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Scattering Methods in Structural Biology Part B, Volume 678 [Kietas viršelis]

Volume editor (Professor and Robert A. Welch Chair in Chemistry, Department of Molecular and Cellular Oncology, The University of Texas, USA)
  • Formatas: Hardback, 460 pages, aukštis x plotis: 229x152 mm, weight: 840 g
  • Serija: Methods in Enzymology
  • Išleidimo metai: 11-Jan-2023
  • Leidėjas: Academic Press Inc
  • ISBN-10: 0323991815
  • ISBN-13: 9780323991810
Kitos knygos pagal šią temą:
  • Formatas: Hardback, 460 pages, aukštis x plotis: 229x152 mm, weight: 840 g
  • Serija: Methods in Enzymology
  • Išleidimo metai: 11-Jan-2023
  • Leidėjas: Academic Press Inc
  • ISBN-10: 0323991815
  • ISBN-13: 9780323991810
Kitos knygos pagal šią temą:

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.

  • Provides the authority and expertise of leading contributors from an international board of authors
  • Presents the latest release in the Methods in Enzymology serial
  • Updated release includes the latest information on Small Angle Scattering Methods for Structural Interpretation
Contributors xi
Preface xv
1 Data quality assurance, model validation, and data sharing for biomolecular structures from small-angle scattering
1(22)
Jill Trewhella
1 Becoming a mainstream structural biology technique
2(2)
2 The path to standards and data sharing
4(4)
3 Draft publication guidelines and plans for data archiving
8(3)
4 A data archive for SAS as part of a federated system for integrative structural biology
11(1)
5 The current publication guidelines and data archiving requirements
11(4)
6 Quantifying data reproducibility and establishing a consensus experimental benchmark data set
15(1)
7 Future opportunities
16(1)
8 Conclusions
17(6)
Acknowledgments
17(1)
References
17(6)
2 Structure and ensemble refinement against SAXS data: Combining MD simulations with Bayesian inference or with the maximum entropy principle
23(32)
Leonie Chatzimagas
Jochen S. Hub
1 Introduction
24(3)
2 SAXS-driven molecular dynamics simulations
27(10)
3 SAXS-driven MD as a tool for Bayesian inference of molecular structures
37(4)
4 Maximum-entropy ensemble refinement against SAXS data
41(7)
5 Discussion: Conceptual considerations and recommendations
48(1)
6 Applications
49(1)
7 Summary
50(5)
Acknowledgments
51(1)
References
51(4)
3 Data analysis and modeling of small-angle neutron scattering data with contrast variation from bio-macromolecular complexes
55(42)
Andrew E. Whitten
Cy M. Jeffries
1 Introduction
56(3)
2 Analysis of the forward scattering intensity, 1(0), and calculation of contrast
59(8)
3 Analysis of the radius of gyration
67(7)
4 Composite scattering functions
74(4)
5 Dummy-atom (bead) modeling against contrast variation data
78(7)
6 Rigid body modeling against contrast variation data
85(6)
7 Summary
91(6)
Acknowledgments
92(1)
References
92(5)
4 Observing protein degradation in solution by the PAN-20S proteasome complex: Astate-of-the-art example of bio-macromolecular TR-SANS
97(24)
Frank Gabel
1 The interest of TR-SANS for dynamic bio-macromolecular systems
98(1)
2 Specific protein degradation in biological cells
99(4)
3 A concrete example of bio-macromolecular TR-SANS: Insight into structural dynamics of substrate processing by the archaeal PAN-proteasome system
103(1)
4 Sample conditions, instrumental setup and data reduction
104(2)
5 Experimental TR-SANS results and mechanistic model of protein degradation
106(9)
6 Conclusions and outlook
115(6)
Acknowledgments
117(1)
References
117(4)
5 Extracting structural insights from soft X-ray scattering of biological assemblies
121(24)
Sintu Rongpipi
Joshua T. Del Mundo
Enrique D. Gomez
Esther W. Gomez
1 Introduction
122(2)
2 Predicting RSoXS scattering contrast from NEXAFS spectra
124(5)
3 Reduction of RSoXS 2D data into 1D
129(3)
4 Interpretation of scattering data
132(4)
5 Identification of the real-space structure that leads to an observed scattering profile
136(2)
6 Opportunities for application of new RSoXS analysis approaches to biological assemblies
138(1)
7 Conclusion and outlook
139(6)
Acknowledgments
140(1)
References
140(5)
6 Reconstruction of 3D density from solution scattering
145(48)
Thomas D. Grant
1 Introduction
146(2)
2 Theory
148(10)
3 DENSS software
158(1)
4 Preparing the data with denss.fit_data.py
159(3)
5 Running a single reconstruction with denss.py
162(11)
6 Alignment and averaging
173(5)
7 Analysis and interpretation of results
178(4)
8 SANS
182(2)
9 Materials science applications
184(1)
10 Publication guidelines and SASBDB deposition
184(2)
11 Summary
186(7)
Acknowledgments
187(1)
Funding
187(1)
References
187(6)
7 Computational methods for the analysis of solution small-angle X-ray scattering of biomolecules: ATSAS
193(44)
Haydyn D.T. Mertens
1 Introduction
194(2)
2 Calculation and simulation of scattering data
196(9)
3 Primary data processing
205(8)
4 Structural modeling from SAXS data
213(18)
5 ATSAS summary
231(6)
References
231(6)
8 Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models
237(26)
Tomer Cohen
Matan Halfon
Lester Carter
Beth Sharkey
Tushar Jain
Arvind Sivasubramanian
Dina Schneidman-Duhovny
1 Introduction
238(3)
2 Materials and methods
241(7)
3 Results
248(7)
4 Protocol
255(1)
5 Discussion
256(7)
Acknowledgments
256(1)
References
257(6)
9 Combining NMR, SAXS and SANS to characterize the structure and dynamics of protein complexes
263(36)
Florent Delhommel
Santiago Marti'nez-Lumbreras
Michael Sattler
1 Introduction
264(2)
2 Sample preparation
266(3)
3 NMR spectroscopy
269(6)
4 Small angle X-ray and neutron scattering (SAXS/SANS)
275(4)
5 Integration of NMR and SAS
279(9)
6 Conclusions and future perspectives
288(11)
Acknowledgments
290(1)
References
290(9)
10 From dilute to concentrated solutions of intrinsically disordered proteins: Interpretation and analysis of collected data
299(32)
Samuel Lenton
Eric Fagerberg
Mark Tully
Marie Skepo
1 Introduction
300(3)
2 How to tell if a protein is an IDP?
303(2)
3 The conformational ensemble
305(6)
4 Ensemble optimization methods
311(3)
5 Special considerations for crowded IDP solutions
314(2)
6 Beyond analytical models
316(5)
7 General notes on the treatment of hydration layers of IDPs
321(2)
8 Summary and conclusions
323(8)
Acknowledgments
324(1)
References
324(7)
11 Applying HT-SAXS to chemical ligand screening
331(20)
Chris A. Brosey
Runze Shen
Davide Moiani
Darin E. Jones
Kathryn Burnett
Greg L. Hura
John A. Tainer
1 Introduction
332(1)
2 Considerations for SAXS target and library selection
333(4)
3 HT-SAXS sample preparation
337(1)
4 Benchmarking a pilot HT-SAXS screen
337(1)
5 Ligand screen design and assembly
338(4)
6 Analysis of HT-SAXS screening datasets
342(4)
7 Summary and future perspectives
346(5)
Simple Scattering deposition
347(1)
Acknowledgments
347(1)
References
348(3)
12 Combining small angle X-ray scattering (SAXS) with protein structure predictions to characterize conformations in solution
351(26)
Naga Babu Chinnam
Aleem Syed
Greg L. Hura
Michal Hammel
John A. Tainer
Susan E. Tsutakawa
1 Introduction
352(5)
2 Obtaining a protein structure prediction
357(3)
3 Prediction of SAXS curve from an atomic model
360(2)
4 Comparison of experimental and predicted SAXS curves
362(2)
5 Fitting of the protein structure prediction(s) to the experimental SAXS data
364(3)
6 Example: XRCC1 solution state
367(2)
7 Notes
369(1)
8 Summary and conclusions
370(7)
Acknowledgments
372(1)
References
372(5)
13 Protein fibrillation from another small angle--SAXS data analysis of developing systems
377(34)
Annette Eva Langkilde
Bente Vestergaard
1 Introduction
378(5)
2 General method notes
383(1)
3 Essential check of SAXS data from fibrillating systems
383(3)
4 Initial analysis of the background subtracted data
386(4)
5 Decomposition of data--Manual approach
390(5)
6 Decomposition of developing data using COSMiCS
395(4)
7 Further interpretation
399(5)
8 Alternative approaches
404(1)
9 Summary and conclusions
405(6)
Acknowledgments
406(1)
References
406(5)
14 Visualizing and accessing correlated SAXS data sets with Similarity Maps and Simple Scattering web resources
411
Daniel T. Murray
David S. Shin
Scott Classen
Chris A. Brosey
Greg L. Hura
1 Introduction
412(4)
2 Visualization of correlated SAXS data
416(14)
3 Simple Scattering data set repository
430(7)
4 Summary and outlook
437
Acknowledgments
438(1)
References
438
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 worlds 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.