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Course Contents

Overview of protein structure (RCSB PDB, PDBe, PDBj) and models (All-atom models, Residue-based models, Simplified residue alphabets, Lattice models), experimental structure determination (X-ray crystallography, NMR) and structure analysis (STRING database, IntAct, DIP, MINT), fold classification (CATH, SCOP, DALI/FSSP), Multiple structural alignment (DaliLite), inference of function from structure, prediction (secondary structure, solvent exposure, neural networks), homology modeling (PMP, NESG, ModWeb), knowledge based energy functions, de novo prediction methods (ROSETTA, LINUS). RNA 2D and 3D structure prediction. Ab initio proten structure prediction (ROBETTA), Ramachandran plot, Docking of ligand with protein (PDBsum, PROCHECK), Computational analysis of protein-protein, protein-DNA, and protein-ligand interactions.

Course Synopsis

This course explores the use of bioinformatics databases and software as research tools. Software tools will be used to compare and analyze sequences and construct gene and protein models for solving research problems related to structural and functional genomics, proteomics and metabolomics

Course Learning Outcomes

To learn the importance of protein 3D structure and how to develop it step by step, experimentally and bioinformatically

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