{"product_id":"algorithms-in-structural-molecular-biology-isbn-9780262548793","title":"Algorithms in Structural Molecular Biology","description":"\u003cb\u003eAn overview of algorithms important to computational structural biology that addresses such topics as NMR and design and analysis of proteins.\u003c\/b\u003eUsing 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.\u003cbr\u003eEach 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.\u003cbr\u003eThe 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.Preface xxiii\u003cbr\u003eAcknowledgments xxxi\u003cbr\u003e1 Introduction to Protein Structure and NMR 1\u003cbr\u003e2 Basic Principles of NMR 7\u003cbr\u003e3 Proteins and NMR Structural Biology 15\u003cbr\u003e4 MBM, SVD, PCA, and RDCs 23\u003cbr\u003e5 Principal Components Analysis, Residual Dipolar Couplings, and Their Relationship in NMR Structural Biology 27\u003cbr\u003e6 Orientational Structures of Native and Denatured Proteins Using RDCs 53\u003cbr\u003e7 Solution Structures of Native and Denatured Proteins Using RDCs 53\u003cbr\u003e8 JIGSAW and NMR 59\u003cbr\u003e9 Peptide Design 67\u003cbr\u003e10 Protein Interface and Active Site Redesign 77\u003cbr\u003e11 Computational Protein Design 87\u003cbr\u003e12 Nonribosomal Code and K* Algorithms for Ensemble-Based Protein Design 97\u003cbr\u003e13 RDCs in NMR Structural Biology 115\u003cbr\u003e14 Nuclear Vector Replacement 119\u003cbr\u003e15-18 Short Course: Automated NMR Assignment and Protein Structure Determination Using Sparse Residual Dipolar Couplings 127\u003cbr\u003e19 Proteomic Disease Classification Algorithm 187\u003cbr\u003e20 Protein Flexibility: Introduction to Inverse Kinematics and the Loop Closure Problem 191\u003cbr\u003e21 Normal Mode Analysis (NMA) and Rigidity Theory 197\u003cbr\u003e22 ROCK and FRODA for Protein Flexibility 205\u003cbr\u003e23 Applications of NMA to Protein-Protein and Ligand-Protein Binding 213\u003cbr\u003e24 Modeling Equilibrium Fluctuations in Proteins 219\u003cbr\u003e25 Generalized Belief Propagation, Free Energy Approximations, and Protein Design 227\u003cbr\u003e26 Ligand Configurational Entropy 245\u003cbr\u003e27 Carrier Protein Structure and Recognition in Peptide Biosynthesis 249\u003cbr\u003e28 Kinetic Studies of the Initial Module PheATE of Gramicidin S Synthetase 253\u003cbr\u003e29 Protein-Ligand NOE Matching 259\u003cbr\u003e30 Side-Chain and Backbone Flexibility in Protein Core Design 265\u003cbr\u003e31 Distance Geometry 273\u003cbr\u003e32 Distance Geometry: NP-Hard, NP-Hard to Approximate 279\u003cbr\u003e33 A Topology-Constrained Network Algorithm for NOESY Data Interpretation 285\u003cbr\u003e34 MARS: An Algorithm for Backbone Resonance Assignment 293\u003cbr\u003e35 Errors in Structure Determination by NMR Spectroscopy 301\u003cbr\u003e36 SemiDefinite Programming and Distance Geometry with Orientation Constraints 307\u003cbr\u003e37 Graph Cuts for Energy Minimization and Assignment Problems 315\u003cbr\u003e38 Classifying the Power of Graph Cuts for Energy Minimization 323\u003cbr\u003e39 Protein Unfolding by Using Residual Dipolar Couplings 333\u003cbr\u003e40 Structure-Based Protein-Ligand Binding 341\u003cbr\u003e41 Flexible Ligand-Protein Docking 345\u003cbr\u003e42 Analyzing Protein Structures Using and Ensemble Representation 351\u003cbr\u003e43 NMR Resonance Assignment Assisted by Mass Spectrometry 355\u003cbr\u003e44 Autolink: An Algorithm for Automated NMR Resonance Assignment 363\u003cbr\u003e45 CS-Rosetta: Protein Structure Generalization from NMR Chemical Shift Data 371\u003cbr\u003e46 Enzyme Redesign by SVM 377\u003cbr\u003e47 Cross-Rotation Analysis Algorithm 383\u003cbr\u003e48 Molecular Replacement and NCS in X-ray Crystallography 387\u003cbr\u003e49 Optimization of Surface Charge-Charge Interactions 393\u003cbr\u003e50 Computational Topology and Protein Structure 399\u003cbr\u003eIndex 415Bruce 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.","brand":"The MIT Press","offers":[{"title":"Default Title","offer_id":46305048232165,"sku":"NP9780262548793","price":70.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780262548793.jpg?v=1767721217","url":"https:\/\/k12savings.com\/es\/products\/algorithms-in-structural-molecular-biology-isbn-9780262548793","provider":"K12savings","version":"1.0","type":"link"}