KE824: Biomolecular Simulations
Comment
If there are fewer than 12 students enrolled, the course may. be held with another teaching form.
Entry requirements
Academic preconditions
Students taking the course are expected to:
- Have knowledge of basic physics chemistry and mathematics
- Be able to use computers
Course introduction
implement the particle-based molecular simulations of complex biological
systems such as proteins, membranes and nucleotides, and interactions
between them. In addition, the course aims to inculcate a quantitative
understanding of biomolecular interactions, as well as to encourage and
emphasize the importance of interdisciplinary research, which is
important in regard to understanding molecular interactions in
biological systems
Furthermore, the students will learn to run simulations on the ABACUS 2.0 supercomputer
The
course builds on the knowledge acquired in courses like molecular
modelling, and gives an academic basis for studying the topics
modelling, nanotechnology, biochemistry, medicinal chemistry that are
part of the degree.
In relation to the competence profile of the degree it is the explicit focus of the course to:
- Give the competence to run state of the art molecular simulations on large supercomputers
- Give
skills to run particle-based simulations for different length scales of
liquid systems, such as proteins, membranes and nucleotides, the
cluster computers. The students will be able to dig useful information
out of these simulations and use it to interpret experimental data.
Students will learn to apply scientific computing methods to solve
research problems - Give knowledge and understanding of biomolecular interactions
Expected learning outcome
- identify the need of implementing a molecular simulation to address a biological problem
- to
explain a limited set of fundamentals of statistical mechanics (phase
space, sampling, ergodic hypothesis, probability density) - to
setup, implement and analyze a molecular dynamics simulation containing
various types of (bio)molecules interacting with each other, and compare
the output to experimental data - is able to use supercomputers to run simulations
Content
- short introduction to statistical mechanics
- molecular dynamics simulation
- analysis of molecular dynamics simulations
- tutorials
on the following topics: simulations of a (1) Lennard jones fluid (2)
ethanol (3) protein in water (4) lipid membranes (5) coarse grained
simulations and (6) specific topics of interest to students - introduction to disspative particle dynamics, monte-carlo simulations
Literature
- Andrew Leach: Molecular Modelling: Principles and Applica-tions..
See Blackboard for syllabus lists and additional literature references.
Examination regulations
Exam element a)
Timing
Tests
Portfolio
EKA
Assessment
Grading
Identification
Language
Examination aids
A closer description of the exam rules will be posted under 'Course Information' on Blackboard.
ECTS value
Additional information
Portfolio: A combination of a project report and an MC-test will constitute to the mark with 50% and 50% respectively
The examination form for re-examination may be different from the exam form at the regular exam.
Indicative number of lessons
Teaching Method
The teaching method is based on three phase model.
Intro phase: 20 hours
Skills training phase: 30 hours, hereof:
- Tutorials: 30 hours
The teaching will be ~ 20% lecture based, and the rest lab exercise based, because the objective of the course is to make the students familiar with running simulations. The lectures will provide a fundamental basis of running the simulations.
Educational activities
The students are expected to become familiar with the fundamentals of both statistical mechanics and molecular dynamics, specific reading will be provided in class. Also, the students will be responsible for becoming familiar with visualization software (VMD) on their own. Tutorials will be provided for these.
Most importantly, the students are expected to continually work on the home assignments.