Prepared by: Samar Kamal Kassim
Module name: Structural Bioinformatics
Contact hours (to be used as a guide): Total (40 hrs), Theory (50%), Practical (50%)
SPECIFIC OUTCOMES ADDRESSED
Structural bioinformatics has been defined as the science of examining the structure and function of genes and proteins through the use of computational analysis, statistics, and pattern recognition.
By the end of this module, students should have gained the following skills:
- Achieve solid understanding of the scope of structural bioinformatics and drug design.
- Understand basic and advanced techniques of protein visualization.
- Learn how to access new information and how to assimilate it into the whole, in order to continue to learn beyond the limits of this course.
Knowledge and Understanding
- Students will understand fundamental principles of structural bioinformatics and how to apply computational methods to interpret biological structural information.
- Students will be aware of the range of applications of structural bioinformatics to molecular biology, clinical medicine, pharmacology, biotechnology, agriculture, forensic science, drug design and other disciplines.
- The role of computers and computer science in the investigations and applications of the data.
- Students will understand the language of both experimental biologist and computing scientists, and will be able to bridge the gap between them in the context of structural bioinformatics.
- Students will understand how sequence-structure relationships form the bridge to protein structure.
- Students will be able to perform basic analyses of structural models of proteins.
- Students will be able to Describe the principles and limitations of protein modeling.
Professional and Practical Skills
- Students will acquire useful knowledge of the techniques and data analysis methods and be able to find such resources on the web.
- Students will have acquired basic skills in information retrieval, data calculations, and the ability to extend these skills by self-directed ‘field work’ on the web.
- Students will be able to describe major methods of acquiring protein structural data.
- Students will be able to compare proteins by superimposing (overlaying) their structures.
- Students will be able to find or construct 3D models of structurally unknown proteins.
- Students will be able to make publication-quality images of protein structures.
- Students will be able to make simple molecular animations.
General and Transferable Skills
- Students will be able to hold discussions among partners from various background (biologists, statisticians, and computer professionals) involved in bioinformatics
- Students will know how to use the web and other resources for gene and protein surveys.
BACKGROUND KNOWLEDGE REQUIRED
BOOKS AND OTHER SOURCES USED
Jenny Gu & Philip E. Bourne (eds) 2009, Structural Bioinformatics. ISBN: 978-0-470-18105-8. 1096 pages. April 2009, Wiley-Blackwell.
A) Theory lectures
1. Defining Structural Bioinformatics? 2 hours
- Why do we care about 3D macromolecular structure?
- What are 3D structure data?
- Where do 3D structure data come from?
- How much 3D structure knowledge do we have?
- Primary and Derived 3D Structure Databases
2. Fundamentals of protein structure. 4 hours
- Central dogma: DNA -> RNA -> Protein
- 20 Amino acids: Codon = 3 nucleotides; 4 nucleotides3 = 64 codons; 3 letters vs 1 letter. Chemical properties: i. Polar, uncharged (cf. water), ii.Charged, iii.Hydrophobic (aliphatic vs. aromatic)
- Polypeptide chain geometry and steric restrictions: Planarity of the Peptide Bonds; Phi/Psi angles and steric collisions; Ramachandran Plots; Pro (helix breaking), Gly (turns).
- Covalent bonds: lengths and angles nearly constant
- Non-covalent bonds: variable lengths and angles: Salt bridges (up to 4.0 Å in proteins); Hydrogen bonds (2.5-3.5 Å in proteins); Cation-pi orbital interactions (up to 6.0 Å in proteins); van der Waals interactions (up to 4.5 Å in proteins)
- Primary, Secondary, Tertiary, Quaternary Protein Structures.
- Protein folds cannot be reliably predicted from sequence alone (using ab initio theory).
3. Fundamentals of DNA and RNA structures. 2 hours
4. Molecular Visualization. 2 hours
5. Identifying structure domains in proteins. 2 hours
6. Inferring protein function from structure. 2 hours
7. Prediction of protein-protein interaction from structure evolutionary information. 2 hours
8. Principles and methods of docking and ligand design. 2 hours
9. The future: Structural genomics. 2 hours
B) Practical component
- 1. Finding published molecules of interest (general, basic) 4 hours
- Atlas of MacroMolecules: atlas.molviz.org
- PDB at a Glance
- Search at pdb.org.
- 2. X-ray diffraction or Nuclear Magnetic Resonance? (follows lecture 1-4) 4 hours
- The experimental method (X-ray diffraction or Nuclear Magnetic Resonance?) and resolution (if X-ray) or number of models (if NMR).
(Proteopedia gives the resolution beneath the molecule for X-ray crystallographic results, or the number of models for NMR results.)
- 3. Seeing 3D protein molecules: (follows lectures 1-4) 4 hours
“The structure of H5N1 avian influenza neuraminidase suggests new opportunities for drug design”, Russell et al., Nature 443:45 (September 7, 2006).
- First, obtain the PDB identification codes for the molecules of interest.
- At Proteopedia.Org, enter the PDB code in the search slot and click Go.
- For more detailed exploration, while looking at the molecule in Proteopedia, click on the link to FirstGlance under Resources beneath the molecule.
- o Optional: How to use Jmol
- 4. Visualizing Protein Evolution: (follows lecture 5) 4 hours
- 5. Publication-Quality Molecular Images (follows lecture 6-10) 4 hours
- Polyview-3D is easy to use.
- It makes beautiful static images that are ideal for scientific papers or Powerpoint.
- It also makes animations (rotating molecules) that play in Powerpoint slides or web pages.
- Optional 3D Molecular Visualization Resources
- Top Five 3D Molecular Visualization Technologies.
- MolviZ.Org has a wide range of educational and research tools.
ASSESSMENT ACTIVITIES AND THEIR WEIGHTS
Assessment 1: Midterm exam. Week 5
Assessment 2: Final exam. Week 10
Weighting of Assessments
Class discussion participation 5%
Homework (exercises, reading assignments) 10%
Practical work 10%
Individual presentations 15%
Mid-term Examination 20%
Final-term Examination 40%
Other types of assessment 0 %