About this course
Description of content
Computational structural biology is a mature field of research whose contribution to life sciences is becoming increasingly more appreciated. The aim of this course is to provide a solid basis of computational structural biology methods, with an emphasis on practical protein modelling and simulation, to interested MSc and PhD students in the life sciences. Further, given the lack of emphasis on practical computational research in MSc and PhD courses, this course is designed to have a smooth learning curve regarding the GNU/Linux environment and its command-line interface. By the end of the course, the students are expected to master the three major computational structural biology methods – homology modelling, molecular dynamics, and protein docking – not only from a user perspective but also from a theoretical standpoint.
The course is scheduled to last three-weeks with in the first two weeks theoretical lectures (including some exercises) in the morning (9:00-12:00) and practical sessions in the afternoon (13:15–17:00). The students are required to summarize the results of the computer practicals by writing a short article in the form of a communication for the Journal of the American Chemical Society. In the second week of the course a guest lecture giving an industry perspective to the topic will be organised. The third week is reserved for the article writing, self study and the final exam. The first afternoon is devoted to the installation of the material and a short crash-course on GNU/Linux and the command-line interface.
The** theoretical part** consists of classical lectures (see programme above) covering the various aspect of computational modelling of biomolecular systems, together with a few exercises sessions integrated within the lectures. These exercises are meant to illustrate some aspects of the methodology discussed. Through a number of simple python scripts, students will be able to play with some of the techniques discussed, and visualize the impact of various parameters on the simulation results. The material for the lectures is based in parts on the following book (recommended for further in depth reading): A.E. Leach, Molecular Modelling: Principles and Applications, 2nd edition, Pearson Eduction Ltd, 2001.
PDF of the lecture slides will be provided after each lecture.
The computer practical part [1] is divided in three main modules, each focused on a major computational structural biology method. The philosophy of the practical components of the course follows also our previous experience: the students are given a set of instructions and follow them at their own pace, with the assistants helping out whenever necessary. An additional module demonstrating the use of AI (AlphaFold) for structure is provided.
The first module comprises the setup and analysis of a molecular dynamics simulation of a small peptide and is based on our previous BSc course and peer-reviewed educational article published in Biochemistry and Molecular Biology Education [2]. The students will make use of GROMACS [3], a widely used software for molecular dynamics simulation, to characterize the conformational landscape of a small peptide and extract representatives that will be used in the third and last module.
The second module covers homology modelling and guides the students throughout all the stages of the process of building a protein model from a structurally characterized homologue. It makes use SWISSMODEL [4] for model building, and Pymol [5] for visualization. The students will use the programs’ command-line interface instead of the readily available web servers. This, we hope, will familiarize them with an important component of computational research, as well as bring them closer to the tools and their many options.
The third module covers the docking of the homology model built in the second module with the peptide conformers extracted from the simulation of the first module. The students will use bioinformatics interface predictors and HADDOCK web servers [6] to predict the interface between the two molecules and build models of their interaction by data-driven docking.
The “bonus” module illustrate the use of AlphaFold, an artificial intelligence-based structure prediction method working directly from sequence.
References:
https://www.bonvinlab.org/education/molmod_online/
Rodrigues JPGLM, Melquiond ASJ, Bonvin AMJJ (2015). Molecular Dynamics characterization of the conformational landscape of a small peptide. Biochemistry and Molecular Biology Education. 44 , 160-167 (2016).
Course Programme
Day 1:
Morning (lecture): General Introduction, empirical force fields, derivatives
(Based on Leach Ch. 4.1-4.6, 4.9.2, 4.9.11, 4.10.1-4.10.3, 4.15, 4.16, 4.18)
Afternoon (computer practical): Software installation, getting acquainted with Linux
Day 2:
Morning (lecture): Homology modelling and structure validation
Afternoon (computer practical): Homology modelling module
Day 3:
Morning (lecture): Potential energy surfaces, energy minimization methods (Based on Leach Ch. 5.1-5.7)
Afternoon (computer practical): Molecular Dynamics practical module
Day 4:
Morning (lecture): Classical mechanics, molecular dynamics, integration schemes practical aspects. (Based on Leach Ch. 7.1-7.3.4, 6.4, 7.4)
Afternoon (computer practical): Molecular Dynamics practical module
Day 5:
Morning (lecture): Practical aspects, solvent treatment, long-range forces, dealing with T and P
Afternoon (computer practical): Molecular Dynamics practical module - MD simulations must be production ready at the end of this day to run over the weekend on HPC resources
Day 6:
Morning (lecture): Analysis and other sampling methods (Based on Leach Ch. 6.6, 6.9, 7.6, 8.1-8.7, 9.1-9.4, 9.9.1, 9.9.2)
Afternoon (computer practical): Molecular Dynamics practical module (analysis)
Day 7:
Morning (lecture): Docking I – general introduction, information-driven docking
Afternoon (computer practical): Docking practical module
Day 8:
Morning (lecture): Docking II – advanced topics
Afternoon (computer practical): Docking practical module
Day 9:
Morning (lecture): AI-based structure prediction
Afternoon: Practical module
Day 10-15:
Morning: self-study and report writing
Afternoon: self-study and report writing
Day 11:
Afternoon: Q&A session
Exam on Day 13 in week 3 (Wednesday)
Literature/study material used :
Recommended book for further in depth reading: A.E. Leach, Molecular Modelling: Principles and Applications, 2nd edition, Pearson Eduction Ltd, 2001.
For the computer practicals:
The source of the material for the computer practical is available online, free of costs at https://www.bonvinlab.org/education/molmod_online/ . The practical consists of three modules.
Registration : Via OSIRIS
Mandatory for students in Master’s programme : NO.
Optional for students in other Master’s programmes GS-LS : YES.
Learning outcomes
At the end of the course, students should have a profound understanding of:
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molecular modelling and its applications in life sciences
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the choices one has to make to model a system properly and how to describe and model interactions between particles
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the modelling techniques used in this field of research, in particular homology modelling, molecular dynamics simulations and biomolecular docking
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modelling of biochemical systems on computers using different software
After completing the course the student is able:
- to choose the best modelling method for a given application
- to generate 3D models of proteins from sequence information
- to study the conformational landscape of molecules with molecular simulations
- to model the interaction between biomolecules
- to use relevant modelling software under a Linux environment
- to critically analyse modelling results
Good to know
Do you study at Eindhoven University of Technology (TU/e) or Wageningen University and Research (WUR)? You can enrol via eduXchange.nl
Required prior knowledge
You must meet the following requirements
- Assigned study entrance permit for the master
Link to more information
- CreditsECTS 4.5
- Levelmaster
- Contact coordinator