Small angle scattering. Part B, Methods for structural interpretation / edited by John A. Tainer.

Format:

Book

Contributor:

Tainer, John, editor.

Series:

Methods in enzymology ; Volume 678.

Methods in enzymology ; Volume 678

Language:

English

Subjects (All):

Enzymology.

Molecular structure.

Small-angle scattering.

Physical Description:

1 online resource (462 pages)

Edition:

1st ed.

Place of Publication:

Cambridge, Massachusetts : Academic Press is an imprint of Elsevier, [2023]

Summary:

Scattering Methods in Structural Biology, Part B, Volume 676 in the Methods in Enzymology serial, highlights advances in the field, presenting chapters on Quality controls, Refining biomolecular structures and ensembles by SAXS-driven molecular dynamics simulations, Data analysis and modelling of small-angle scattering data with contrast.

Contents:

Intro

Small Angle Scattering Part B: Methods for Structural Interpretation

Copyright

Contents

Contributors

Preface

Chapter One: Data quality assurance, model validation, and data sharing for biomolecular structures from small-angle scat ...

1. Becoming a mainstream structural biology technique

2. The path to standards and data sharing

3. Draft publication guidelines and plans for data archiving

4. A data archive for SAS as part of a federated system for integrative structural biology

5. The current publication guidelines and data archiving requirements

6. Quantifying data reproducibility and establishing a consensus experimental benchmark data set

7. Future opportunities

8. Conclusions

Acknowledgments

References

Chapter Two: Structure and ensemble refinement against SAXS data: Combining MD simulations with Bayesian inference or wit ...

1. Introduction

2. SAXS-driven molecular dynamics simulations

2.1. Experiment-supported energetic bias

2.2. Increasing the computational efficiency by smoothing and re-binning the experimental curve

2.3. Accounting for systematic and calculated errors

2.4. On-the-fly averaging of the calculated SAXS curve

2.5. SAXS-derived forces applied during MD

2.6. Protocol A

3. SAXS-driven MD as a tool for Bayesian inference of molecular structures

3.1. Posterior, likelihood, and prior distributions

3.2. Bayesian treatment of systematic errors at small angles

3.3. Protocol B

4. Maximum-entropy ensemble refinement against SAXS data

4.1. Theoretical background

4.2. Parallel-replica ensemble refinement against SAXS data

4.3. Choosing the number of replicas

4.4. Protocol C

4.5. Example: Ensemble refinement of a detergent micelle

5. Discussion: Conceptual considerations and recommendations.

5.1. SAXS-driven MD simulations (should) feel only a weak bias by the SAXS data

5.2. Accelerating transitions with SAXS data and sampling limitations

5.3. Further analysis

6. Applications

7. Summary

Chapter Three: Data analysis and modeling of small-angle neutron scattering data with contrast variation from bio-macromo ...

2. Analysis of the forward scattering intensity, I(0), and calculation of contrast

2.1. Programs

2.2. Procedure

2.3. Notes

3. Analysis of the radius of gyration

3.1. Programs

3.2. Procedure

3.3. Notes

4. Composite scattering functions

4.1. Programs

4.2. Procedure

4.3. Notes

5. Dummy-atom (bead) modeling against contrast variation data

5.1. Programs

5.2. Procedure

5.3. Notes

6. Rigid body modeling against contrast variation data

6.1. Programs

6.2. Procedure

6.3. Notes

Chapter Four: Observing protein degradation in solution by the PAN-20S proteasome complex: Astate-of-the-art example of b ...

1. The interest of TR-SANS for dynamic bio-macromolecular systems

2. Specific protein degradation in biological cells

3. A concrete example of bio-macromolecular TR-SANS: Insight into structural dynamics of substrate processing by the arch ...

4. Sample conditions, instrumental setup and data reduction

5. Experimental TR-SANS results and mechanistic model of protein degradation

5.1. The PAN-GFP system

5.2. The PAN-20S-GFP system

5.3. A mechanistic model of protein degradation based on the TR-SANS results

6. Conclusions and outlook

Chapter Five: Extracting structural insights from soft X-ray scattering of biological assemblies

2. Predicting RSoXS scattering contrast from NEXAFS spectra.

2.1. Materials

3. Reduction of RSoXS 2D data into 1D

3.1. Materials

4. Interpretation of scattering data

4.1. Materials

5. Identification of the real-space structure that leads to an observed scattering profile

5.1. Materials

6. Opportunities for application of new RSoXS analysis approaches to biological assemblies

7. Conclusion and outlook

Chapter Six: Reconstruction of 3D density from solution scattering

1.1. History of modeling solution scattering data

1.2. Ab initio modeling

1.3. Ab initio density reconstruction

2. Theory

2.1. Iterative phase retrieval

2.2. Overview of DENSS iterative structure factor retrieval

2.3. Determination of object support using Shrinkwrap

2.4. Solvent considerations

2.5. Uniqueness

3. DENSS software

3.1. DENSS software suite

3.2. DENSS workflow

4. Preparing the data with denss.fit_data.py

5. Running a single reconstruction with denss.py

5.1. Overview of basic parameters and modes of denss.py

5.2. Assessing the quality of reconstructions

5.3. Advanced options

5.3.1. Symmetry averaging

5.3.2. Oversampling

5.3.3. Shrinkwrap options

5.3.4. Enforce connectivity

6. Alignment and averaging

6.1. Alignment

6.2. Averaging

6.3. Enantiomer selection

6.4. Resolution estimation

6.5. Refinement

7. Analysis and interpretation of results

7.1. Visualization

7.2. Comparison with atomic model

7.3. Advanced modeling using DENSS reconstructions

8. SANS

9. Materials science applications

10. Publication guidelines and SASBDB deposition

11. Summary

Funding

References.

Chapter Seven: Computational methods for the analysis of solution small-angle X-ray scattering of biomolecules: ATSAS

2. Calculation and simulation of scattering data

2.1. Computation of SAXS intensities and model fitting

2.2. Simulation of 2D SAXS intensities

3. Primary data processing

3.1. Primary data processing of 1D SAXS profiles/curves

3.1.1. Basic operations on 2D and 1D scattering data

3.1.2. Indirect Fourier transformation and the real-space distance distribution

3.1.3. Estimation of molecular weight of proteins from SAXS data

4. Structural modeling from SAXS data

4.1. Ab initio (shape) methods

4.1.1. Direct modeling from experimental data

4.1.2. Multiphase modeling of membrane proteins in solution

4.2. Hybrid modeling procedures

4.2.1. Rigid-body modeling

4.2.2. Flexible body modeling and ensembles

4.2.3. Quasi-atomistic modeling of membranes, detergents and membrane proteins

4.3. Polydisperse systems

4.3.1. Ab initio methods applied to polydisperse solutions

4.3.2. Modeling polydisperse solutions of lipid vesicles

5. ATSAS summary

Chapter Eight: Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models

2. Materials and methods

2.1. Software

2.2. Integrative modeling

2.2.1. Gathering information

2.2.2. Model representation

2.2.3. Sampling good-scoring models

2.2.4. Analyzing models and information

3. Results

4. Protocol

5. Discussion

Chapter Nine: Combining NMR, SAXS and SANS to characterize the structure and dynamics of protein complexes

2. Sample preparation

2.1. Sample requirements

2.2. Isotope labeling

3. NMR spectroscopy

3.1. Structural analysis.

3.2. Binding studies and domain interactions

3.3. Conformational dynamics

4. Small angle X-ray and neutron scattering (SAXS/SANS)

4.1. Structural information from SAXS

4.2. Contrast matching and structural analysis of subdomains from SANS

5. Integration of NMR and SAS

5.1. Validation of structural models in solution

5.2. Characterization of rigid and dynamic complexes

5.3. Rigid complexes

5.4. Ensembles of dynamic assemblies

6. Conclusions and future perspectives

Chapter Ten: From dilute to concentrated solutions of intrinsically disordered proteins: Interpretation and analysis of c ...

2. How to tell if a protein is an IDP?

3. The conformational ensemble

3.1. Determination of the size through the radius of gyration

3.2. Determination of size through the molecular mass

3.3. Determination of the shape through the pair distribution function

3.4. Determination of the shape through the Porod regime

3.5. Notes on the average conformational properties

4. Ensemble optimization methods

5. Special considerations for crowded IDP solutions

6. Beyond analytical models

6.1. Models for the simulation of IDPs

6.2. Simulation techniques

6.3. Simulations of the single IDP and SAXS-related analysis

6.4. Simulations of concentrated solutions of IDPs and SAXS-related analysis

7. General notes on the treatment of hydration layers of IDPs

8. Summary and conclusions

Chapter Eleven: Applying HT-SAXS to chemical ligand screening

2. Considerations for SAXS target and library selection

3. HT-SAXS sample preparation

4. Benchmarking a pilot HT-SAXS screen

5. Ligand screen design and assembly

6. Analysis of HT-SAXS screening datasets

7. Summary and future perspectives.

Simple Scattering deposition.

Notes:

Description based on print version record.

Description based on publisher supplied metadata and other sources.

Other Format:

Print version: Tainer, John Scattering Methods in Structural Biology Part B

ISBN:

9780323991827

OCLC:

1492939948