HBM 621E - Chemoinformatics

Course Objectives

1. Introducing different chemoinformatics methods
2. Providing examples on the use of chemoinformatics in drug design research
3. Gaining practical experience with Python on the methods used in chemoinformatics

Course Description

The scope and history of chemoinformatics, Representation and manipulation of 2D and 3D molecular structures, Overview of databases/data sources, Calculation of physical and chemical data: molecular mechanics and quantum mechanics, Methods for data analysis: machine learning techniques in chemistry, neural networks, evolutionary algorithms and clustering techniques, Molecular descriptors, Quantitative Structure – Activity Relationship (QSAR), Drug design, Similarity methods, Analysis of high-throughput screening data, Virtual screening and docking, Combinatorial chemistry and library design.