The Evolution of Protein Structure, Function, and Folding

该项目的目标，分子生物物理学在分子和细胞生物科学部和理论和计算化学计划在化学部的共同支持下，是开发最好地保存同源蛋白质的系统发育树拓扑结构的进化概况。使用多维QR算法最近开发的初步研究中，非冗余的序列和结构，最好的跨越蛋白质的进化空间的集合将构建从组合的序列和结构比对信息。这些研究的目标将主要是参与翻译机制的蛋白质，核糖体蛋白和氨酰-tRNA合成酶（阿尔斯），它们存在于生命的所有领域。 我们的目标是应用这些进化概况来识别对折叠重要的结构词，并分析蛋白质/RNA结构和序列模式的进化变化。有了结构数据库中25，000多个条目的数据和200多个基因组的完整序列，主要的进化事件现在可以与蛋白质形状和功能的变化相关联。 从这些配置文件中提取的功能也将有助于开发新的检测方法，以改善基因注释。这些配置文件将在 并在蛋白质结构预测算法中进行测试。 使用混合分子动力学模拟，折叠的结构字和相互作用， 将研究几个生命领域的生物体的阿尔斯与tRNA的AARS，并将结果与与实验室合作进行的研究进行比较。 组 从这项工作中获得的信息将加强对结构，功能和折叠之间相互作用的进化和物理原理的理解。在这个项目中开发的概念和方法将被纳入课程，“计算化学生物学”，PI最近在UIUC化学系开发。 本课程针对对化学、生物物理学和计算机科学的研究感兴趣的本科生和一年级研究生。 这种生物信息学进化方法的初步工作 QR算法已经在美国国家科学基金会赞助的两个计算生物学研讨会以及最近在美国和澳大利亚举办的其他几个研讨会上提出。 更多的实践研讨会正在规划中，教程的副本可通过网络获得。 在这个项目中开发的QR算法和进化概况将提供给更广泛的科学界，作为流行的可视化程序VMD的序列和结构生物信息学插件的一部分。

The objective of this project, jointly supported by Molecular Biophysics in the Division of Molecular and Cellular Biosciences and the Theoretical and Computational Chemistry Program in the Chemistry Division, is to develop evolutionary profiles that best preserve the phylogenetic tree topology of homologous proteins. Using a multidimensional QR algorithm recently developed in a preliminary study, non-redundant sets of sequences and structures that best span the evolutionary space of the proteins will be constructed from combined sequence and structural alignment information. The targets of these studies will primarily be the proteins involved in the translational machinery, ribosomal proteins and aminoacyl-tRNA synthetases (AARS), that are present in all domains of life. The goal is to apply these evolutionary profiles to identify structural words important for folding and to analyze evolutionary changes in patterns of structures and sequences governing protein/RNA. With data available from over 25,000 entries in the structural databases and the complete sequences of over 200 genomes, major evolutionary events can now be correlated with changes in shape and function of the proteins. Features extracted from these profiles will also be instrumental in developing new assays for improving gene annotation. These profiles will be implemented and tested in a protein structure prediction algorithm. Using hybrid molecular dynamics simulations, the folding of the structural words and interactions of the AARS with tRNA for organism s from several domains of life will be investigated and the results compared to studies carried out in collaboration with an experimental group. The information obtained from this work will enhance the understanding of the evolutionary and physical principles of interplay between structure, function, and folding.The concepts and methods developed in this project will be incorporated into the course, "Computational Chemical Biology" that the PI has recently developed in the UIUC Chemistry Department. This course is aimed at undergraduates and first-year graduate students interested in research at the interface of chemistry, biophysics, and computer science. The preliminary work on this evolutionary approach to bioinformatics and the QR algorithm has been presented at two NSF sponsored workshops on computational biology as well as several other recent workshops in the US and Australia. More hands-on workshops are in the planning, and copies of the tutorials are made available through the web. The QR algorithms and evolutionary profiles developed in this project will be made available to the broader scientific community as part of a sequence and structure bioinformatics plug-in for the popular visualization program VMD that is freely distributed.