Molecular Interaction Maps and Analysis of Bioregulatory

近年来，关于调节细胞生长的分子的知识呈指数级增长，但我们理解这些详细信息的能力却没有增长。此外，虽然染色质是细胞周期信号传导的主要靶点，但关于细胞如何在染色质水平上对这些信号做出反应，我们知之甚少。我们的研究通过分析决定DNA复制的位点和时间的分子因素来探索这个缺失的环节。有关这些研究的更多详细信息，请参见项目1（哺乳动物细胞中的DNA复制研究）的描述。与此同时，我们也在共同努力描绘控制哺乳动物细胞周期的细胞信号网络。 为了更多地了解生物调控网络如何控制正常细胞和癌细胞的细胞周期，我们与一个跨学科的团队合作，生成电子分子相互作用图，显示正常生长期间和干扰细胞周期的条件下细胞周期调控途径的行为。这些努力有助于开发组织大量事实的生物信息学工具，包括相互作用的调控分子，多蛋白质复合物，蛋白质修饰（例如磷酸化）等网络的描述。 组织分子知识的主要障碍之一是缺乏一种共同语言，使科学家能够以清晰，标准化，最好是计算机可读的格式整合数据。为此，我们实现了分子相互作用图（MIM）语言，这是一种由Kurt Kohn首先提出的图解注释，它以图表（分子相互作用图或MIM）的形式编码分子信息。这些MIM用于表示和分析分子相互作用，就像电路图用于电子设备故障排除一样。 研究人员通常用卡通图来描述生物化学途径，但这些分子相互作用的表示往往是不完整和模糊的。例如，两个组分之间的箭头可以表示量的增加、活性的增加或一个分子被另一个分子修饰。此外，生物调节网络中的酶通常是其他酶的底物，并且分子通常会进行改变其结合或酶促能力的修饰。此外，调节蛋白可以形成多分子复合物，其具有不同的活性，这取决于它们的组成和修饰。最后，调节分子内的每个结构域可以具有其自身的结合、修饰和/或酶功能。因此，分子的活性和相互作用能力可能取决于其修饰状态，以及它可能结合的其他分子。为了充分理解系统，必须考虑所有这些相互作用。 在MIM语言中，我们使用少量定义明确的图形符号来描绘每种类型的分子相互作用。每个分子都在图中的一个位置表示，分子之间的相互作用由连接线末端的箭头或条指定。由于修饰的分子和多分子复合物可能具有与原始分子不同的性质，因此每个相互作用的结果（例如磷酸化分子或多分子复合物）被描绘为相互作用线上的圆圈或“节点”。这些节点的处理方式允许它们形成更多的交互并扩展网络。该语言中使用的符号和约定，以及MIM的示例，可以在我们的网站上访问：http://discover.nci.nih.gov/mim和一篇描述MIM语言原理的文章。 图形MIM语言允许同时查看涉及任何给定分子的许多相互作用。它可以描绘竞争的相互作用，这在生物调节网络中很常见。

Knowledge about molecules that regulate cell growth has increased exponentially in recent years, but our ability to make sense of this detailed information has not. Moreover, although chromatin is a major target for cell cycle signaling, very little is known about how cells respond to these signals at the chromatin level. Our studies probe into this missing link through the analysis of molecular factors that determine the site and the timing of DNA replication. More details about these studies are provided in the description of Project 1, DNA replication studies in mammalian cells. In parallel, we are engaged in a collaborative effort to depict cellular signaling networks that control the mammalian cell cycle. To learn more about how bio-regulatory network control the cell cycle in normal and cancer cells, we collaborate with a crossdisciplinary team to generate electronic molecular interaction maps, which show the behavior of cell cycle regulatory pathways during normal growth and under conditions that perturb the cell cycle. These efforts help develop bioinformatics tools that organize large collections of facts, including descriptions of networks of interacting regulatory molecules, multi-protein complexes, protein modifications (e.g. phosphorylations), etc.. One of the main stumbling blocks to organizing molecular knowledge is the lack of a common language that allows scientists to integrate data in a clear, standardized, and preferably computer-readable format. To that end, we implemented the Molecular Interaction Map (MIM) language, a diagrammatic annotation first proposed by Kurt Kohn, which encodes molecular information in the form of diagrams (molecular interaction maps or MIMs). These MIMs are used to represent and analyze molecular interactions in the same way as circuit diagrams are used to trouble-shoot electronic devices. Investigators usually describe biochemical pathways in cartoon-like diagrams, but these representations of molecular interactions are often incomplete and ambiguous. For example, an arrow between two components could signify an increase in quantity, an increase in activity, or a modification of one molecule by the other. In addition, enzymes in bioregulatory networks are often substrates of other enzymes, and molecules are often subject to modifications that change their binding or enzymatic capabilities. Moreover, regulatory proteins can form multi-molecular complexes, which have different activities, depending on their composition and modifications. Finally, each domain within regulatory molecules may have its own binding, modification, and/or enzymatic functions. Thus, a molecule's activity and interaction capabilities may depend on its modification state, and on the other molecules to which it may be bound. All of these interactions must be taken into account for a full understanding of the system. In the MIM language, we use a small number of defined unambiguous graphical symbols to portray each type of molecular interaction. Each molecule is represented in a single place in a diagram, and interactions between molecules are specified by arrows or bars at the end of connecting lines. Because modified molecules and multi-molecular complexes may have different properties than the original molecules, the outcome of each interaction (such as a phosphorylated molecule, or a multi-molecular complex) is depicted as a circle, or "node" on an interaction line. These nodes are treated in a way that allows them to form more interactions and extend the network. The symbols and conventions used in the language, as well as examples of MIMs, can be accessed at our website: http://discover.nci.nih.gov/mim and in an article describing the principles of the MIM language. The graphical MIM language allows a simultaneous view of many interactions involving any given molecule. It can portray competing interactions, which are common in bioregulatory networks.