Biomolecular Simulations

Course manual 2023/2024

Course content

Molecular dynamics is a powerful tool to investigate the structure and dynamics of biologically relevant molecules such as proteins, DNA and lipids in atomistic detail. The insight from MD simulation yields quantitative predictions and a 'molecular movie' of important processes that helps experimentalists interpret their results. Such simulations can also be used to predict effects of e.g. point mutations. This course provides an introduction to biomolecular simulation using molecular dynamics, and enhanced sampling methodology to study biomolecular processes.

This course consists of lectures which will cover the following topics: 1) the basics of molecular dynamics, 2) the structural analysis of biomolecules, e.g. through NMR and crystallography, 3) multiscale modeling of biomolecular systems 4) the problem of rare events in conformational changes.

In addition to the lectures there will be a practical tutorial consisting of theoretical exercises as well as computer problems. The course ends with doing a small project including a real simulation on a biomolecular system.

Study materials

Syllabus

Software

Other

• Online tutorials

Objectives

• Characterize the structure of proteins and nucleic acids and assess the quality of structures in the Protein DataBank.
• Cescribe the relevant aspects of statistical mechanics, thermodynamics and transition state theory.
• Cescribe the basic principles of molecular dynamics.
• List the relevant interactions that are required to model a biomolecular system.
• Perform a molecular dynamics simulation on a protein system.
• Explain what a rare event is.
• List methods to overcome the rare event problem.
• Perform a simulation with a bias potential.
• Perform a transition path sampling simulation.
• Understand the concepts behind multi-scale modelling.

Teaching methods

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

Lectures and werkcolleges/computer practicum.

Learning activities

Attendance

This programme does not have requirements concerning attendance (TER part B).

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. Reasonable requests for deadline extension can be granted. Reasonable means as soon as the need for the extension arises, and such a need should be circumstances beyond the control of the student (stolen laptop, family emergency, sickness, etc). Extension of a deadline will only be granted on an individual basis. 
• Communication will go via canvas. The account information for the supercomputer snellius will be sent by email to each student individually. 

Assessment

Examination consists of five assignments, each 10 % of the grade, and a written report, based on a molecular simulation study of a biomolecule performed during the course, 50 % of the grade. 

Failure to hand in an assignment on time will result in a grade of 1 for that particular assignment. 

Inspection of assessed work

The manner of inspection will be communicated via the digitial learning environment.

Assignments will be discussed during the computer lab session following the deadline of the assignment. Feedback on the report will be provided on the speedgrader 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. Feedback will be provided via grading in canvas. Grades will be given via canvas.

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

Additional information

Recommended prior knowledge: thermodynamics, statistical mechanics, biochemistry, linux, python

It is possible to take this course while missing some of the prior knowledge. If you miss all, the course may be hard to follow. 

Contact information

Coordinator

• dr. Jocelyne Vreede

Contact the course coordinator for questions.