Crystallography of Protein Dynamics / edited by Nozomi Ando.

Format:

Book

Contributor:

Ando, Nozomi, editor.

Series:

Methods in Enzymology Series

Methods in Enzymology Series ; v.Volume 688

Language:

English

Subjects (All):

Crystallography.

Proteins--Structure.

Proteins.

Physical Description:

1 online resource (0 pages)

Edition:

First edition.

Place of Publication:

Cambridge, MA : Academic Press, [2023]

Summary:

Approx.400 pagesApprox.400 pages.

Contents:

Front Cover

Series page

Title page

Copyright

Contents

Contributors

Preface

Chapter One: Introduction to diffuse scattering and data collection

1 Introduction

2 Theory

3 Samples for diffuse scattering

3.1 Crystallization and transport

3.2 Sample mounting

4 Experimental design

4.1 Beamline parameters

4.2 Data collection strategy

4.3 Background measurement

5 Data quality assessment

5.1 Examination of diffraction images

5.2 Quantifying and controlling radiation damage

5.3 Diffuse map quality assessment

6 Conclusions

Acknowledgments

References

Chapter Two: Processing macromolecular diffuse scattering dataProcessing macromolecular diffuse scattering data

1.1 Brief history of macromolecular diffuse scattering

1.2 Data processing software

2.1 Scattering geometry

2.2 Components of diffraction

2.3 Estimating and correcting errors

3 Data processing tutorial

3.1 Indexing and geometry refinement

3.1.1 Metadata import

3.1.2 Beamstop mask

3.1.3 Spotfinding

3.1.4 Indexing

3.1.5 Geometry refinement

3.1.6 Diagnostic statistics and plots

3.1.7 Background image metadata

3.2 Data exploration

3.2.1 Importing diffraction data

3.2.2 Importing diffraction geometry

3.2.3 Calculating a rocking curve in Python

3.3 Bragg peak masking

3.4 Background subtraction

3.5 Integration, scaling and merging

3.5.1 Integration

3.5.2 Scaling

3.5.3 Merging

3.6 Visualization

3.7 Map statistics

3.7.1 Intensity vs. resolution

3.7.2 Correlation of half-datasets

4 Conclusions

Appendix A

A.1. Obtaining and running the tutorial in Jupyter notebooks

A.2. Downloading the tutorial dataset

A.3. Setting up the python environment

A.4. Installing mdx2.

A.5. Installing DIALS, NeXpy, and JupyterLab

Chapter Three: Molecular-dynamics simulations of macromolecular diffraction, part I: Preparation of protein crystal simulationsMolecular-dynamics simulations of macromolecular diffraction, part I

2 Methods and discussion

2.1 Jupyter notebook

2.2 Preparing a structural model: Missing atoms and residues

2.3 Force fields: Choices and parametrization

2.4 The Computational Crystallography Toolbox (cctbx)

2.5 Expanding the system using the crystalline symmetry

2.6 Solvent modeling

2.7 Minimization

2.8 Adjusting the pressure via iterative solvation and equilibration

2.9 Harmonic restraints

2.10 Production simulation

3 Summary

Chapter Four: Molecular-dynamics simulations of macromolecular diffraction, part II: Analysis of protein crystal simulationsMolecular-dynamics simulations of macromolecular diffraction, part II

2.1 Jupyter notebooks

2.2 Preparation of the MD trajectory for analysis

2.3 Bragg analysis

2.3.1 Calculating mean structure factors and intensities from the MD trajectory

2.3.2 Using the MD structure factors to refine an MD structural model

2.3.3 MD simulation B-factors

2.3.4 Visualizing crystalline MD snapshots as ensembles of symmetry-related proteins

2.4 Diffuse analysis

2.4.1 Calculating diffuse scattering from an MD trajectory

2.4.2 Comparing the simulated and experimental diffuse intensities

2.4.3 Analysis of the covariance of atomic displacements from an MD trajectory

2.4.4 Associating covariance information with the LLM and RBM models of diffuse scattering

References.

Chapter Five: MD simulations of macromolecular crystals: Implications for the analysis of Bragg and diffuse scatteringMD simulations of macromolecular crystals

2 Brief summary of X-ray scattering in crystals

3 MD simulations of biomolecular crystals

3.1 Setup and equilibration

3.2 Common analysis tasks

3.2.1 Removing unit cell "drift"

3.2.2 Moving atoms into a principal asymmetric unit

3.2.3 Computing structure factors

3.3 Convergence of simulations

4 Bragg scattering and crystallographic refinement

4.1 Creating reference data sets

4.2 Geometry restraints and molecular force fields

4.3 Alternate conformers and ensembles

4.4 Dealing with disordered solvent

5 Diffuse scattering

5.1 Lattice vibrations

5.2 Internal contributions to diffuse scattering

Chapter Six: Modeling diffuse scattering with simple, physically interpretable models

2 Set up and resources

3 Modeling disorder

3.1 Models of biological dynamics

3.2 Models relevant to structure determination

3.3 Models of lattice dynamics

4 Model evaluation

5 Discussion

Code availability

Chapter Seven: Interpreting macromolecular diffraction through simulation

2 Present status and future prospects for diffuse scattering

2.1 Pixel array detectors

2.2 Space group and unit cell

2.3 Ambient temperature

3 Image simulation methods

4 Extending simulators to diffuse scattering

5 Complexity of the simulation

6 Parameter space and implications for simulation

6.1 Incident beam

6.2 Unit cell and symmetry

6.3 Crystal orientation

6.4 Mosaic character

6.5 Diffuse scattering

6.6 Oscillation width and rotation

6.7 Background and noise

7 Conclusions.

8 Software availability

Acknowledgements

Chapter Eight: Refinement of multiconformer ensemble models from multi-temperature X-ray diffraction dataRefinement of multiconformer ensemble models

2 Collection of multi-temperature X-ray diffraction data

2.1 Obtaining crystals for X-ray diffraction

2.2 Achieving high-temperature capabilities and temperature control

2.3 Diffraction data collection

2.4 Data processing

3 Single conformer model refinement

3.1 Molecular replacement

3.2 Initial model building

3.3 Iterative model refinement

3.4 Modeling an unknown ligand appearing at high temperatures

4 Multiconformer model refinement

4.1 Automatic refinement using qFit

4.2 Manual pruning and refinement

4.3 Automatic relabeling of structural segments

4.4 Modeling coupled conformational preferences

5 Identifying temperature-dependent conformational changes

5.1 Ringer analysis

6 Summary and conclusions

Chapter Nine: Combining temperature perturbations with X-ray crystallography to study dynamic macromolecules: A thorough discussion of experimental methods

2 Sample cryocooling in macromolecular crystallography

2.1 Cryocooling has become standard practice in macromolecular crystallography

2.2 Cryocooling can cause lattice distortions that lead to practical challenges

2.3 Cryocooling perturbs the structures of macromolecules

3 Non-cryogenic macromolecular crystallography

3.1 Modern hardware and software obviate the need for cryocooling

3.1.1 Breakthroughs in X-ray detector technology

3.1.2 Integration of weak reflection intensities with modern software

3.2 Practical considerations for non-cryogenic data collection

3.2.1 Sample preparation

3.2.2 Data collection.

3.2.3 Multi-crystal approaches and serial crystallography

3.3 Structural modeling with non-cryogenic data

4 Temperature as a tool for studying conformational heterogeneity and dynamics

4.1 Multi-temperature crystallography

4.1.1 Practical considerations for multi-temperature crystallography

4.1.2 Studying the conformational ensemble with multi-temperature crystallography

4.1.3 Examples of multi-temperature crystallography to study protein function

4.2 Time-resolved crystallography using temperature-jump

4.2.1 Infrared laser-induced temperature-jump

4.2.2 Practical considerations for T-jump crystallography experiments

4.2.3 Studying macromolecular dynamics with T-jump

5 Conclusion

Chapter Ten: Room temperature crystallography and X-ray spectroscopy of metalloenzymesRoom Temp XES and XRD

2 Sample preparation

2.1 Crystallization kinetics and phase diagram

2.2 Crystallization techniques

2.3 PSII purification and crystallization

2.3.1 Crystallization in microbatch plates

2.3.2 Microseeding procedure

2.3.3 Post-crystallization treatment

2.4 IPNS

3 Sample delivery system

3.1 Sample handling and loading

3.2 Sample infusion and ejection

3.3 Tape drive control

3.4 Delivering droplets to the XFEL beam

3.5 Peripherals

3.6 Reaction triggering

3.6.1 Photoactivation

3.6.2 O2-activation

4 XES data collection

5 XRD data collection

Chapter Eleven: Exploring the structural dynamics of proteins by pressure perturbation using macromolecular crystallographyStructural dynamics of proteins by pressure perturbation

2 Diamond anvil cell

3 Sample managing

4 DAC-based experiment

4.1 Pressure generation

4.2 Pressure measurement

4.3 Incident beam energy.

4.4 Sample loading.

Notes:

Description based on print version record.

Description based on publisher supplied metadata and other sources.

ISBN:

0-443-15926-2

0-443-15927-0

OCLC:

1401057865