Drug design 1000-717PRL
1) Introduction to drug design
2) Review of the background knowledge
- the most important types of non-covalent interactions
- thermodynamic description of interactions
- 2D vs 3D structure, polymorphisms, isomers and conformations
- molecular modeling methods: force fields, conformational space and its sampling
3) Macromolecules as a drug target.
- primary, secondary, tertiary and quaternary structure of proteins; prosthetic groups and ligands
- structure of nucleic acids
- modeling of protein structure and dynamics: comparative modeling and molecular dynamics
4) Protein-ligand interactions
- protein surface and its properties, active site, binding pocket
- antagonist, agonist, inhibitor
- docking algorithms, scoring functions
5) Elements of chemoinformatics
- databases of chemical particles and their searches
- SMILES
- graph-based and other common algorithms
- combinatorial chemistry
6) Drug design strategies
- leading structure
- drug pharmacophore
- Lipiński's rule
- pharmacodynamics and pharmacokinetics
7) Proteins as therapeutic agents
- design of artificial proteins
- antibodies
8) Application of machine learning
Course coordinators
Type of course
Mode
Learning outcomes
After finishing the course student:
- knows typical drug design problems,
- can analyze the structure and function of biomolecular systems related to disease processes,
- can analyze the properties of both small molecules and the receptor
- can use acquired knowledge in other fields, e.g. in medical diagnostics and in medical biology,
- is aware of the responsibility for the research, experiments or observations undertaken,
- understands and appreciates the importance of intellectual honesty in their own and other people's actions; acts ethically,
- can formulate opinions on basic bioinformatics issues,
- is able to see the limitations of his own knowledge and the need to constantly supplement and update it.
Assessment criteria
To pass the laboratories, it is necessary to:
- attend classes and submit reports (typically a Jupyter notebook or a Python script)
- finish semester’s project
To pass the lecture, it is necessary to:
- pass the laboratories
- write a theoretical exam comprising several open questions
- two exam terms will be scheduled plus an “early-bird” term
Phd students additionally should complete a research project within the laboratory.
Bibliography
Erland Stevens, "Medicinal Chemistry The Modern Drug Discovery Process", PEARSON