ABI Innovation: Co-evolution of domains, genes and species: models, algorithms, and software

卡耐基梅隆大学获得了一个奖项，用于开发多结构域蛋白质家族的进化模型、算法和软件。 这些家族通过结构域的插入、复制和缺失而进化，结构域是编码作为蛋白质功能的构建块的离散结构单元的序列。 新结构域组合的出现推动了蛋白质家族中执行核心分子功能的功能变异和相互作用特异性的进化。 多域家庭在整个生命中至关重要。 在细菌中，多结构域家族编码双组分激酶信号系统，该系统是细胞通信的骨干。 在真核生物中，多结构域家族涉及组织修复、细胞死亡、炎症反应、抗原识别和先天免疫。 该项目将开发一个计算框架，用于重建多结构域家族的进化历史，包括产生当今蛋白质的结构域事件，它们进化的祖先结构域架构，以及描述整个家族历史的树。 这个新的框架将包括一个正式的，基于事件的模型的多域家庭进化;算法推断域事件和祖先域的内容，一个给定的家庭;和这些算法在原型软件中的实现推理和可视化的多域蛋白质的历史。 因为这种方法考虑了域序列和域内容，并结合了一个明确的事件模型，它保证了准确性和细节的显着增加。 该项目的结果将使进化生物学家能够研究蛋白质进化的过程，实验室生物学家能够确定适当的实验目标，细胞生物学家能够通过进化分析补充实验结果。 该项目将通过为本科生课程、研究生课程和关于“在少数民族学校发展生物信息学方案”的讲习班编写关于多领域进化的教材，为教育资源作出贡献。“这个为期一周的研讨会是匹兹堡超级计算中心在少数民族服务机构开发新的生物信息学项目的一部分。该项目还将为本科生和研究生提供生物学和计算机科学之间接口的研究培训。

An award is made to Carnegie Mellon University to develop evolutionary models, algorithms, and software for multidomain protein families. These families evolve through the insertion, duplication, and deletion of domains, sequences that encode discrete structural units that are the building blocks of protein function. The emergence of novel domain combinations drives the evolution of functional variation and interaction specificity in protein families that perform core molecular functions. Multidomain families are of central importance throughout life. In bacteria, multidomain families encode the two-component kinase signaling systems that are the back-bone of cellular communication. In eukaryotes, multidomain families are implicated in tissue repair, cell death, inflammation response, antigen recognition, and innate immunity. This project will develop a computational framework for reconstructing the evolutionary history of a multidomain family, including the domain events that gave rise to present-day proteins, the ancestral domain architectures from which they evolved, and a tree describing the history of the family as a whole. This new framework will comprise a formal, event-based model of multidomain family evolution; algorithms for inferring domain events and the ancestral domain content of a given family; and an implementation of these algorithms in prototype software for inference and visualization of multidomain protein histories. Because this approach considers domain sequence, as well as domain content, and incorporates an explicit model of events, it promises a dramatic increase in accuracy and detail. The results of this project will enable evolutionary biologists to investigate the processes of protein evolution, bench biologists to identify appropriate experimental targets, and cell biologists to complement experimental results with evolutionary analyses. This project will contribute to educational resources through the development of teaching materials on multidomain evolution for an undergraduate course, a graduate course, and a workshop on "Developing Bioinformatics Programs at Minority Schools." This one week workshop is part of a Pittsburgh Supercomputing Center initiative to develop new bioinformatics programs at minority-serving institutions. This project will also provide research training for undergraduate and graduate students at the interface between biology and computer science.