Free Energy Simulations in Soft Matter and Biomolecular Physics
This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective
PH8130 is a semester module
which is offered irregularly.
This Module is included in the following catalogues within the study programs in physics.
- Subject-Related Qualification Modules for Doctoral Candidates in Physics (Seminars)
If not stated otherwise for export to a non-physics program the student workload is given in the following table.
|Total workload||Contact hours||Credits (ECTS)|
Responsible coordinator of the module PH8130 is Martin Zacharias.
- Overview of classical atomistic Molecular Dynamics (MD) simulations and the computer-assisted determination of biomolecular binding free energies
- Hands-on exercises for calculating a binding free energy with
* Alchemical methods
* Pathway methods (Umbrella sampling and non-equilibrium pulling)
After successful completion of the module the students are able to plan, setup and perform free energy calculations using MD simulations. The students will know the theoretical basis, methodology, advantages and disadvantages of the most important methods for the calculation of a (bio)molecular binding free energy with MD simulations. They can independently carry out and analyze binding free-energy calculations for a target-ligand complex using a common MD simulation package and can assess the reliability of the results. Finally, they can report the results in a manner compatible with publication in a research journal.
list of all the learning outcome:
1. Understanding the theory and practice of free energy simulations
2. Setup of computer simulations of large biomolecular systems
3. Anaylsis of MD simulations
4. Extraction of free energy changes and other thermodynamic quantities
5. Setup of alchemical changes in MD simulations
6. Calculation of relative and absolute binding free energies
- Basic knowledge in classical mechanics and statistical thermodynamics, familiarity with Unix-like operating systems and shell scripting and/or python programming are of advantage.
Courses and Schedule
Learning and Teaching Methods
Learning and Teaching Methods:
- Introductory powerpoint presentation including interactive explanations on the blackboard or virtual whiteboard
- Hands-on computer exercises
- Working in small teams
- Interactive discussion and immediate feedback
Powerpoint presentation, blackboard or virtual whiteboard, written instructions in the form of a tutorial booklet
- Reference manual for the employed simulation package (will be provided as a download/link)
- D. Frenkel, B. Smit, Understanding Molecular Simulation: From Algorithms to Applications, Academic Press. 2014
- Mark E. Tuckerman, Statistical Mechanics: Theory and Molecular Simulation, Oxford Graduate Press, 2016
Description of exams and course work