Journal article
Integrated modeling methodology for microtubule dynamics and Taxol kinetics with experimentally identifiable parameters
Computer methods and programs in biomedicine, v 88(1)
2007
PMID: 17707543
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
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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Details
- Title
- Integrated modeling methodology for microtubule dynamics and Taxol kinetics with experimentally identifiable parameters
- Creators
- He Zhao - Drexel UniversityBahrad A. Sokhansanj - Drexel University
- Publication Details
- Computer methods and programs in biomedicine, v 88(1)
- Publisher
- Elsevier Ireland Ltd
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000249650800003
- Scopus ID
- 2-s2.0-34548281204
- Other Identifier
- 991019168741404721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Computer Science, Theory & Methods
- Engineering, Biomedical
- Medical Informatics