gray vertical bars equal to 1 SD; the curves calculated from the simulated annealing structures are shown in red. The residuals, given by, are plotted above each panel.
Structure statistics for 10 lowest energy lysozyme structures w and w/o SAXS all NMR data deposited NMR X-ray structures 1E8L structure without SAXS with SAXS (model 49) NOE violations 4.3 ±2.5 0.2 ±0.4 0.0±0.0 0 RDC R-factor, medium 1% 9.9 ±1.5 5.9 ±0.3 5.9±0.3 13.3 RDC R-factor, medium 2% 13.8 ±2.4 9.2 ±0.8 5.7±0.4 15.2 dihedral violations 4.4 ±1.2 0.1 ±0.3 0.0±0.2 0 SAXS χ 2 2.3 ±1.4 0.4±0.1 1.7±0.6 0.86 HBDB energy (kcal/mol) 116.4 ±18.8 −160.7 ±13.3 −45.6 ± 9.1 (−36.2) −255.12 torsion DB violations 3.8 ±2.6 1.4 ±1.5 1.7±0.9 (2) 0 bond violations 6.5 ±5.2 0.4 ±0.8 0.0±0.0 0 angle violations 8.6 ±5.9 0.1 ±0.3 10.3±0.8 (10) 48 improper violations 3.1 ±2.7 0.0±0.0 0.0±0.0 24 bad non-bonded contacts 21.2 ±7.5 2.7 ±1.8 166.5±7.8 (176) 48 precision to mean (Å) 2.30±0.58 0.84±0.14 0.50±0.13 − precision to mean (Å) 2.78±0.56 1.50±0.14 0.52±0.20 1.46 C rmsd to X-ray struct. (Å) 2.82±0.59 1.32±0.19 1.48±0.10 (1.46) −
SAS improves the performance of docking methods, e.g.: pyDock, Jimenez-Garciaet al. (2015) Nucleic Acids Res 2015 43, W356. FoXSDock, Schneidman-Duhovny et al. (2013) Biophys J 105, 962 HADDOCK, Karaca & Bonvin (2013) Acta Crystallogr D69 , 683 Using a common set of 70 benchmark cases, success rates for combined docking and SAXS were: 43% for pyDOCK, 48% for HADDOCK 63% for FoXSDock compared with 23% when only SAXS data were used. Schneidman-Duhovny et al. (2012) BMC Struct Biol 12, 17
Regions of the scattering curve Size shape surface q
Guinier Plot R g and I (0) shape and size Log I ( q ) q 2 I ( q ) Kratky Plot foldedness q 2 (Å -2 ) q (Å -1 ) Porod Plot volume P ( r ) q 4 I ( q ) r (Å) q (Å -1 )
Lysozyme SAXS Data Effects of more and less subtle inter- particle interference & aggregation Jacques & Trewhella (2010) Protein Science 19 , 642
Determining the size of the scattering particle: from I (0) 𝐽 𝑟 = 𝑂 Δ 𝜍𝑊 2 𝑄 𝑟 𝑇(𝑟) For non-interacting particles and 𝑟 = 0 ( i.e. 𝑇 𝑟 & 𝑄 0 are 1 ) 𝜍𝑊 2 = 𝐷∆𝜍 2 𝐽 0 = 𝑂 ∆ 𝜑 2 𝑁 Where: C is the concentration in g/cm 3 𝜑 is the partial specific volume in cm 3 /g M is the mass of the particle in g I (0) is in cm -1 Note: Doubling the concentration of the scattering particles will double the intensity, while doubling the size will quadruple the intensity.
Multiplication of the mass M r by Avergadros number yields the molecular mass of the scattering particle: 𝑁 𝑠 = 𝐽 0 𝑂 𝐵 𝐷∆𝜍 2 𝜑 2 Data can be placed on an absolute scale using the well- characterised scattering of water (for both X-rays* and neutrons) This method requires an accurate concentration determination *Orthaber et al. (2000) J. Appl. Cryst. 33 , 218
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