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Integrated modeling methodology for microtubule dynamics and Taxol kinetics with experimentally identifiable parameters
Journal article   Peer reviewed

Integrated modeling methodology for microtubule dynamics and Taxol kinetics with experimentally identifiable parameters

He Zhao and Bahrad A. Sokhansanj
Computer methods and programs in biomedicine, v 88(1)
2007
PMID: 17707543

Abstract

Mathematical modeling Microtubules Paclitaxel Simulation Taxol
Microtubule dynamics play a critical role in cell function and stress response, modulating mitosis, morphology, signaling, and transport. Drugs such as paclitaxel (Taxol) can impact tubulin polymerization and affect microtubule dynamics. While theoretical methods have been previously proposed to simulate microtubule dynamics, we develop a methodology here that can be used to compare model predictions with experimental data. Our model is a hybrid of (1) a simple two-state stochastic formulation of tubulin polymerization kinetics and (2) an equilibrium approximation for the chemical kinetics of Taxol drug binding to microtubule ends. Model parameters are biologically realistic, with values taken directly from experimental measurements. Model validation is conducted against published experimental data comparing optical measurements of microtubule dynamics in cultured cells under normal and Taxol-treated conditions. To compare model predictions with experimental data requires applying a “windowing” strategy on the spatiotemporal resolution of the simulation. From a biological perspective, this is consistent with interpreting the microtubule “pause” phenomenon as at least partially an artifact of spatiotemporal resolution limits on experimental measurement.

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Web of Science research areas
Computer Science, Interdisciplinary Applications
Computer Science, Theory & Methods
Engineering, Biomedical
Medical Informatics
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