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11.3
Exercises for Chap. 11
Task 11.1
Describe how a linear RNA code becomes a three-dimensional protein structure.
Task 11.2
Describe how to bioinformatically perform protein structure analysis.
Task 11.3
Name methods for predicting a protein structure from a sequence.
Task 11.4
What is a Ramachandran Plot and what can I use it for?
Conclusion
• The design principles of a cell are derived from molecular biology: The flow of
genetic information follows from the genome via RNA to individual proteins.
This can be deciphered bioinformatically in detail by sequence analyses and
more elaborate methods. Regulation, particularly through control of gene expres
sion, is an important design principle that is bioinformatically analyzed through
analyses of RNA and statistical analyses of gene expression, upon which network
analyses are then built. Protein and drug design use protein building principles.
• The localization of proteins, their transport and secretion are also precisely
encoded in the cell and are crucial for the ordered structure of the cell. This can
be elucidated in particular by sequence analyses (localization, secretion, trans
port signals). Modern imaging techniques and advanced imaging software help to
validate these predictions. It is also important to classify all cellular processes by
analyzing the gene ontology. Combined with information on the protein-protein
interactome, the resulting cellular network can be traced using software such as
CellDesigner or Cytoscape. For example, motor proteins and the actin-myosin
cytoskeleton are crucial for cell movement.
• An orderly metabolism is important. Its “design” is quickly queried via databases
such as KEGG or calculated more precisely via metabolic modelling (e.g. with
YANA or Metatool). Complex signalling networks are important for fast reac
tions (stress response, chemotaxis in bacteria) and especially for multicellularity
(cell differentiation, tumorigenesis, embryology, inflammatory processes, ner
vous system). These are modelled in detail with dynamic modelling (see Chaps.
5 and 9), but can also be clearly described with the aid of protein networks and,
taking the processes into account, with the aid of gene ontology.
11.3 Exercises for Chap. 11