Drug design
General data
Course ID: | 1000-717PRL |
Erasmus code / ISCED: |
11.954
|
Course title: | Drug design |
Name in Polish: | Projektowanie leków |
Organizational unit: | Faculty of Mathematics, Informatics, and Mechanics |
Course groups: |
Obligatory courses for 2nd stage Bioinformatics |
ECTS credit allocation (and other scores): |
6.00
|
Language: | Polish |
Type of course: | obligatory courses |
Mode: | Remote learning |
Short description: |
The aim of the course is to present the basics of computational design of biologically active compounds. |
Full description: |
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 |
Bibliography: |
Erland Stevens, "Medicinal Chemistry The Modern Drug Discovery Process", PEARSON |
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 methods and 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. |
Classes in period "Winter semester 2023/24" (past)
Time span: | 2023-10-01 - 2024-01-28 |
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MO TU W WYK
LAB
TH FR |
Type of class: |
Lab, 30 hours
Lecture, 30 hours
|
|
Coordinators: | Dominik Gront | |
Group instructors: | Dominik Gront, Karol Wróblewski | |
Students list: | (inaccessible to you) | |
Examination: | Examination |
Classes in period "Winter semester 2024/25" (future)
Time span: | 2024-10-01 - 2025-01-26 |
Navigate to timetable
MO TU W WYK
LAB
TH FR |
Type of class: |
Lab, 30 hours
Lecture, 30 hours
|
|
Coordinators: | Dominik Gront | |
Group instructors: | Dominik Gront, Karol Wróblewski | |
Students list: | (inaccessible to you) | |
Examination: | Examination |
Copyright by University of Warsaw.