Biomolecular Modelling

Course manual 2024/2025

Study materials

Literature

• Lecture slides and scientific literature will be provided. 

Practical training material

• Tutorials will be provided before each computer tutorial. 

Software

• VMD: https://www.ks.uiuc.edu/Research/vmd/

• Python, visual studio code: https://code.visualstudio.com/docs/languages/python

• Linux/Unix (for windows: https://ubuntu.com/tutorials/install-ubuntu-on-wsl2-on-windows-11-with-gui-support#1-overview)

Objectives

• The student is able to characterize the structure of proteins and nucleic acids.
• The student is able to describe the principles of molecular simulations, including moleuclar dynamics and importance sampling.
• The student is able to list the relevant interactions that are required to model a biomolecular system.
• The student is able to perform a molecular dynamics simulation on a biomolecular system.
• The student is able to construct structural models of proteins and nucleic acids.
• The student is able to describe the principles of docking.

Teaching methods

• Lecture
• Laptop seminar
• Computer lab session/practical training
• Working independently on e.g. a project or thesis

During the lectures, concepts will be introduced, including theoretical background and examples of applications. During the laptop seminars and computer lab sessions, the students will work with the concepts introduced in the lectures, and apply these to relevant problems. 

Learning activities

Attendance

Programme's requirements concerning attendance (OER-B):

• Active participation is expected of each student in the course for which he is registered.
• If a student cannot attend an obligatory part of a programme's component due to circumstances beyond his control, he must report in writing to the teacher in question as soon as possible. The teacher, if necessary after consulting the study adviser, may decide to issue the student a replacing assignment.
• It is not allowed to miss obligatory parts of the programme's component if there is no case of circumstances beyond one's control.
• In case of participating qualitatively or quantitatively insufficiently, the examiner can expel a student from further participation in the programme's component or a part of that component. Conditions for sufficient participation are fixed in advance in the study guide and/or on Canvas.

Additional requirements for this course:

• Attendance is not compulsory, but highly recommended. When attending lectures or computer lab sessions, be on time. When a student has not attended a lecture or computer lab session, it is the responsibility of the student to catch up, by self-study, asking other students, or making an appointment with the lecturer or TA. 
• The students have to hand in all assignments before the deadline. Missing an assignment means that that assignment is graded with 1.  All assignment grades are included in the average grade. Requests for deadline extension must be communicated as soon as the need for the extension arises, and will only be granted if there are compelling personal reasons beyond the control of the student (stolen laptop, family emergency, sickness, etc). Extension of a deadline will only be granted on an individual basis and may be checked with the study advisor. 
• Communication will go via canvas. The account information for the supercomputer snellius will be sent by email to each student individually. 

Assessment

Missing an assignment means that that assignment is graded with 1.  All assignment grades are included in the average grade. Requests for deadline extension must be communicated as soon as the need for the extension arises, and will only be granted if there are compelling personal reasons beyond the control of the student (stolen laptop, family emergency, sickness, etc). Extension of a deadline will only be granted on an individual basis and may be checked with the study advisor. 

Inspection of assessed work

Assignments will be discussed during the computer lab session following the deadline of the assignment. Feedback on the report will be provided on the speed-grader in canvas. Further feedback can be provided during an appointment. The initiative for such an appointment lies with the student. 

Assignments

All assignments will be individual and will be checked for plagiarism and use of generative AI models without fact checking. 

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Contact information

Coordinator

• dr. Jocelyne Vreede

Staff

• D.P. Geerke