Mathematical Models of the Cell Division Cycle

摘要 细胞分裂周期的主要事件，DNA合成和有丝分裂，是由“细胞周期蛋白依赖性激酶”（CDK）触发的：一个酶家族，其活性和特异性取决于它们与各种细胞周期蛋白的结合。 CDK活性也通过磷酸化和与抑制性蛋白的结合来调节。 这些调节蛋白在复杂的生化反应和反馈信号网络中相互作用，以产生细胞周期的有序进展。 到目前为止，这种调控系统的特征一直是还原论的：将网络分解为组成部分，并确定哪些部分相互作用。 严格的数学方法正在开发，以组装成一个完整的调节系统的连贯模型，使预测可以与生物体的生理学和遗传学的实验观察进行定性比较。使用动力系统理论的标准方法，研究人员正在构建全面，准确和预测。 酵母细胞和青蛙胚胎细胞周期的数学模型。 人类基因组计划承诺提供丰富的信息流，关于基因和蛋白质，管理我们所有的生理事务。作为对基因组分析（存储和检索，序列比较，结构预测）的“信息”方面的广泛研究的补充，该项目解决了一个新层次的“动力学”问题：分子如何在时间和空间中相互作用，以产生活细胞的有组织的功能行为？适当的数学和计算工具来回答这个问题正在开发的一个特定的生理问题的背景下：细胞生长和分裂。 了解细胞增殖是如何调控的，不仅是基础科学的一个令人满意的成就，也是临床医学的一个突破。 当启动或抑制细胞分裂的信号被理解时，抑制癌细胞增殖或诱导神经细胞再生的方法将变得更加明显。 这项工作由计算生物学（BIO），信号转导（BIO）和数学生物学（MPS）计划资助。

ABSTRACT The major events of the cell division cycle, DNA synthesis and mitosis, are triggered by 'cyclin-dependent kinases' (CDK's): a family of enzymes whose activity and specificity depend on their binding to various cyclins. CDK activity is also regulated by phosphorylation and by binding to inhibitory proteins. These regulatory proteins interact with each other in a complex web of biochemical reactions and feedback signals, to generate an orderly progression of the cell cycle. So far, characterization of this regulatory system has been reductionistic: breaking the network into its constituent pieces and determining which pieces interact. Rigorous mathematical methods are being developed to assemble the pieces into a coherent model of the intact regulatory system, so that predictions can be compared qualitatively with experimental observations about the physiology and genetics of the organisms. Using standard methods of dynamical systems theory, the investigators are constructing comprehensive, accurate, and predictive. Mathematical models of the cell cycle in yeast cells and frog embryos. The human genome project promises to deliver a rich stream of information about the genes and proteins that govern all our physiological affairs. Complementing extensive research on the 'informational' aspects of genome analysis (storage and retrieval, sequence comparison, structural predictions) this project addresses a new level of 'dynamical' questions: how do molecules interact with one another in time and space to produce the organized, functional behavior of living cells? Appropriate mathematical and computational tools to answer this question are being developed in the context of a specific physiological problem: cell growth and division. To understand how cell proliferation is regulated would not be only a satisfying achievement of basic science but also a breakthrough for clinical medicine. When the signals that initiate or suppress cell division are understood, the means to restrain the proliferation of cancer cells or to induce the regeneration of nerve cells will become more apparent. This work is being funded by the Computational Biology (BIO), Signal Transduction (BIO), and Mathematical Biology (MPS) Programs.