Introduction to Structural Bioinformatics offers a complete overview to the fundamental concepts and methodologies of structural bioinformatics and computational structural biology. The book is divided into three sections, beginning with a discussion of the key principles of bioinformatics and fundamental aspects including bioinformatics databases, multiple sequence alignment and machine learning. Section two then moves on to structural bioinformatics, where topics include Monte Carlo simulation, protein structure prediction, RNA structure prediction, and protein design. The final section of the book focuses on experimental structural determination, where chapters focus on techniques including X-ray crystallography, nuclear magnetic resonance and cryo-electron microscopy. This is an ideal guide to the key principles, methods and most up-to-date developments across structural bioinformatics and computational structural biology, providing a comprehensive reference for postgraduate students, instructors and researchers working in these and adjacent subjects.
Part 1: Bioinformatics Basics
1. Bioinformatics databases
2. Pairwise sequence alignments and database search
3. Evolution and phylogenetic tree
4. Multiple sequence alignments
5. Machine learning and deep neural-network learning
Part 2: Structural Bioinformatics
6. Protein structure alignments
7. Monte Carlo simulation and local energy minimization
8. Protein structure prediction
9. RNA structure prediction
10. Quaternary structure prediction
11. Function annotations
12. Protein design
Part 3: Experimental Structural Determination
13. Principle of X-ray crystallography and molecular replacement
14. Introduction to nuclear magnetic resonance
15. Cryo-electron microscopy for protein structure determination
Dr Yang Zhang is Professor in the Department of Computer Science, School of Computing, National University of Singapore (NUS). He also serves as Professor and Senior Principal Investigator in the Department of Biochemistry at School of Medicine, NUS, and Cancer Science Institute of Singapore, respectively. Prior to this, Dr Zhang worked as Professor in the Department of Computational Medicine and Bioinformatics and the Department of Biological Chemistry, University of Michigan. Dr Zhang has been teaching graduate courses in bioinformatics for more than a decade. His research interests are in artificial intelligence, deep neural network learning, protein folding, structure prediction, and protein design and engineering. Dr. Zhang is the inventor of many fundamental concepts and methods in structural bioinformatics, including TM-score, TM-align, I-TASSER, and QUARK. Dr. Zhang has received honours including the Alfred P Sloan Award, US NSF Career Award, ASBMB DeLano Award, and University of Michigan Basic Science Research Award.
Dr. Jun Hu obtained his Ph.D. in Control Science and Engineering from Nanjing University of Science and Technology. He served as an Associate Professor of Bioinformatics at Zhejiang University of Technology from 2018 to 2023 and has been a Research Associate Professor of AI and Bioinformatics at the Suzhou Institute of Systems Biology since 2024. His research focuses on deep learning-based protein structure and function prediction. He has authored over 40 peer-reviewed publications, including 18 as first and/or corresponding author. His work includes widely used open-source algorithms in structural bioinformatics, such as LS-align, ATPdock, and RLEAAI, for ligand structure alignment, proteinATP docking, and antibodyantigen interaction prediction, respectively.
