Application of graph modularity inference to represent protein structures.

蛋白质是大分子，参与了活细胞的大部分工作。我们有能力解决由特定基因编码的蛋白质的形状。然而，它们的三维结构又大又复杂。本研究计划旨在提供新的方法来概念化这些大分子的内部力学。我们首先感兴趣的是了解这些长链如何将自己排列成数量较少的刚性组件或模块。为了做到这一点，我们正在使用分子模拟的尖端分析，也将开发新的分析。我们认为，试图设计蛋白质以实现特定功能应该考虑这种模块化结构。我们还对推断在进化过程中保持稳定的模块感兴趣。这是通过比较许多具有相同祖先的蛋白质的形状来完成的。在进化过程中保持稳定的模块很可能是互补突变网络的结果。由于蛋白质工程通常使用突变来改变蛋白质的功能，因此更好地了解蛋白质中一个位置与其相邻位置的关系可以增加预测突变间接后果的机会。我们通过在网络分析中应用和扩展计算机科学的工作来实现这一点。接下来，我们有兴趣探索进化模块和稳定模块之间的关系。这类知识对于我们进一步了解蛋白质的稳定性和分子水平的进化，以及帮助蛋白质的合理工程设计具有新功能的蛋白质是很重要的。

Proteins are large molecules that are implicated in the majority of the work done in living cells. We have the ability to solve the shape of the protein encoded by a particular gene. However, their three-dimensional structures are large and complex. This research program aims to provide new ways to conceptualize the inner mechanics of these large molecules. We are first interested in understanding how these long chains arrange themselves into a smaller number of rigid components, or modules. To do this, we are using cutting edge analysis of molecular simulations, and also will develop new analyses. We ascribe that attempts to engineer proteins to achieve a particular function should consider this modular structure. We are also interested in inferring modules that are stable over evolutionary time. This is done by comparing the shape of many proteins sharing the same ancestor. Modules that are stable over evolutionary time are likely to be the result of networks of complementary mutations. Since protein engineering is commonly using mutations to alter the function of a protein, understanding better the relation of one position in the protein with respect to its neighbors increases the chance of anticipating the indirect consequences of mutations. We achieve this by applying and extending work in computer science on network analyses. Going forward, we are interested to explore how evolutionary and stability modules are related. This kind of knowledge is important to further our understanding of protein stability, evolution at the molecular level, and to assist in the rational engineering of protein to design proteins capable of novel functions.