Low-Resolution Structures of Proteins in Solution Retrieved from X-Ray Scattering with a Genetic Algorithm  P. Chacón, F. Morán, J.F. Díaz, E. Pantos,

Slides:



Advertisements
Similar presentations
Analysis and Evaluation of Channel Models: Simulations of Alamethicin
Advertisements

Philippe Derreumaux, Tamar Schlick  Biophysical Journal 
Fiona E. Müllner, Sheyum Syed, Paul R. Selvin, Fred J. Sigworth 
Three-Dimensional Structure of the Human DNA-PKcs/Ku70/Ku80 Complex Assembled on DNA and Its Implications for DNA DSB Repair  Laura Spagnolo, Angel Rivera-Calzada,
Vishwanath Jogini, Benoît Roux  Biophysical Journal 
Toshiro Oda, Keiichi Namba, Yuichiro Maéda  Biophysical Journal 
Maxim V. Petoukhov, Dmitri I. Svergun  Biophysical Journal 
Molecular Dynamics Simulation Analysis of Membrane Defects and Pore Propensity of Hemifusion Diaphragms  Manami Nishizawa, Kazuhisa Nishizawa  Biophysical.
Volume 94, Issue 5, Pages (March 2008)
Mechanism of the Lamellar/Inverse Hexagonal Phase Transition Examined by High Resolution X-Ray Diffraction  Michael Rappolt, Andrea Hickel, Frank Bringezu,
Β-Hairpin Folding Mechanism of a Nine-Residue Peptide Revealed from Molecular Dynamics Simulations in Explicit Water  Xiongwu Wu, Bernard R. Brooks  Biophysical.
Volume 80, Issue 1, Pages (January 2001)
Alfonso Jaramillo, Shoshana J. Wodak  Biophysical Journal 
Molecular Dynamics Free Energy Calculations to Assess the Possibility of Water Existence in Protein Nonpolar Cavities  Masataka Oikawa, Yoshiteru Yonetani 
Refolding of a High Molecular Weight Protein: Salt Effect on Collapse
Theory and Simulation of Water Permeation in Aquaporin-1
Carlos R. Baiz, Andrei Tokmakoff  Biophysical Journal 
How Does Protein Architecture Facilitate the Transduction of ATP Chemical-Bond Energy into Mechanical Work? The Cases of Nitrogenase and ATP Binding-Cassette.
A Consistent Experimental and Modeling Approach to Light-Scattering Studies of Protein-Protein Interactions in Solution  D. Asthagiri, A. Paliwal, D.
Γ-TEMPy: Simultaneous Fitting of Components in 3D-EM Maps of Their Assembly Using a Genetic Algorithm  Arun Prasad Pandurangan, Daven Vasishtan, Frank.
Seung Joong Kim, Charles Dumont, Martin Gruebele  Biophysical Journal 
Frank Alber, Michael F. Kim, Andrej Sali  Structure 
Volume 106, Issue 6, Pages (March 2014)
Marcelo Nöllmann, Jiuya He, Olwyn Byron, W.Marshall Stark 
Christopher B. Stanley, Tatiana Perevozchikova, Valerie Berthelier 
Large-Scale Conformational Dynamics of the HIV-1 Integrase Core Domain and Its Catalytic Loop Mutants  Matthew C. Lee, Jinxia Deng, James M. Briggs, Yong.
Monika Sharma, Alexander V. Predeus, Nicholas Kovacs, Michael Feig 
A Comparison of Genotype-Phenotype Maps for RNA and Proteins
Coarse-Grained Molecular Dynamics Simulations of Phase Transitions in Mixed Lipid Systems Containing LPA, DOPA, and DOPE Lipids  Eric R. May, Dmitry I.
Coarse-Grained Peptide Modeling Using a Systematic Multiscale Approach
Greta Faccio, Stefan Salentinig  Biophysical Journal 
Volume 83, Issue 2, Pages (August 2002)
Analysis and Evaluation of Channel Models: Simulations of Alamethicin
Carlos R. Baiz, Andrei Tokmakoff  Biophysical Journal 
G. Fiorin, A. Pastore, P. Carloni, M. Parrinello  Biophysical Journal 
A Molecular Dynamics Study of Ca2+-Calmodulin: Evidence of Interdomain Coupling and Structural Collapse on the Nanosecond Timescale  Craig M. Shepherd,
Volume 83, Issue 2, Pages (August 2002)
Volume 84, Issue 6, Pages (June 2003)
Volume 96, Issue 7, Pages (April 2009)
Ligand Binding to the Voltage-Gated Kv1
Volume 103, Issue 2, Pages (July 2012)
Validating Solution Ensembles from Molecular Dynamics Simulation by Wide-Angle X- ray Scattering Data  Po-chia Chen, Jochen S. Hub  Biophysical Journal 
Comparative Studies of Microtubule Mechanics with Two Competing Models Suggest Functional Roles of Alternative Tubulin Lateral Interactions  Zhanghan.
Molecular Dynamics Study of the KcsA Potassium Channel
Alfonso Jaramillo, Shoshana J. Wodak  Biophysical Journal 
Grischa R. Meyer, Justin Gullingsrud, Klaus Schulten, Boris Martinac 
Volume 103, Issue 5, Pages (September 2012)
Structural Flexibility of CaV1. 2 and CaV2
Tsuyoshi Terakawa, Shoji Takada  Biophysical Journal 
Volume 111, Issue 1, Pages (July 2016)
Molecular Mechanism for Stabilizing a Short Helical Peptide Studied by Generalized- Ensemble Simulations with Explicit Solvent  Yuji Sugita, Yuko Okamoto 
A Flexible Approach to the Calculation of Resonance Energy Transfer Efficiency between Multiple Donors and Acceptors in Complex Geometries  Ben Corry,
Areas of Monounsaturated Diacylphosphatidylcholines
Small Angle X-Ray Scattering Studies and Modeling of Eudistylia vancouverii Chlorocruorin and Macrobdella decora Hemoglobin  Angelika Krebs, Helmut Durchschlag,
Accurate Flexible Fitting of High-Resolution Protein Structures to Small-Angle X-Ray Scattering Data Using a Coarse-Grained Model with Implicit Hydration.
Γ-TEMPy: Simultaneous Fitting of Components in 3D-EM Maps of Their Assembly Using a Genetic Algorithm  Arun Prasad Pandurangan, Daven Vasishtan, Frank.
Volume 111, Issue 11, Pages (December 2016)
Yoshiteru Yonetani, Hidetoshi Kono  Biophysical Journal 
Volume 113, Issue 12, Pages (December 2017)
Gydo C.P. van Zundert, Adrien S.J. Melquiond, Alexandre M.J.J. Bonvin 
Mechanism of Interaction between the General Anesthetic Halothane and a Model Ion Channel Protein, III: Molecular Dynamics Simulation Incorporating a.
Alexander Spaar, Christian Münster, Tim Salditt  Biophysical Journal 
Kevin McHale, Andrew J. Berglund, Hideo Mabuchi  Biophysical Journal 
Jochen Zimmer, Declan A. Doyle, J. Günter Grossmann 
Volume 94, Issue 12, Pages (June 2008)
Patrick J. Fleming, Karen G. Fleming  Biophysical Journal 
Quantitative Modeling and Optimization of Magnetic Tweezers
Distribution of Halothane in a Dipalmitoylphosphatidylcholine Bilayer from Molecular Dynamics Calculations  Laure Koubi, Mounir Tarek, Michael L. Klein,
Volume 15, Issue 6, Pages (June 2007)
Molecular Dynamics Simulation of a Synthetic Ion Channel
Presentation transcript:

Low-Resolution Structures of Proteins in Solution Retrieved from X-Ray Scattering with a Genetic Algorithm  P. Chacón, F. Morán, J.F. Díaz, E. Pantos, J.M. Andreu  Biophysical Journal  Volume 74, Issue 6, Pages 2760-2775 (June 1998) DOI: 10.1016/S0006-3495(98)77984-6 Copyright © 1998 The Biophysical Society Terms and Conditions

Figure 1 Scheme of implementation of the genetic algorithm method of SAXS simulation to numerically solve the inverse scattering problem. Biophysical Journal 1998 74, 2760-2775DOI: (10.1016/S0006-3495(98)77984-6) Copyright © 1998 The Biophysical Society Terms and Conditions

Figure 2 (A) Representation of the search performance with different dimensions of the initial object, for the βb2-crystallin fragment. The fitness parameter F (see Materials and Methods) of the best member of the population is plotted versus the number of generations of the genetic algorithm. Solid line, performance of the method with an initial search model formed by 102 beads. Dashed line, 154 beads; dotted line, 254 beads; long dashed line, 736 beads; dash-dotted line, 64 beads. Note that as the dimension increases, the performance of the search decreases. Note as well how with the 64 bead search space there is no optimization, because the search space does not contain the problem structure. The bead model I corresponds to the best start model in the randomly generated initial population, and model II is the local minimum in which the algorithm falls with an initial object formed by 736 beads. Model III is the same final best-fit model at which the algorithm arrived with initial models made of 102, 154, or 254 beads. (B) An example of mask strategy with the same test object. The result of successively increasing resolution by creating a new search space with smaller beads (an envelope to the previous best-fit model) can be observed. N is the number of beads of each initial object for each of the three runs of the algorithm, and R is the bead radius. Biophysical Journal 1998 74, 2760-2775DOI: (10.1016/S0006-3495(98)77984-6) Copyright © 1998 The Biophysical Society Terms and Conditions

Figure 3 Calculated and fitted scattering profiles for the known protein structures of (A) βb2-crystallin (2bb2.pdb), (B) γ-crystallin (4grc.pdb), (C) ribonuclease inhibitor (1bnh.pdb), (D) lysozyme (6lyz.pdb), and (E) two molecules of lysozyme (1rcm.pdb). Solid lines: synthetic profiles calculated from each pdb file with the program DALAI (Pantos et al., 1996; hydrogen atoms and water molecules have not been taken into account). Points (circles), DALAI_GA simulated profiles. Dotted lines, synthetic profiles with added noise. Dashed lines, corresponding simulated profiles. A CPK view of the problem structure is shown in the upper right part of each panel, and the best fitted bead models are shown below it. (F) The numbers of beads N in models with different bead radii are plotted versus the anhydrous molecular masses of the problem structures. The corresponding linear regression parameters (N=a+bMr) are a=0.497, b=1.13×10−3, r=0.998; a=1.151, b=3.0×10−3, r=0.996; a=−8.70, b=20.66×10−3, r=0.974 for bead radii of 6, 4, and 2Å, respectively. Data include those from the models derived from scattering profiles with and without noise (A–F) and similar experiments with lactoferrin (1lfd.pdb, Mr 76,000). Biophysical Journal 1998 74, 2760-2775DOI: (10.1016/S0006-3495(98)77984-6) Copyright © 1998 The Biophysical Society Terms and Conditions

Figure 4 Bead models obtained from synthetic SAXS solution profiles in comparison with the known protein x-ray crystal structures. To get a reasonably good comparative display, the PDB structures are in a ribbon peptide chain and wireframe side-chain representation (yellow), and the models are displayed as a dotted Connolly surface (blue; probe radius 4.00Å) generated from the sphere model with Insight II (version 95.0). Note that the comparison of each pair of high-low-resolution structures is not a simple task, and has to be made using graphic tools for molecular representation. In this work we have manually overlaid the structures; the automation of this procedure is an open problem. The proteins modeled are (A) the βb2-crystallin fragment and (B) the same with noise added to the SAXS profile; (C) γ-crystallin and (D) the same with noise; (E) pancreatic ribonuclease inhibitor and (F) the same with noise. In each panel the left view has been rotated 90° in the x and y axes to generate the center and right views, respectively. The bars indicate 20Å. Biophysical Journal 1998 74, 2760-2775DOI: (10.1016/S0006-3495(98)77984-6) Copyright © 1998 The Biophysical Society Terms and Conditions

Figure 5 Experimental (solid line) and simulated SAXS profile (dots) of lysozyme. The best fit bead model (2-Å bead radius) is shown. The molecular mass values estimated for lysozyme from models with 6, 4, and 2Å bead radius, employing the linear regression shown in Fig. 3 F, are 15,400, 18,200, and 17,500, respectively. Biophysical Journal 1998 74, 2760-2775DOI: (10.1016/S0006-3495(98)77984-6) Copyright © 1998 The Biophysical Society Terms and Conditions

Figure 6 Bead models (blue) obtained from SAXS solution data of lysozyme in comparison with the x-ray crystal structure (yellow). The structures are represented as in Fig. 4. (A) Model derived from the calculated SAXS profile to 0.06 A−1; (B) same with noise added to profile; (C) model obtained from the calculated profile limited to 0.03 A−1. D shows the model derived from the experimental SAXS profile of lysozyme to 0.03 A−1 (Fig. 5), in six different projections. The bar indicates 20Å. Biophysical Journal 1998 74, 2760-2775DOI: (10.1016/S0006-3495(98)77984-6) Copyright © 1998 The Biophysical Society Terms and Conditions