Scattering Methods in Structural Biology Part B

1st Edition, Volume 678 - January 11, 2023
Imprint: Academic Press
Editor: John Tainer
Language: English
Hardback ISBN:
9 7 8 - 0 - 3 2 3 - 9 9 1 8 1 - 0
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 9 1 8 2 - 7

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, Refin… Read more

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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 variation, Observing protein degradation in solution by the PAN-20S proteasome complex: state-of-the-art and future perspectives of TR-SANS as a complementary tool to NMR, crystallography and Cryo-EM, Extracting structural insights from chemically-specific soft X-ray scattering, Reconstruction of 3D density of biological macromolecules from solution scattering, ATSAS- present state and new developments in computational methods, and much more.

Additional chapters cover Modeling Structure and Dynamics of Protein Complexes with SAXS Profiles (FoXSDock and MultiFoXS), Validation of macromolecular flexibility in solution by SAXS, Combining NMR, SAXS and SANS to characterize the structure and dynamics of protein complexes, Application of Molecular Simulation Methods to Analyze SAS Data, and more.

Cover image
Title page
Table of Contents
Copyright
Contributors
Preface
Chapter One: Data quality assurance, model validation, and data sharing for biomolecular structures from small-angle scattering
Abstract
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 with the maximum entropy principle
Abstract
1: Introduction
2: SAXS-driven molecular dynamics simulations
3: SAXS-driven MD as a tool for Bayesian inference of molecular structures
4: Maximum-entropy ensemble refinement against SAXS data
5: Discussion: Conceptual considerations and recommendations
6: Applications
7: Summary
References
Chapter Three: Data analysis and modeling of small-angle neutron scattering data with contrast variation from bio-macromolecular complexes
Abstract
1: Introduction
2: Analysis of the forward scattering intensity, I(0), and calculation of contrast
3: Analysis of the radius of gyration
4: Composite scattering functions
5: Dummy-atom (bead) modeling against contrast variation data
6: Rigid body modeling against contrast variation data
7: Summary
Acknowledgments
References
Chapter Four: Observing protein degradation in solution by the PAN-20S proteasome complex: Astate-of-the-art example of bio-macromolecular TR-SANS
Abstract
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 archaeal PAN-proteasome system
4: Sample conditions, instrumental setup and data reduction
5: Experimental TR-SANS results and mechanistic model of protein degradation
6: Conclusions and outlook
Acknowledgments
References
Chapter Five: Extracting structural insights from soft X-ray scattering of biological assemblies
Abstract
1: Introduction
2: Predicting RSoXS scattering contrast from NEXAFS spectra
3: Reduction of RSoXS 2D data into 1D
4: Interpretation of scattering data
5: Identification of the real-space structure that leads to an observed scattering profile
6: Opportunities for application of new RSoXS analysis approaches to biological assemblies
7: Conclusion and outlook
Acknowledgments
References
Chapter Six: Reconstruction of 3D density from solution scattering
Abstract
1: Introduction
2: Theory
3: DENSS software
4: Preparing the data with denss.fit_data.py
5: Running a single reconstruction with denss.py
6: Alignment and averaging
7: Analysis and interpretation of results
8: SANS
9: Materials science applications
10: Publication guidelines and SASBDB deposition
11: Summary
References
Chapter Seven: Computational methods for the analysis of solution small-angle X-ray scattering of biomolecules: ATSAS
Abstract
1: Introduction
2: Calculation and simulation of scattering data
3: Primary data processing
4: Structural modeling from SAXS data
5: ATSAS summary
References
Chapter Eight: Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models
Abstract
1: Introduction
2: Materials and methods
3: Results
4: Protocol
5: Discussion
Acknowledgments
References
Chapter Nine: Combining NMR, SAXS and SANS to characterize the structure and dynamics of protein complexes
Abstract
1: Introduction
2: Sample preparation
3: NMR spectroscopy
4: Small angle X-ray and neutron scattering (SAXS/SANS)
5: Integration of NMR and SAS
6: Conclusions and future perspectives
Acknowledgments
References
Chapter Ten: From dilute to concentrated solutions of intrinsically disordered proteins: Interpretation and analysis of collected data
Abstract
1: Introduction
2: How to tell if a protein is an IDP?
3: The conformational ensemble
4: Ensemble optimization methods
5: Special considerations for crowded IDP solutions
6: Beyond analytical models
7: General notes on the treatment of hydration layers of IDPs
8: Summary and conclusions
Acknowledgments
References
Chapter Eleven: Applying HT-SAXS to chemical ligand screening
Abstract
1: Introduction
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
Acknowledgments
References
Chapter Twelve: Combining small angle X-ray scattering (SAXS) with protein structure predictions to characterize conformations in solution
Abstract
1: Introduction
2: Obtaining a protein structure prediction
3: Prediction of SAXS curve from an atomic model
4: Comparison of experimental and predicted SAXS curves
5: Fitting of the protein structure prediction(s) to the experimental SAXS data
6: Example: XRCC1 solution state
7: Notes
8: Summary and conclusions
Acknowledgments
References
Chapter Thirteen: Protein fibrillation from another small angle—SAXS data analysis of developing systems
Abstract
1: Introduction
2: General method notes
3: Essential check of SAXS data from fibrillating systems
4: Initial analysis of the background subtracted data
5: Decomposition of data—Manual approach
6: Decomposition of developing data using COSMiCS
7: Further interpretation
8: Alternative approaches
9: Summary and conclusions
Acknowledgments
References
Chapter Fourteen: Visualizing and accessing correlated SAXS data sets with Similarity Maps and Simple Scattering web resources
Abstract
1: Introduction
2: Visualization of correlated SAXS data
3: Simple Scattering data set repository
4: Summary and outlook
Acknowledgments
References

John Tainer

Prof. John A. Tainer trained in X-ray crystallography, biochemistry, and computation. With this foundation, he contributed to structural biochemistry for the biology for DNA repair, reactive oxygen control, the immune response, and other stress responses for >20 years. His NCI-funded papers report robust structural and biophysical measurements to advance understanding of cellular stress responses that are evolutionarily conserved and important in preserving genome stability and preventing diseases in humans. His methods, results, and concepts have stood the test of time: they are often used and cited >30,000 total times. At Scripps, Prof. Tainer created and ran the Scripps NSF Computational Center for Macromolecular Structure along with an NIH P01 on Metalloprotein Structure and Design. He also helped develop and utilize the Scripps share of the NSF San Diego Supercomputer Center. At LBL, he developed and directed the ~$2.9 million/year DOE Program “Molecular Assemblies Genes and Genomics Integrated Efficiently” (MAGGIE) from 2004-2011. At Berkeley, Prof. Tainer designed, developed, and directed the world’s only dual endstation synchrotron beamline SIBYLS (Structurally Integrated BiologY for Life Sciences), used by >200 NIH labs. This unique technology integrates high flux small angle x-ray scattering (SAXS) and macromolecular X-ray crystallography (MX). At SIBYLS his lab develop, optimize, and apply technologies to determine accurate structures, conformations and assemblies both in solution and at high resolution. His lab defined an R-factor gap in MX revealing an untapped potential for insights on nanoscale structures by better modeling of bound solvent and flexible regions. At the University of Texas MD Anderson Cancer Center, Prof. Tainer is joining biochemistry and biophysics to fluorescent imaging measures of protein and RNA interactions on DNA for mechanistic insights. He is integrating these data with cryo-EM, MX and SAXS structures by linking MD Anderson and SIBYLS facilities. As an originator of applying proteins from thermophiles to defining dynamic structures and functional conformations, Prof. Tainer develop methods for measurements on structures including conformations, and assemblies in solution. Prof. Tainer has combined cryo-EM and X-ray structures with biochemistry to define functional assemblies. His lab introduced new equations for analyzing X-ray scattering for flexible macromolecules and complexes. His lab also defined a novel SAXS invariant: the first discovered since the Porod invariant ~60 years ago. The defined parameters quantitatively assess flexibility, measure intermolecular distances, determine data to model agreement, and reduce false positives. Prof. Tainer has a track record of successful collaborations, completing projects, sharing innovating approaches and technologies, developing insights along with new structural data, and providing fundamentally important technologies that improve the ways others do their research. He has benefited from continuous peer-reviewed NCI funding since 1999. NCI support has allowed Prof. Tainer to develop expertise in the methods development and in the structural biology of DNA repair, immune responses, and other stress.

Affiliations and expertise

Professor and Robert A. Welch Chair in Chemistry, Department of Molecular and Cellular Oncology, The University of Texas, USA

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Scattering Methods in Structural Biology Part B

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