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.
1. Cover image - p. i 2. Title page - p. ii 3. Table of Contents - p. iii 4. Series Page - p. iii 5. Copyright - p. iii 6. Contributors - p. iii 7. Preface - p. xv 8. Chapter One: Data quality assurance, model validation, and data sharing for biomolecular structures from small-angle scattering - p. 5 9. Chapter Two: Structure and ensemble refinement against SAXS data: Combining MD simulations with Bayesian inference or with the maximum entropy principle - p. 23 10. Chapter Three: Data analysis and modeling of small-angle neutron scattering data with contrast variation from bio-macromolecular complexes - p. 55 11. Chapter Four: Observing protein degradation in solution by the PAN-20S proteasome complex: Astate-of-the-art example of bio-macromolecular TR-SANS - p. 97 12. Chapter Five: Extracting structural insights from soft X-ray scattering of biological assemblies - p. 121 13. Chapter Six: Reconstruction of 3D density from solution scattering - p. 145 14. Chapter Seven: Computational methods for the analysis of solution small-angle X-ray scattering of biomolecules: ATSAS - p. 193 15. Chapter Eight: Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models - p. 237 16. Chapter Nine: Combining NMR, SAXS and SANS to characterize the structure and dynamics of protein complexes - p. 263 17. Chapter Ten: From dilute to concentrated solutions of intrinsically disordered proteins: Interpretation and analysis of collected data - p. 299 18. Chapter Eleven: Applying HT-SAXS to chemical ligand screening - p. 331 19. Chapter Twelve: Combining small angle X-ray scattering (SAXS) with protein structure predictions to characterize conformations in solution - p. 351 20. Chapter Thirteen: Protein fibrillation from another small angle—SAXS data analysis of developing systems - p. 377 21. Chapter Fourteen: Visualizing and accessing correlated SAXS data sets with Similarity Maps and Simple Scattering web resources - p. 411
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.
1. Cover image - p. i 2. Title page - p. ii 3. Table of Contents - p. iii 4. Series Page - p. iii 5. Copyright - p. iii 6. Contributors - p. iii 7. Preface - p. xv 8. Chapter One: Data quality assurance, model validation, and data sharing for biomolecular structures from small-angle scattering - p. 5 9. Chapter Two: Structure and ensemble refinement against SAXS data: Combining MD simulations with Bayesian inference or with the maximum entropy principle - p. 23 10. Chapter Three: Data analysis and modeling of small-angle neutron scattering data with contrast variation from bio-macromolecular complexes - p. 55 11. Chapter Four: Observing protein degradation in solution by the PAN-20S proteasome complex: Astate-of-the-art example of bio-macromolecular TR-SANS - p. 97 12. Chapter Five: Extracting structural insights from soft X-ray scattering of biological assemblies - p. 121 13. Chapter Six: Reconstruction of 3D density from solution scattering - p. 145 14. Chapter Seven: Computational methods for the analysis of solution small-angle X-ray scattering of biomolecules: ATSAS - p. 193 15. Chapter Eight: Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models - p. 237 16. Chapter Nine: Combining NMR, SAXS and SANS to characterize the structure and dynamics of protein complexes - p. 263 17. Chapter Ten: From dilute to concentrated solutions of intrinsically disordered proteins: Interpretation and analysis of collected data - p. 299 18. Chapter Eleven: Applying HT-SAXS to chemical ligand screening - p. 331 19. Chapter Twelve: Combining small angle X-ray scattering (SAXS) with protein structure predictions to characterize conformations in solution - p. 351 20. Chapter Thirteen: Protein fibrillation from another small angle—SAXS data analysis of developing systems - p. 377 21. Chapter Fourteen: Visualizing and accessing correlated SAXS data sets with Similarity Maps and Simple Scattering web resources - p. 411
