Cyclization specificity in terpene synthases by residue interaction networks

酶对生命是必不可少的，对旨在生产日常药物、生物燃料和精细化学品的工业生物技术努力至关重要。对酶功能的全面了解将使我们能够充分利用酶来成功地适应不断变化和不确定的世界。我们通过关注发生化学反应的活性部位，不断在我们对酶功能的理解上取得重大进展。然而，在定向进化实验中，很好地证明了外层突变(远离活性部位的酶结构区域)极大地提高了催化活性。尽管蛋白质的外层结构明显对酶的功能产生了深刻的影响，但这一点仍然知之甚少；我们目前的知识主要依赖于基于结构的回溯性分析，而进行的调查有限。从我自己对自然进化的萜烯合成酶的研究中，我发现外层突变对于化学反应的特异性是必不可少的。这些研究的结果表明，外层通过蛋白质结构中的网络连接与活性部位进行通信，类似于通过互联网连接的计算机。将折叠蛋白质看作一个网络，这个方案将利用成熟的图论工具，这是描述连通性的数学分支，从蛋白质结构的网络分析中预测重要的外层残基位置。此外，我们将应用基于结构的组合蛋白质工程收集的新酶‘重新连接’外层连接，开始系统地询问我们的预测。此外，这项工作将产生丰富的数据集，以促进我们对酶的基础知识，并产生新的‘部件’，用于合成生物学和工业生物技术应用。

Enzymes are essential to life and critical for industrial biotechnology efforts aimed at producing everyday pharmaceuticals, biofuels, and fine chemicals. A complete understanding of enzyme function will enable us to fully exploit enzymes to successfully adapt to an ever changing and uncertain world. We are continually making major strides in our understanding of enzyme function through focusing on the active site where the chemical reactions occur. However, it is well documented in directed evolution experiments that outer tier mutations (regions of the enzyme structure distant from the active site) greatly enhance catalytic activity. Although outer tiers of protein structure clearly exert profound influence on enzyme function, this remains poorly understood; our current knowledge rests largely on retrospective structure-based analysis while limited investigations have been conducted. From my own investigations of naturally evolved terpene synthases, enzymes that make diverse bioactive natural products, I discovered that outer tier mutations were essential for the specificity of a chemical reaction. Results from theses studies indicate that the outer tier 'communicates' to the active site through network connections in the protein structure, akin to computers linked through the Internet. Considering a folded protein as a network, this proposal will exploit well-developed graph theory tools, a branch of math to describe 'connectivity', to predict important outer tier residue positions from network analysis of protein structure. Further, we will apply structure-based combinatorial protein engineering collections of new enzymes that 'rewire' outer tier connections to begin to systematically interrogate our predictions. In addition, this work will produce rich data sets to advance our fundamental knowledge of enzymes and generate new 'parts' for synthetic biology and industrial biotechnology applications.