ENZYME ACTIVE SITE TEMPLATES

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 巴比特小组是鉴定酶超家族的先驱， 也就是说，在进化上远距离相关的一组蛋白质 具有几乎无法检测到的序列相似性，但具有相同的架构和功能的某些方面。我们正在比较蛋白质家族和超家族之间的结构和基于结构的可观察性，目的是更好地理解序列和结构是如何受到限制的。 我们正在识别3D基序或活性位点模板，这是一组小残基的空间排列，可以诊断蛋白质家族或超家族的成员身份。除了研究已知的超家族外，我们还希望对尚未得到很好描述的相关蛋白质组进行表征。 这项工作使用了Chimera和其他可在当地和RBVI网站上获得的序列和结构分析工具。我们根据需要与Chimera开发团队合作，以进一步研究并促进有用的研究软件的创建。 我们在烯醇酶和卤代酸活性中心模板方面的初步工作 脱卤酶超家族已在蛋白质中发表(见下文)。最近，我们自动发现在任何一组相关蛋白质之间共享的3D基序的方法已发表在《生物信息学》杂志上。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The Babbitt group has been a pioneer in identifying enzyme superfamilies, that is, groups of proteins that are distantly evolutionarily related and share nearly undetectable sequence similarity, but that share an architecture and certain aspects of their function. We are comparing structures and observables based on structure among and between families and superfamilies of proteins, with the goal of better understanding how sequence and structure are constrained. We are identifying 3D motifs or active site templates, spatial arrangements of small sets of residues that can be diagnostic of membership in a family or superfamily of proteins. Besides studying known superfamilies, we also wish to characterize sets of related proteins that have not already been well described. Chimera and other sequence and structure analysis tools available locally and on the RBVI web site are employed in this work. We collaborate with the Chimera development team as needed to further the research and facilitate the creation of useful research software. Our initial work on active site templates for the enolase and haloacid dehalogenase superfamilies has been published in Proteins (see below). More recently, our method to automatically discover 3D motifs shared among any group of related proteins has been published in Bioinformatics.