Section I. Data Collection, Analysis, and Visualization 1. Chapter 1 ? Defining Bioinformatics and Structural Bioinformatics Introductory overview of the field of Structural Bioinformatics, the technical advances, challenges, and accomplishments presented by the field for the advancement of science. Keywords: Structural Bioinformatics 2. Chapter 2 ? Fundamentals of Protein Structure Basic introduction to primary, secondary, and tertiary structural features of proteins. Keywords: Amino Acids, alpha helix, beta strands, coil, primary structure, secondary structure, tertiary structure. 3. Chapter 3 ? Fundamentals of DNA and RNA Structure Basic introduction to the structure of DNA and RNA. Highly detailed discussion of interacting base pairs and conformational alternative. Various tertiary conformation of DNA and RNA is also discussed with implication for intermolecular interactions with proteins and small molecules. Keywords: Nucleic Acids, Base pair Geometry, DNA Duplex, A-DNA, B-DNA, Z-DNA, RNA Duplex, Transfer RNA, Ribozymes, Ribosome. 4. Chapter 4 ? Computational Aspects of High-throughput Crystallographic Macromolecular Structure Determination Automating the process of obtaining structure solutions for X-ray crystallographic experiments. Computational approaches complements experimental strategies for faster structural elucidation. Also, strategies to overcome potential experimental roadblocks such as merohedral twinning are discussed. Density modification, molecular replacement, and map interpretation that are subsequently applied to the raw data helps to improve the success of obtain a structure solution. Finally refinement and validation procedures are necessary to ensure the correct solution. Keywords: Multi-wavelength anomalous diffraction, single anomalous diffraction, heavy atom refinement and phasing, density modification, electron density map interpretation. 5. Chapter 5 ? Macromolecular Structure Determination of NMR Spectroscopy The use of nuclear magnetic resonance spectroscopy offers several advantages over X-ray crystallography particularly for the study of conformational variants and protein dynamics. Technological advances and strategies in experimental as well as computational methods to facilitate high throughput NMR spectroscopy are discussed. Keywords: Nuclear Magnetic Resonance Spectroscopy, Stable Isotope Labeling, Cell based methods, Cell free methods, NOE Assignment 6. Chapter 6 ? Electron Microscopy in the Context of Structural Systems Biology Electron microscopy allows for the visualization of how high resolution structures fit together to form large heterogeneous assemblies that have a wide range of morphologies and complexity. The transient and steady structures of these large systems can be better understood with knowledge of structural pathways and ligand interactions that occur in the cellular environment with this technique. Keywords: Electron Microscopy, Electron optics, Image formation, 3D Reconstruction, Single-particle analysis, electron tomography 7. Chapter A- Study of protein three-dimensional structure and dynamics using peptide amid hydrogen/deuterium exchange mass spectrometry and chemical cross-linking with mass spectrometry to constrain molecular modeling. Emerging techniques to obtain experimental constraints that can provide insight into the structure and dynamic of molecules that cannot otherwise be easily obtained using traditional structure biology techniques. Keywords: Hydrogen-Deuterium Exchange mass spectrometry, Deuterium Exchange Mass Spectrometry, Chemical Cross-linkage, 8. Chapter B ? Sampling and Search Techniques Covers fundamentals for issues that needs to be considered when designing structural bioinformatics algorithms. 9. Chapter 7 ? Molecular Visualization Once the structural solution is obtained, it is important to be able to properly visualize and communicate these findings in an easily accessible manner. The different representations that have already been implicitly introduced in the book are discussed in more detail here. The technical challenges and different representations of biological molecules to be communicated are presented. Keywords: Molecular Visualization, Protein Representation, Small Molecule Representation, interactive graphic 3D Visualization Section II. Data Representation and Databases 10. Chapter 8 ? The PDB Format. mmCIF Formats, and other data formats Data formats that are used to represent the structural data are presented here. Proper data organization is important in facilitating access for bioinformatics analysis and preserving information content. Keywords: PDB Format, mmCIF, PDBML 11. Chapter 9 ? The Worldwide Protein Data Bank The organization of the wwPDB, a data repository for protein structures, is described here. The services for data acquisition, validation and distribution is provided by several member sites for this global resource. Keywords: wwPDB 12. Chapter 10 ? The Nucleic Acid Database A resource for specialists studying nucleic acid structures providing several services that has enabled discoveries. Keywords: Nucleic Acid Database 13. Chapter 11 ? Other Structure-Based Databases Secondary resources using data from either the PDB or the NDB that are more focused and better annotated. Other topics of interest such as molecular interaction and conditions for successful crystallizations are examples of these specialized databases. Section III. Data Integrity and Comparative Features 14. Chapter 14 ? Structural Quality Assurance Submitted structures are not without errors, this chapter discusses some egregious errors that has been identified and mechanisms to detect and reduce these errors in structures. 15. Chapter 15 ? All-Atom Contacts: A new approach to structure validation A method to reduce the number of errors and validate structures that have been deposited. Keywords: All atom contact analysis, MolProbity, Structure Validation 16. Chapter 16 ? Structure Comparison and Alignment To make comparison between structures, it is important to properly align them before analysis. Comparison of the performances of different algorithms are discussed. Keyword: Multiple Structure Alignment, 17. Chapter 12 ? Protein Structure Evolution and the SCOP Database Similarities between protein structures are conserved and can be classified based on features such as their topology. The evolutionary origin of these similarities can be rooted in selective pressures for stable folds that are necessary for function. The classification schema for this data organization that is sorted by experts is useful in understanding the structural space sampled by Nature. Keywords: SCOP, Protein evolution, fold conservation, Structure Classification 18. Chapter 13 ? The CATH Domain Structure Database CATH is a resource that also identifies structural similarities and evolutionary relationship between proteins with more use of automated techniques. The pipeline of how these classifications are achieved and the modules of each stage are described in detail. Resources such as CATH help researches gauge the coverage of the protein structure space and whether the current knowledge base is adequate. Keywords: CATH, Structure Classification, CORA, Gene3D, Dictionary of Homologous Superfamilies Section IV. Structural and Functional Assignment 19. Chapter 17 ? Secondary Structure Assignment Regular secondary structure elements in the 3D structure can be identified in all known structures and proper assignment of these elements are needed. Assignment schemes and their importance for studying proteins are discussed. Keywords: Secondary Structure Assignment, Hydrogen Bond, Voronoi tessellation 20. Chapter 18 ? Identifying Structural Domains in Proteins The underlying concepts that shape the foundation of how domain boundaries are defined in proteins structures are discussed. The strength and weaknesses of different strategies are discussed. Furthermore the promising development of sequence based methods that are guided by our understanding gleaned from structures will also be reviewed. Keywords: Domain Boundary definition 21. Chapter 19 ? Inferring Protein Function from Structure Strategies to annotate function to protein structures are discussed. Structural features that can be extracted for functional annotation has proved to be useful for understand newly resolved protein structures.

This is achieved through fold comparisons and identification of surface clefts, binding pockets, and key functional residues. Keywords: Functional Annotation, Enzyme Commission, Residue Template 22. Chapter C ? Genome Functional Annotation with Structural Alignment Based Profiles Annotation of genomes by leveraging structural information allows for identification of distantly related homologous that can not otherwise be achieved using only sequence information. The results allow for the identification of new target genes to be characterized and provide insight into evolutionary mechanisms for diversification. Keywords: Genome annotation 23. Chapter K ? Structures to Study Evolution The use of domain composition has been a useful marker to help deconvolute and clarify evolutionary histories of different species. The use of structural information has provided added advantage and demonstration of the additional insights gained from this approach is discussed. Keywords: LUCA, Domain Content, Domain Evolution Section V. Macromolecular Interactions 24. Chapter 21 ? Electrostatic Interactions Structural models of molecules needs to be related back to their biophysical properties to fully appreciate the fundamental driving forces in Nature that give rise to their structure and function. Among the various components of molecular energetics, the electrostatic interactions are of special importance due to the long range of the interactions and the substantial charges that are typical components of biopolymers with many functional consequences. Keywords: Electrostatic Interactions, Poisson-Boltzman equation, Electrostatic comparisons. 25. Chapter D ? Prediction of Protein-Nucleic Acid Interactions Current structures of DNA-Protein interactions often contain recognition to well studied transcription start sites. Consequently, there is a significant value in being able to identify other DNA recognition sites that can be recognized by transcription factors. Research advances in making predictions for Protein-Nucleic Acid is discussed. Keywords: Transcription Site recognition 26. Chapter 20 ? Prediction of Protein-Protein Interactions from Evolutionary Information Similarly to Chapter 25, a better reconstruction of the protein interaction network will help improve our understanding of biological processes. Integrating the use of structural information, as well as information from multiple sources, will help provide a refined network of interactions. To achieve this reconstruction, binding surfaces and interacting residues that are important for intermolecular recognition needs to be accurately identified. Furthermore, it is also important to identify correct interacting protein pairs. Keywords: Protein-Protein Interaction, Binding Interfaces, Protein Interacting Pairs 27. Chapter 22 ? Docking Methods, Ligand Design, and Validating Datasets in the Structural Genomics Era Fundamentals of docking and applications to ligand design are discussed. Keywords: Docking, Structure Based Drug Design Section VI. Structure Prediction 28. Chapter 24 ? CASP and CAFASP Experiments and their findings A brief history of a biannual self-evaluation of structure prediction methods created by the community to raise new standards in understanding the sequence-structure relationship. Other benchmarking services for structure prediction algorithms are also discussed. Keywords: CASP, CAFASP, LiveBench, EVA 29. Chapter 28 ? Prediction in 1D: Secondary Structure, Membrane Helices and Accessibility One dimensional predictions from sequence information can provide researchers with knowledge of boundaries between features such as secondary structure and other protein properties such as transmembrane regions. Often predictors in this class are applied to proteins in which obtaining structural data is particularly difficult even with the use of 3D prediction methods. These predictors are also particularly useful for large-scale analyses often demanded by recent genome projects because of the low computational requirements. Keywords: Secondary Structure Prediction, Transmembrane Region Predictions 30. Chapter 25 ? Homology Modeling The first of three strategies in which the research aims are to obtain protein models from sequence information. Protein structure models are constructed when structural information is available for a close homolog. Solutions are often easier to obtain in instances where homology modeling can be used. Keywords: Homology Modeling, Template Recognition, Model Optimization, Model Validation 31. Chapter 26 ? Fold Recognition Methods 32. Chapter 27 ? Ab Initio Methods For the most difficult proteins without a homologue sharing >25% sequence identity, researchers are forced to resort to ab initio Structure prediction methods. The challenges and strategies to improve predictions are discussed. Keywords: de novo Structure Prediction, Reduced Complexity Models, High Resolution Structure Prediction 33. Chapter F ? RNA Structural Bioinformatics Approaches to predicting RNA structures are discussed in this chapter. Fundamentals of RNA structure and different representations used in RNA structural bioinformatics are reviewed. Keywords: RNA Structural Bioinformatics, RNA Structure Prediction, RNA Motifs Section VII. Therapeutic Discovery 34. Chapter 23 ? Structural Bioinformatics in Drug Discovery The dramatic increase in the availability of protein sequences and structures holds tremendous value for the pharmaceutical industry. Structural bioinformatics techniques are required in order for the potential value of this information to be fully exploited in the search for new medicines. This chapter discusses the current and future impact of structural bioinformatics in pre-clinical drug discovery. Keywords: drug discovery, protein structure, protein sequence, virtual screening 35. Chapter E ? Antigen Recognition Sites Identifying antigen sites on proteins will be useful in antibody-based therapeutics. Understanding structure of the epitope is important for identifying key features responsible for recognition by the antibody. The ultimate goal of epitope prediction is to enable the design of molecules that will substitute for the antigen to interfere with the immune response which will be useful in treating autoimmune diseases, for example. Keywords: Antigenicity, epitope recognition, antibody structure Section VIII. Future Challenges 36. Chapter G ? Methods to classify and predict the structure of membrane proteins. The physico-chemical properties of membrane associated proteins make it a more difficult system to obtain structural information compared to globular proteins. Membrane proteins are highly insoluble and unstable in aqueous solutions thus leading to significant experimental challenges. Computational methods for the identification and structural prediction of membrane proteins are discussed. Available web resources to help facilitate a better understanding of membrane proteins are also reviewed. Keywords: Membrane proteins, biological membrane 37. Chapter L ? Protein Motion 38. Chapter I ? Protein Disorder and Conformational variants Disordered regions prevent structural elucidation of protein structure and are a significant challenge to structural genomics efforts. Through bioinformatics efforts significant understanding of these regions have been made by examining the sequence space of regions in the protein that are beyond the limits of structural detection. Keywords: Protein Disorder, Conformational Variants 39. Chapter H ? Protein Designability and Engineering The limits of protein design as constrained by structural and thermodynamic necessity is reviewed in this chapter to better understand how proteins can be altered. Several factors that allow for modulation or that needs to be consider in the design of new folds are discussed. Keywords: Protein Designability, Protein Engineering, and Domain Evolution 40. Chapter 29 ? Structural Genomics of Protein Superfamilies Structural genomics aims to deliver high resolution structures for biologically themed and community nominated targets in a high throughput fashion. The successes of this ongoing initiative conducted by several different centers and their contribution to scientific advancement is discussed. Keywords: Structural Genomics, Biological Theme Targets, NYSGXRC, Community_Nominated Targets