KE824: Biomolecular Simulations

Study Board of Science

Teaching language: English
EKA: N540034102
Censorship: Second examiner: Internal
Grading: 7-point grading scale
Offered in: Odense
Offered in: Spring
Level: Master's level course approved as PhD course

STADS ID (UVA): N540034101
ECTS value: 5

Date of Approval: 24-10-2018


Duration: 1 semester

Version: Approved - active

Comment

10007201(former UVA) is identical with this course description. 
If there are fewer than 12 students enrolled, the course may. be held with another teaching form. 

Entry requirements

None

Academic preconditions

Students taking the course are expected to:

  • Have knowledge of basic physics chemistry and mathematics
  • Be able to use computers

Course introduction

The aim of the course is to enable the student to understand and
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

The learning objective of the course is that the student demonstrates the ability to:
  • 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

The following main topics are contained in the course:
  • 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

Spring

Tests

Portfolio

EKA

N540034102

Censorship

Second examiner: Internal

Grading

7-point grading scale

Identification

Full name and SDU username

Language

Normally, the same as teaching language

Examination aids

A closer description of the exam rules will be posted under 'Course Information' on Blackboard.

ECTS value

5

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

50 hours per semester

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.

Teacher responsible

Name E-mail Department
Himanshu Khandelia hkhandel@sdu.dk

Timetable

Administrative Unit

Fysik, kemi og Farmaci

Team at Registration & Legality

NAT

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