BMB834: Protein structure, dynamics and modelling
Comment
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
prerequisite for unravelling biological systems and molecular networks,
and for development of new drugs for treatment of diseases.
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.
acquired in:Molecular Biology and Protein Chemistry (BMB832, Conversion
class) (or similar) “Fundamentals of bioinformatics” (DM847),
Introduction to programming (DM857) (or similar).
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.
- 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
- 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
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
Tests
Mini-projects and reports during the course
EKA
Assessment
Grading
Identification
Language
Examination aids
To be announced during the course
ECTS value
Additional information
The prerequisite examination is a prerequisite for participation in exam element a)
Exam element a)
Timing
Prerequisites
Type | Prerequisite name | Prerequisite course |
---|---|---|
Examination part | Prerequisites for participating in the exam element a) | N210040101, BMB834: Protein structure, dynamics and modelling |
Tests
Final oral exam based on review of scientific article and topics/reports prepared during the course
EKA
Assessment
Grading
Identification
Language
Examination aids
To be announced during the course
ECTS value
Additional information
Indicative number of lessons
Teaching Method
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