Signal Transduction
BIO202
Aurnab Ghose; 150121
X1 X2 X3
Signal 1 Signal 2 Signal 3 Signal 4 Signal N
Xm
gene 1 gene 2 gene 3 gene 4 gene 5 gene 6 ... gene k
Environment
Transcription factors
genes
...
...
An environmental sensing mechanism
Wyrick and Young, 2002
Transcription factor activities form the internal representation of the environmental states
The colored circles represent distinct transcriptional activators. The rectangular ovals represent potential target genes The color of the rectangular oval indicates which transcriptional activator is regulating its expression in response to the environmental stimulus; in addition, arrows point from each transcriptional activator to its regulated genes.
What is Signal Transduction?
It is the process of converting signals into responses
i.e., receiving, interpreting, processing, amplifying and responding to information
Signal transduction • Conversion of information from one
form into another
Evolution and Expansion of Intracellular Signaling
Autocrine Paracrine Endocrine
Forms of secreted molecules-mediated signaling
Components of Signal Transduction
SIGNAL
RESPONSE
DISCRIMINATOR
TRANSDUCER
AMPLIFIER
Discriminator
Transducer
Amplifier
Effector
Martin Rodbell applied this analogy to signal transduction in biology
Extracellular signaling molecules fall into 2 classes:
1. Molecules that are too large or too hydrophilic to cross the plasma membrane - rely on membrane receptors
2. Molecules that are small enough or hydrophobic and pass through the membrane - directly activate intracellular enzymes or bind cytosolic receptors
(e.g. NO; steroids)
Cell surface receptors fall into 3 main classes
1. Ion channel-linked receptors
2. G-protein-linked receptors (GPCRs)
3. Enzyme-linked receptors
Cell surface receptors fall into 3 main classes
Major Signal Transduction Pathways
Mitogen Activated Protein Kinase (MAPK) pathway : A typical example
(receptor – ligand interaction)
MAPK signalling cascade
From relatively simple biochemical pathway – How is specificity achieved?
How is sensitivity achieved?
How is reliability achieved (robustness)?
How is pleiotropy in biological function achieved? (integration of multitude of inputs)
Amplitude and duration of the signal flux
Combinatorial integration of network crosstalk Versatility of component function
Pleiotropy of biological function Not possible to have a unique receptor or a signal transduction unit for every input. The structure and the dynamics of the system will matter
Combinatorial integration of network crosstalk Versatility of component function
Protein based information flux in order to act as a signal transduction system requires:
(receptor – ligand interaction)
K1 > K2 > K3 > K4
Allosteric Regulation
The regulation of an enzyme or other protein by the binding of an effector molecule at a site other than the protein's active site.
Koshland’s sequential model
Specificity
Specificity
There is sea of ‘similar’ molecules, then ….
Kinetic Proofreading *
Equilibrium binding considerations suggest ~100x higher error rate
Note: 3-tiered Dual-phosphorylation
Is more better than less?
Why do MAPKs have a 3 tiered structure? Does dual phosphorylation requirement of MAPKs for activation have an advantage?
Sensitivity
- Signal amplification (modest)
- More regulatory interfaces
- Multistep ultrasensitivity
Why do MAPKs have a 3 tiered structure?
Sensitivity
Multistep Ultrasensitivity
Sensitivity Specificity
Noise filtration Switch-like responses for small range of filtered stimuli
Does dual phosphorylation requirement of MAPKs for activation have an advantage?
- Coincidence detection (specificity)
- Ultrasensitivity
Sensitivity Specificity
Regulatory Influences of MAPK pathways
Inhibitory proteins Phosphatases
Sensitivity Specificity
Feedback loops
Sensitivity Specificity Positive feedback loops can enhance sensitivity
(EGF/EGFR > ROS > Inhibition of phosphatases)
Green arrows: activation Red blunt-ended lines: inhibition
Scaffold proteins: localization/specificity
Specificity
MAPK signalling cascade
Specificity
Network view of signal transduction
Patterns of connectivity in “real networks” are called network motif’s
Nodes are signalling proteins Edges: Directed interactions (covalent modification of another protein)
How to find network motif’s in a network? Compare “real” and “randomized” networks (randomized: same # of nodes and edges as real networks but the connections are made randomly)
Network motif‘s are patterns that occur more significantly (statistically) in real than randomized networks Network motif’s are patterns conserved through evolution Mutations can randomly change edges (remove or add) Edges need to be constantly selected in order to prevent randomization
Diamond motif
Seen uniquely in signal transduction networks and not in transcriptional networks
Multi-layer patterns in signalling networks show connections from one layer to the next (no connections two-layers down, for example) Structure is similar to patterns in AI and Artificial neural networks
The question of Integration: can Neural Networks help?
Thickness of arrows indicate connection weight
A neural network trained by evolution! Neural networks can be trained to recognize specific input patterns and generate corresponding specific output patterns
Specificity
Large interactive networks (incl. Neural Networks) display Robustness ie, can maintain function despite external and internal perturbations
Robustness is essential for:
Appropriate communication Generating appropriate response Preventing cellular malfunction
Robustness
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