Admission requirements
Master students of Bio-Pharmaceutical Sciences, Biomedical Sciences, Life Science & Technology, Molecular Science & Technology. Required background knowledge is thorough knowledge of protein structure and organic chemistry at the level of Molecular Chemistry (for MSc LST students) or Organic Chemistry 2 (4052ORGC2 for BSc MST or equivalent).
Description
Computational approaches are now an established part of modern drug discovery. In this course, we will cover some of the main advances in the field, such as (but not limited to) molecular dynamics, free energy perturbation, machine learning and de novo molecular generation. The student will learn about the theoretical background of these approaches in a series of lectures, after which they will put this knowledge into practice to ultimately design a potential new drug candidate of their own. This course aims to:
Introduce key advances in the field of computational drug discovery
Leave the student with a set of tools to independently perform computer aided drug discovery approaches
Aid in understanding relevant literature in the field of computational drug discovery
Introduce public databases and repositories relevant to computational drug discovery
Understand and explain limitations of computational drug discovery
Course objectives
At the end of this course the student is able to:
describe and explain key methods in computational drug discovery
describe and explain basic machine learning models
design experimental setups for using computational modelling in drug discovery
read scientific literature, and can critically reflect on the rational and experimental approach of the study as well as on the results presented and conclusions drawn by the authors.
present key research findings to peers.
report key research findings in a written report
Timetable
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
Lectures (hoorcolleges)
Tutorial (werkcollege)
Practical work (praktisch werk/practica)
Tutoring (studiebegeleiding)
Self-tuition (zelfstudie)
Assessment method
The course will be concluded with a written report and a presentation. The written report will be counting for 80% and the presentation for 20% of the final grade for the course.
Reading list
Will be announced during the course.
Registration
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.
Contact
Coordinator: Willem Jespers (e-mail: w.jespers@lacdr.leidenuniv.nl).
Remarks
This information is without prejudice. Alterations can be made for next year.