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Win, Lose, or Tie: Mathematical Modeling of Ligand Competition at the Cell-Extracellular Matrix Interface.

ABSTRACT: Integrin transmembrane proteins conduct mechanotransduction at the cell-extracellular matrix (ECM) interface. This process is central to cellular homeostasis and therefore is particularly important when designing instructive biomaterials and organoid culture systems. Previous studies suggest that fine-tuning the ECM composition and mechanical properties can improve organoid development. Toward the bigger goal of fully functional organoid development, we hypothesize that resolving the dynamics of ECM-integrin interactions will be highly instructive. To this end, we developed a mathematical model that enabled us to simulate three main interactions, namely integrin activation, ligand binding, and integrin clustering. Different from previously published computational models, we account for the binding of more than one type of ligand to the integrin. This competition between ligands defines the fate of the system. We have demonstrated that an increase in the initial concentration of ligands does not ensure an increase in the steady state concentration of ligand-bound integrins. The ligand with higher binding rate occupies more integrins at the steady state than does the competing ligand. With cell type specific, quantitative input on integrin-ligand binding rates, this model can be used to develop instructive cell culture systems.

SUBMITTER: Karagoz Z

PROVIDER: S-EPMC8117103 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Mathematical Modeling of Ligand Competition at the Cell–Extracellular Matrix Interface

Project description:Modeling the competition of two ligands which have the ability to bind to the same receptor. Example is given from ECM proteins fibronectin and von Willebrand factor and their common receptor integrin alpha v beta 3.

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Different isoforms of Maxwell´s Demon, a conserved cell membrane protein, mediate lose/win decisions during cell competition

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2011-02-09 | E-GEOD-21230 | biostudies-arrayexpress

Different isoforms of Maxwell´s Demon, a conserved cell membrane protein, mediate lose/win decisions during cell competition

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Mathematical modeling of Trypanosoma brucei transcription

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Mathematical modeling of Trypanosoma brucei transcription

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May the Best Molecule Win: Competition ESI Mass Spectrometry.

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Win-stay-lose-learn promotes cooperation in the prisoner's dilemma game with voluntary participation.

Project description:Voluntary participation, demonstrated to be a simple yet effective mechanism to promote persistent cooperative behavior, has been extensively studied. It has also been verified that the aspiration-based win-stay-lose-learn strategy updating rule promotes the evolution of cooperation. Inspired by this well-known fact, we combine the Win-Stay-Lose-Learn updating rule with voluntary participation: Players maintain their strategies when they are satisfied, or players attempt to imitate the strategy of one randomly chosen neighbor. We find that this mechanism maintains persistent cooperative behavior, even further promotes the evolution of cooperation under certain conditions.

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Dynamic aspiration based on Win-Stay-Lose-Learn rule in spatial prisoner's dilemma game.

Project description:Prisoner's dilemma game is the most commonly used model of spatial evolutionary game which is considered as a paradigm to portray competition among selfish individuals. In recent years, Win-Stay-Lose-Learn, a strategy updating rule base on aspiration, has been proved to be an effective model to promote cooperation in spatial prisoner's dilemma game, which leads aspiration to receive lots of attention. In this paper, according to Expected Value Theory and Achievement Motivation Theory, we propose a dynamic aspiration model based on Win-Stay-Lose-Learn rule in which individual's aspiration is inspired by its payoff. It is found that dynamic aspiration has a significant impact on the evolution process, and different initial aspirations lead to different results, which are called Stable Coexistence under Low Aspiration, Dependent Coexistence under Moderate aspiration and Defection Explosion under High Aspiration respectively. Furthermore, a deep analysis is performed on the local structures which cause defectors' re-expansion, the concept of END- and EXP-periods are used to justify the mechanism of network reciprocity in view of time-evolution, typical feature nodes for defectors' re-expansion called Infectors, Infected nodes and High-risk cooperators respectively are found. Compared to fixed aspiration model, dynamic aspiration introduces a more satisfactory explanation on population evolution laws and can promote deeper comprehension for the principle of prisoner's dilemma.

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Win-Stay-Lose-Shift as a self-confirming equilibrium in the iterated Prisoner's Dilemma.

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