Introduction to Structural Bioinformatics

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, protein–ATP docking, and antibody–antigen interaction prediction, respectively.

• Part 1: Bioinformatics Basics1. Bioinformatics databases2. Pairwise sequence alignments and database search3. Evolution and phylogenetic tree4. Multiple sequence alignments5. Machine learning and deep neural-network learningPart 2: Structural Bioinformatics6. Protein structure alignments7. Monte Carlo simulation and local energy minimization8. Protein structure prediction9. RNA structure prediction10. Quaternary structure prediction11. Function annotations12. Protein designPart 3: Experimental Structural Determination13. Principle of X-ray crystallography and molecular replacement14. Introduction to nuclear magnetic resonance15. Cryo-electron microscopy for protein structure determination