BMB834: Protein structure, dynamics and modelling
Study Board of Science
Teaching language: English
EKA: N210040112, N210040102
Assessment: Second examiner: None, Second examiner: Internal
Grading: Pass/Fail, 7-point grading scale
Offered in: Odense
Offered in: Spring
Level: Master
STADS ID (UVA): N210040101
ECTS value: 5
Date of Approval: 15-05-2023
Duration: 1 semester
Version: Approved - active
Entry requirements
Academic preconditions
Students taking the course are expected to:
- Have basic knowledge of chemistry, biochemistry and molecular biology, including protein biochemistry and protein structure
- Knowledge of basic computational approaches in bioinformatics
- Use computers to retrieve data and software from public repositories
Course introduction
Detailed understanding of protein structure and function is a prerequisite for unravelling biological systems and molecular networks, and for development of new drugs for treatment of diseases. The aim of the course is to enable the student to understand protein structure and related computational techniques to investigate protein structure. This is important in regard to protein function in biological systems, understanding protein interactions, design of protein-targeting drugs and protein-based drugs, and optimization of enzyme activities.
The course builds on the knowledge acquired in: Molecular Biology and Protein Chemistry (BMB832, Conversion class) (or similar) “Fundamentals of bioinformatics” (DM847), Introduction to programming (DM857) (or similar).The course provides an academic basis for conducting computational protein structure analysis, and for studying protein structure-function relationships using computational tools, including macromolecular modelling methods 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:
- Acquire knowledge within the field of structural biology, protein structure and simulation
- Understand and apply common terms and parameters in the context of protein structure analysis
- Interpretation of experimental data using computational methods within the field of protein structure and dynamics
- Understand principles of bioanalytical methods for measurements of protein structure and for determining structural constraints, including X-ray diffraction, NMR spectroscopy, mass spectrometry, calorimetry, scattering, cryoelectron microscopy
- Understand basic principles and applications of High-performance computing for protein structure modelling and simulation
- Perform simple protein structure modelling/simulation experiments using computational tools and be familiar with the underlying theory
Give skills to:
- Embark in studies of protein structure and function using computational resources and tools.
- Read and understand scientific literature on protein structure modelling and simulations
- Select and apply proper computational tools for investigations of specific aspects of protein structure
Give knowledge and understanding of the importance of protein structure-function relationships in the context of biology, biomedicine and drug development
Expected learning outcome
The learning objectives of the course is that the student demonstrates the ability to:
- Use scientific terminology to describe protein structure and protein structure-function relationships,and be able to present this information in written reports, discussions and presentations.
- Describe the biochemical forces underlying protein folding, stability and interactions.
- Describe the bioanalytical methods presented in the course.
- Describe the computational methods presented in the course.
- Apply computational methods for protein structure retrieval and visualization.
- Apply High performance computing (HPC) methods for protein structure modelling
- Describe docking methods for studying protein-ligand complexes
- Apply the methods to simple problems presented in the course.
- Apply the methods to situations different from the ones presented in the course;
- Reflect on and assess design of computational pipelines for protein structure analysis.
- Learning methods and report the results.
In relation to the competence profile of the degree it is the explicit focus of the course to give the competence to:
- Appreciate the importance of protein structure analysis in biology, biomedicine and in drug development and optimization
- Critically assess and select appropriate computational tools for protein structure analysis
- Apply simple computational methods and algorithms to investigate protein structure and protein-ligand interactions
Content
The following main topics are contained in the course:
- Fundamentals of protein biochemistry and protein structure
- Protein structure databases
- Algorithms and computer software for protein structure analysis
- Data visualization methods
- Bioanalytical techniques for protein structure analysis
- Protein interactions
- Aspects of High performance computing
- Molecular mechanics methods for protein modelling
- Analysis of molecular mechanics trajectories. Constraint based protein modelling
- Docking
- Homology modelling
Literature
Examination regulations
Prerequisites for participating in the exam element a)
Timing
Spring
Tests
Mini-projects and reports during the course
EKA
N210040112
Assessment
Second examiner: None
Grading
Pass/Fail
Identification
Full name and SDU username
Language
English
Examination aids
To be announced during the course
ECTS value
0
Additional information
The prerequisite examination is a prerequisite for participation in exam element a)
Exam element a)
Timing
Spring
Prerequisites
| Type | Prerequisite name | Prerequisite course |
|---|---|---|
| Examination part | Prerequisites for participating in the exam element a) | N210040101, BMB834: Protein structure, dynamics and modelling |
Tests
Oral examination
EKA
N210040102
Assessment
Second examiner: Internal
Grading
7-point grading scale
Identification
Student Identification Card
Language
English
Duration
25 minutes
Examination aids
To be announced during the course
ECTS value
5
Additional information
Exam consists of a final oral exam based on review of scientific article and topics/reports prepared during the course.
Indicative number of lessons
Teaching Method
At the faculty of science, teaching is organized after the three-phase model ie. intro, training and study phase.
- Intro phase (lectures) - 20 hours
- Training phase: 30 hours, including 18 hours tutorials and 12 hours laboratory
The teaching follows the three-phase model. The intro phase consists primarily of lectures which will introduce the students to the general topics and themes within protein structure and structure analysis with computer and software algorithms. The tutorials and lab exercises (computer exercises), will follow up on the lectures/intro phase and will go into depth with a number of examples. The students will here work with specific problems and questions, and are expected to formulate hypotheses. The students are expected to work independently, either individually or in smaller groups. The study phase consists of preparation, reading scientific papers and writing mini projects.
Educational activities:
- Reading text book
- Reading articles
- Discussions in groups
- Preparation for computational exercises / programming
- Mini-projects
Teacher responsible
| Name | Department | |
|---|---|---|
| Ole Nørregaard Jensen | jenseno@bmb.sdu.dk | Institut for Biokemi og Molekylær Biologi |
Additional teachers
| Name | Department | City | |
|---|---|---|---|
| Himanshu Khandelia | hkhandel@sdu.dk | Institut for Fysik, Kemi og Farmaci | |
| Jacob Kongsted | kongsted@sdu.dk | Institut for Fysik, Kemi og Farmaci |
Timetable
Administrative Unit
Team at Educational Law & Registration
Offered in
Recommended course of study
| Profile | Education | Semester | Offer period |
|---|---|---|---|
| MSc major in Computational Biomedicine - registration 1 September 2021, 2022 and 2023 | | Odense | 2 | E23 |
Transition rules
Transitional arrangements describe how a course replaces another course when changes are made to the course of study.
If a transitional arrangement has been made for a course, it will be stated in the list.
See transitional arrangements for all courses at the Faculty of Science.