Core course in MSc Chemistry – Chemical Biology. Elective course for MSc Life Science and Technology, MSc Chemistry – Energy & Sustainability and MSc Bio-pharmaceutical Sciences.
Required background knowledge is thorough knowledge of protein structure and organic chemistry at the level of Molecular Chemistry (4423MCHEM) (for MSc LST students) or Organic Chemistry 2 (4052ORGC2 for BSc MST or equivalent).
Although chemical biological research is typically viewed as a purely empirical endeavour, computational techniques can be of tremendous help in explaining and predicting observations made.
In this course, students will be introduced to a broad set of computational approaches used in chemical biology. Topics include: calculating and analysing physicochemical properties of large sets of compounds (cheminformatics), finding and using online repositories of published data, running and analysing molecular dynamics simulations on proteins, quantum mechanical approaches to conformation analysis and finally structure based drug discovery and machine learning applications to drug discovery.
This course aims to
raise students’ interest and enthusiasm for the field of computational chemical biology.
give an introduction of the most important concepts and computational methods used and their application in chemical biology and drug discovery.
give the student sufficient background to interpret computational methods and fundamental approaches found in chemical biology research publications.
introduce a number of public databases that are relevant for computational chemical biology.
explain limitations in cheminformatics, bioinformatics or computational chemical biology.
introduce the latest developments and insights in the field of machine learning and drug discovery.
allow students to solve problems that are rooted the biological domain with computational tools.
After the course, students will
be able to apply important principles of chemical informatics;
understand the basic principles governing the physicochemical properties of molecules;
be able to explain the benefits and limitations of computational techniques as applied in chemical biology;
be able to set up a molecular dynamics simulation for a protein and analyse the results
understand the fundamental differences between molecular mechanics force fields and quantum-mechanical calculations and when to apply which;
have a basic understanding of structure-based drug discovery and the most important subdisciplines thereof;
have a basic understanding of artificial intelligence methods as it is applied in drug discovery;
Schedule information can be found on the website of the programmes. Assignment deadlines are communicated via Brightspace.
Mode of Instruction
The course will use a combination of lectures (typically 4-6 hours per week) and hands-on computer work (typically 2-4 hours per week, usually after the lectures). A laptop running Windows, Linux or Macintosh operating system is required. In case of ongoing restrictions in group size or university access, online alternatives will be used to organise lectures and working groups.
A written exam will make up the final grade (100%).
Presence and active participation during the working groups (mainly computer assignments) and discussions is mandatory.
If the corona situation precludes a physical on-campus exam, changes to the assessment method will be announced via Brightspace a minimum of 10 working days before the originally scheduled exam date.
Literature will be provided during the course via Brightspace.
Register for this course via uSis
A laptop running Windows, Linux or Macintosh operating system is required.
According to OER article 4.8, students are entitled to view their marked examination for a period of 30 days following the publication of the results of a written examination. Students should contact the lecturer to make an appointment for such an inspection session.