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Related Concept Videos

Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
Diversity in Cell Signaling Responses01:22

Diversity in Cell Signaling Responses

The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity. 
Graded and Abrupt Responses
Some signaling systems generate...
Amplifying Signals via Enzymatic Cascade01:22

Amplifying Signals via Enzymatic Cascade

When a ligand binds to a cell-surface receptor, the receptor's intracellular domain changes shape, which may either activate its enzyme function or allow its binding to other molecules. The initial signal is amplified by most signal transduction pathways. This means that a single ligand molecule can activate multiple molecules of a downstream target. Proteins that relay a signal are most commonly phosphorylated at one or more sites, activating or inactivating the protein. Kinases catalyze the...
Assembly of Signaling Complexes01:30

Assembly of Signaling Complexes

Multiprotein signaling complexes are formed in a dynamic process involving protein-protein interactions at the cytoplasmic domain of transmembrane receptors or enzymatic and non-enzymatic proteins associated with the receptor. These complexes ensure the activation and propagation of intracellular signals that regulate cell functions.
Interaction domains in cell signaling
Interaction domains recognize exposed features of their binding partners containing post-translationally modified sequences,...
Signal Transduction: Overview01:26

Signal Transduction: Overview

Cells respond to many types of information, often through receptor proteins positioned on the membrane. They respond to chemical signals, such as hormones, neurotransmitters, and other signaling molecules, initiating a series of molecular reactions to produce an appropriate response. This is called signal transduction. Cells also coordinate different responses elicited by the same signaling molecule via mediators, allowing molecular cross-talk.
Typically, signal transduction involves three...
Cell Signaling Feedback Loops01:07

Cell Signaling Feedback Loops

Positive and negative feedback loops are crucial for regulating biological signaling systems. These feedback loops are processes that connect output signals to their inputs.
Negative feedback loops
Most signaling systems have negative feedback loops that can perform different functions such as output limiter, and adaptation.
Output limiter
Upon receiving an input signal, the cellular response rapidly increases until a threshold is reached. Beyond this threshold, a negative feedback loop...

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Spatiotemporal Control of Protein Activity through Optogenetic Allosteric Regulation
08:00

Spatiotemporal Control of Protein Activity through Optogenetic Allosteric Regulation

Published on: October 4, 2024

Modelling the dynamics of signalling pathways.

Sree N Sreenath1, Kwang-Hyun Cho, Peter Wellstead

  • 1Case Complex Systems Biology Center, Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH 44139, U.S.A. n.sreenath@case.edu

Essays in Biochemistry
|September 17, 2008
PubMed
Summary
This summary is machine-generated.

This chapter details methods for modeling, calibrating, and validating cellular signaling pathways. It covers choosing model types, using databases, and system identification for accurate pathway analysis.

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Biochemical Pathway Analysis

Background:

  • Cellular signaling pathways are complex and crucial for biological functions.
  • Accurate modeling of these pathways requires robust methodologies for their dynamics.
  • Understanding pathway interactions is key to deciphering cellular responses.

Purpose of the Study:

  • To present methodologies for modeling, calibration, and validation of cellular signaling pathway dynamics.
  • To guide the selection of appropriate modeling techniques and levels of detail.
  • To illustrate the process with a case study on pathway cross-talk.

Main Methods:

  • Discusses techniques for translating chemical kinetics into mathematical models of biochemical pathways.
  • Explores choices between deterministic/stochastic, discrete/continuous time, and continuous/discrete state models.
  • Covers model calibration using web-based databases and system identification with measured data.

Main Results:

  • Provides a framework for developing and validating mathematical models of cellular signaling.
  • Highlights the importance of selecting appropriate modeling approaches based on available data and research questions.
  • Demonstrates the application of these methods through an analysis of the IL-1/NF-kappaB and TGF-beta/Smad2 pathway cross-talk.

Conclusions:

  • Methodologies for modeling, calibration, and validation are essential for understanding cellular signaling dynamics.
  • The choice of modeling approach significantly impacts the accuracy and interpretability of pathway analysis.
  • Integrated approaches combining computational tools and experimental data yield robust insights into complex biological systems.