General

In Silico Drug Discovery

A major contributor of new leads to the drug discovery process is large-scale, often database-driven, calculation based on modelling ligand-macromolecular interactions or searches based on properties derived from pre-existing chemical entities. In this course these database mining techniques, along with allied chemical fragment-based approaches will be explored.

Learning Outcomes

At the end of this course students should be able to:

• Describe the major aspects of a docking application, including the methods for initial site point generation, and the various approaches to pose fitting.
• Distinguish between force field/enthalpy-based and knowledge-based pose scoring methods.
• Understand the properties that increase the value of compound databases.
• Have a clear understanding of the values and problems associated with multiconformer vs. single conformer chemical databases.
• Describe the principles behind QSAR analysis and provide examples of how QSAR can be used in decision making.
• Describe the major classes of similarity searching algorithms, and understand the types of problem that such programs can be applied to.