LAYING THE FOUNDATIONS FOR GENOMIC ENZYMOLOGY

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。 机械上不同的酶超家族代表着一组不同的蛋白质，它们的底物、产物甚至整体功能可能会有很大的不同。这种差异很大的化学反应的不同进化可以用化学约束的酶进化模型来描述，在该模型中，大自然通过保留基本的化学能力(如部分反应)来重新设计祖先支架以实现各种功能，同时进化底物结合的变化，从而进化出整体化学。这项续期提案有四个目标，它们扩大了上一笔赠款所取得的进展： 1)研究其他机械上不同的酶超家族，以确定催化的传递如何受到每个家族中共同的催化模块的限制。我们还将详细说明如何出现新的催化剂来执行各种功能。我们期望这些结果揭示自然界中利用的酶设计的一般原理，并确定适用于所研究的每个超家族的功能推理和机制理解的特定规则。这些信息将通过我们的结构-功能链接数据库(SFLD)提供给科学界。 2)识别区分特征超家族中亚群/家族的序列/结构差异，以获得比仅通过预测超家族-共同功能获得的更精确的功能推断。 3)调查利用复杂共因子的超级家庭，以了解这些超级家庭与相对更简单的超级家庭有何不同。我们以前研究过的超级家族的类型。这些研究将首先集中在使用FAD辅助因子的超级家庭。 4)为预测混杂和新的化学反应奠定基础，这些反应可以由本提案中研究的催化模块支持。对接方法将用于识别可能结合或可能被超家族成员翻转的小分子。这些结果将被添加到SFLD中，以帮助其他人推断功能，识别在结构表征或药物设计中有用的抑制剂，并指导应用于人类健康的蛋白质工程/设计。

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. Mechanistically diverse enzyme superfamilies represent sets of divergent proteins whose substrates, products and even overall functions can be substantially different. Divergent evolution of such broadly varied chemical reactions can be described by the chemistry-constrained model of enzyme evolution, in which nature re-engineers the ancestral scaffold for a variety of functions by conserving a fundamental chemical capability such as a partial reaction, while evolving variations in substrate binding, and therefore overall chemistry. This renewal proposal has four aims, which extend the progress achieved in the previous grant: 1) Investigate additional mechanistically diverse enzyme superfamilies to determine how the delivery of catalysis is constrained by the common catalytic module in each. We will also detail for each how new catalysts have arisen to perform a variety of functions. We expect the results to reveal general principles of enzyme design utilized in nature and identify specific rules applicable for functional inference and mechanistic understanding for each of the superfamilies investigated. This information will be made available to the scientific community via our ?Structure-Function Linkage Database (SFLD)?. 2) Identify sequence/structural differences that discriminate subgroups/families in characterized superfamilies to achieve more precision in functional inference than can be obtained by prediction of the superfamily-common functions alone. 3) Investigate superfamilies that utilize complex co-factors to learn how such superfamilies differ from the relatively more ?simple? types of superfamilies we have previously studied. These studies will focus first on superfamilies that use FAD cofactors. 4) Lay the groundwork for predicting promiscuity and new chemical reactions that could be supported by the catalytic modules studied in this proposal. Docking methodologies will be used to identify small molecules likely to bind or that could be turned over by superfamily members. The results will be added to the SFLD to aid others in inference of function, identification of inhibitors useful in structural characterization or drug design, and to guide protein engineering/design for applications to human health.