An overview of algorithms important to computational structural biology that addresses such topics as NMR and design and analysis of proteins.
Using the tools of information technology to understand the molecular machinery of the cell offers both challenges and opportunities to computational scientists. Over the past decade, novel algorithms have been developed both for analyzing biological data and for synthetic biology problems such as protein engineering. This book explains the algorithmic foundations and computational approaches underlying areas of structural biology including NMR (nuclear magnetic resonance); X-ray crystallography; and the design and analysis of proteins, peptides, and small molecules. Each chapter offers a concise overview of important concepts, focusing on a key topic in the field. Four chapters offer a short course in algorithmic and computational issues related to NMR structural biology, giving the reader a useful toolkit with which to approach the fascinating yet thorny computational problems in this area. A recurrent theme is understanding the interplay between biophysical experiments and computational algorithms. The text emphasizes the mathematical foundations of structural biology while maintaining a balance between algorithms and a nuanced understanding of experimental data. Three emerging areas, particularly fertile ground for research students, are highlighted- NMR methodology, design of proteins and other molecules, and the modeling of protein flexibility. The next generation of computational structural biologists will need training in geometric algorithms, provably good approximation algorithms, scientific computation, and an array of techniques for handling noise and uncertainty in combinatorial geometry and computational biophysics. This book is an essential guide for young scientists on their way to research success in this exciting field.
By:
Bruce R. Donald (Professor Duke University)
Imprint: MIT Press
Country of Publication: United States
Dimensions:
Height: 229mm,
Width: 203mm,
Weight: 454g
ISBN: 9780262548793
ISBN 10: 0262548798
Series: Computational Molecular Biology
Pages: 464
Publication Date: 15 August 2023
Recommended Age: From 18 years
Audience:
College/higher education
,
Primary
Format: Paperback
Publisher's Status: Active
Preface xxiii Acknowledgments xxxi 1 Introduction to Protein Structure and NMR 1 2 Basic Principles of NMR 7 3 Proteins and NMR Structural Biology 15 4 MBM, SVD, PCA, and RDCs 23 5 Principal Components Analysis, Residual Dipolar Couplings, and Their Relationship in NMR Structural Biology 27 6 Orientational Structures of Native and Denatured Proteins Using RDCs 53 7 Solution Structures of Native and Denatured Proteins Using RDCs 53 8 JIGSAW and NMR 59 9 Peptide Design 67 10 Protein Interface and Active Site Redesign 77 11 Computational Protein Design 87 12 Nonribosomal Code and K* Algorithms for Ensemble-Based Protein Design 97 13 RDCs in NMR Structural Biology 115 14 Nuclear Vector Replacement 119 15-18 Short Course: Automated NMR Assignment and Protein Structure Determination Using Sparse Residual Dipolar Couplings 127 19 Proteomic Disease Classification Algorithm 187 20 Protein Flexibility: Introduction to Inverse Kinematics and the Loop Closure Problem 191 21 Normal Mode Analysis (NMA) and Rigidity Theory 197 22 ROCK and FRODA for Protein Flexibility 205 23 Applications of NMA to Protein-Protein and Ligand-Protein Binding 213 24 Modeling Equilibrium Fluctuations in Proteins 219 25 Generalized Belief Propagation, Free Energy Approximations, and Protein Design 227 26 Ligand Configurational Entropy 245 27 Carrier Protein Structure and Recognition in Peptide Biosynthesis 249 28 Kinetic Studies of the Initial Module PheATE of Gramicidin S Synthetase 253 29 Protein-Ligand NOE Matching 259 30 Side-Chain and Backbone Flexibility in Protein Core Design 265 31 Distance Geometry 273 32 Distance Geometry: NP-Hard, NP-Hard to Approximate 279 33 A Topology-Constrained Network Algorithm for NOESY Data Interpretation 285 34 MARS: An Algorithm for Backbone Resonance Assignment 293 35 Errors in Structure Determination by NMR Spectroscopy 301 36 SemiDefinite Programming and Distance Geometry with Orientation Constraints 307 37 Graph Cuts for Energy Minimization and Assignment Problems 315 38 Classifying the Power of Graph Cuts for Energy Minimization 323 39 Protein Unfolding by Using Residual Dipolar Couplings 333 40 Structure-Based Protein-Ligand Binding 341 41 Flexible Ligand-Protein Docking 345 42 Analyzing Protein Structures Using and Ensemble Representation 351 43 NMR Resonance Assignment Assisted by Mass Spectrometry 355 44 Autolink: An Algorithm for Automated NMR Resonance Assignment 363 45 CS-Rosetta: Protein Structure Generalization from NMR Chemical Shift Data 371 46 Enzyme Redesign by SVM 377 47 Cross-Rotation Analysis Algorithm 383 48 Molecular Replacement and NCS in X-ray Crystallography 387 49 Optimization of Surface Charge-Charge Interactions 393 50 Computational Topology and Protein Structure 399 Index 415
Bruce R. Donald is William and Sue Gross Professor of Computer Science at Duke University and Professor of Biochemistry in the Duke University Medical Center. His laboratory is associated with Duke's Program in Computational Biology and Institute for Genome Sciences and Policy.
