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.
You will find the timetables for all courses and degree programmes of Leiden University in the tool MyTimetable (login). Any teaching activities that you have sucessfully registered for in MyStudyMap will automatically be displayed in MyTimeTable. Any timetables that you add manually, will be saved and automatically displayed the next time you sign in.
MyTimetable allows you to integrate your timetable with your calendar apps such as Outlook, Google Calendar, Apple Calendar and other calendar apps on your smartphone. Any timetable changes will be automatically synced with your calendar. If you wish, you can also receive an email notification of the change. You can turn notifications on in ‘Settings’ (after login).
For more information, watch the video or go the the 'help-page' in MyTimetable. Please note: Joint Degree students Leiden/Delft have to merge their two different timetables into one. This video explains how to do this.
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, see below. 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%). The retake will have the form of an essay assignment to be handed in via Brightspace.
Presence and active participation during the working groups (mainly computer assignments) and discussions is mandatory.
Literature will be provided during the course via Brightspace.
From the academic year 2022-2023 on every student has to register for courses with the new enrollment tool MyStudyMap. There are two registration periods per year: registration for the fall semester opens in July and registration for the spring semester opens in December. Please see this page for more information.
Please note that it is compulsory to both preregister and confirm your participation for every exam and retake. Not being registered for a course means that you are not allowed to participate in the final exam of the course. Confirming your exam participation is possible until ten days before the exam.
Extensive FAQ's on MyStudymap can be found here.
Assignment deadlines are communicated via Brightspace.
A relatively young laptop (2014 onwards) running Windows, Linux or Macintosh operating system is required. Macs with Apple Silicon (MacBook Pro (13-inch, M1, 2020), MacBook Pro (14-inch, 2021), MacBook Pro (16-inch, 2021), MacBook Air (M1, 2020) and later models) are not supported.
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.