Experimentally derived quantitative model of protein evolution

序列的系统发育分析是生物学中一种重要的计算工具。它是理解蛋白质结构和功能的进化、物种形成、基因和谱系之间的关系以及病原体传播的动力学的核心。在生物化学中，它是理解蛋白质结构-功能关系进化的起点。任何系统发育方法的核心都是分子进化的量化模型，它描述了突变的速度和选择的严格性。然而，一个主要的挑战是，广泛使用的编码序列进化的量化模型假设一个基因(或蛋白质)中的所有位置都是独立的和等价的。这两种假设都与蛋白质生物物理学不符。此外，这种转换矩阵适用于所有蛋白质，忽略了蛋白质折叠影响替代矩阵中选择的严格性的事实。该研究计划的长期目标是通过发展分子系统学的新方法来应对这些挑战。一个主要的创新部分是，我们将直接测量蛋白质中每个位置的氨基酸倾向，并将其嵌入系统发育模型中，而不是假设一个替代矩阵或从序列比对中估计它们。 近期，我们将重点研究叶酸合成途径中的核心代谢酶二氢翼酸合成酶(DHPS)。DHPS是一个很好的模型，因为它是磺胺类抗生素的重要靶点，并且遵循Tim-Barrel折叠，这是蛋白质组中最常见的蛋白质折叠类型。首先，我们将通过对每个位点的氨基酸偏好进行高通量测量来确定dhsp的适应度格局。其次，我们将开发一个基于实验得出的替换矩阵的系统发育推断模型。第三，我们将使用新的系统发育推断模型重建DHPs结构-功能关系的进化。虽然我们把重点放在DHPs的短期上，但我们研究计划的长期观点是将这种方法推广到其他蛋白质折叠。事实上，这种方法可能导致一个蛋白质组范围的实验衍生的进化模型。 这一多学科的研究计划将用于培养学生和其他高素质的生物物理、生物化学、分子进化和生物信息学方面的人才。这种广泛的理论和实验培训也可以为学生未来在学术界和工业界的职业生涯提供有价值的培训。

Phylogenetic analysis of sequences is an essential computational tool in biology. It is central to understanding the evolution of protein structure and function, speciation, the relationship among genes and genealogies, and the dynamics of the spread of pathogens. In biochemistry, it is the starting point for understanding the evolution of structure-function relationship in proteins. At the core of any phylogenetics method is a quantitative model of molecular evolution that describes the rate of mutation and the stringency of selection. However, a major challenge is that the widely used quantitative models of coding sequence evolution assume that all sites in a gene (or protein) are independent and equivalent. Both assumptions are inconsistent with protein biophysics. Additionally, this transition matrix is applied to all proteins, ignoring the fact that protein folds affect the stringency of selection in the substitution matrix.The long-term objective of the research program is to address these challenges by developing novel methods in molecular phylogenetics. A major innovative component is that instead of assuming a substitution matrix or estimating them from sequence alignments, we will directly measure the amino acid propensity for each site in the protein and embed it in a phylogenetics model. In the near term, we will focus our methods development on dihydropteroate synthase (DHPS), a core metabolic enzyme in the folate synthesis pathway. DHPS is an excellent model because it is an important target of sulfonamide antibiotics and follows a TIM-barrel fold, the most prevalent type of protein fold in a proteome. First, we will determine the fitness landscape of DHSP by performing high-throughput measurement of the per site amino acid preference. Second, we will develop a phylogenetic inference model based on the experimentally derived substitution matrix. Third, we will reconstruct the evolution of DHPS structure-function relationship using the new phylogenetic inference model. While we focus on DHPS on the short-term, the long-term view of our research program is to generalize this approach to other protein folds. Indeed, this approach could lead to a proteome-wide experimentally derived model of evolution. This multi-disciplinary research program will be used to train students and other highly qualified personnel at the interface of biophysics, biochemistry, molecular evolution, and bioinformatics. This training broad training in both theory and experiment could also provide valuable training for students for their future careers in both academia and industry.