Course manual 2022/2023

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;
  • describe the relevant aspects of statistical mechanics, thermodynamics and transition state theory;
  • describe 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 metadynamics simulation and perform a transition path sampling simulation. 
  • describe interactions between particles and how these interactions are used in a computer model.
  • 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

Activity

Number of hours

Laptop lectures

16

Lectures

16

Self study (includes reviewing lectures, making assignments, writing report)

136

Attendance

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

Assessment

Item and weight Details

Final grade

1 (10%)

Searching, downloading and visualizing PDB files

1 (10%)

Introduction to linux and python

1 (10%)

Molecular Dynamics with GROMACS

1 (10%)

Metadynamics with GROMACS and PLUMED

1 (10%)

Transition Path Sampling using OpenPathSampling

5 (50%)

Project: Explore the conformational space of DNA or peptide

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. 

Inspection of assessed work

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

Assignments

vmd

  •  Searching, downloading and visualizing PDB files

linux/python

  •  Introduction to linux and python

gromacs

  • Molecular Dynamics with GROMACS

plumed

  •  Metadynamics with GROMACS and PLUMED

OpenPathSampling

  •  Transition Path Sampling using OpenPathSampling

Project

  •  Explore the conformational space of DNA or peptide

Assignments and project will be evaluated individually, and checked for plagiarism. 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

Weeknummer Onderwerpen Studiestof
1  Structure of biomolecules  
2  Molecular Dynamics  
3  Force fields  
4  Sampling  
5  Biased sampling  
6  Transition path sampling  
7  Coarse graining  
8 Docking  

Timetable

The schedule for this course is published on DataNose.

Additional information

Recommended prior knowledge: thermodynamics, statistical mechanics, biochemistry

Contact information

Coordinator

  • dr. Jocelyne Vreede

Contact the course coordinator for questions.