Exploring the evolution of novel enzyme functions within structurally defined protein superfamilies.
Exploring the evolution of novel enzyme functions within structurally defined protein superfamilies.
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DOI：
10.1371/journal.pcbi.1002403
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发表时间：
2012
影响因子：
4.3
通讯作者：
Thornton JM
中科院分区：
文献类型：
--
作者：
Furnham N;Sillitoe I;Holliday GL;Cuff AL;Laskowski RA;Orengo CA;Thornton JM
为了了解酶反应的进化和获得生物催化的概述，我们将序列和结构数据结合起来，在分析276个结构上定义的酶超家族中生成系统发育树，并使用这些来研究酶的功能是如何进化的。我们详细描述了两个超家族的分析，以说明酶进化的不同范式。收集所有超家族的数据支持并发展了这样一种观察，即它们都进化到作用于不同的底物，而新化学的进化则不太常见。尽管如此，通过汇集如此多的数据，我们可以对功能中最常见和最罕见的变化类型提供一个全面的概述。我们的分析在比先前研究更大的范围内证明，总体化学修饰仍然发生，在酶委员会（E.C.）分类的初级水平上观察到或多或少的所有可能的变化。系统发育树描绘了一个超家族的进化路线，以及一个超家族中所有可能的变化。这已被用于生成从一种酶功能到另一种酶功能的观察交换矩阵，揭示了酶进化的规模和性质，以及e.c类之间和内部的某些类型的交换比其他类型更普遍。令人惊讶的是，所有已知酶的功能中有很大一部分（71%）是由这相对较小的276个超家族完成的。这加强了一种假设，即相对较少的古老酶结构域超家族是生命所需的大多数化学物质的祖先。酶作为生物催化剂，对生命至关重要。了解酶是如何进化来进行各种各样的反应的，这是广泛的生物学研究的基础，尤其是那些导致新疗法的研究。揭示新酶功能的进化需要结合蛋白质结构、序列、系统发育和化学（从相互作用的小分子和反应机制方面）的信息。我们已经制定了一项综合这些广泛数据的协议，我们已将其应用于由一些非常不同的亲属组成的相对较多的家庭。这使我们能够对新酶功能的进化进行初步概述，其中我们观察到亲属之间功能的一些变化比其他变化更常见，而在自然界中观察到的大多数功能仅限于相对较少的家族。此外，我们能够确定在一个超家族内将酶功能从一种反应改变为另一种反应的进化途径。这些信息可能有助于预测尚未通过实验表征的酶的功能，以及为工业和医疗目的设计新的酶。
In order to understand the evolution of enzyme reactions and to gain an overview of biological catalysis we have combined sequence and structural data to generate phylogenetic trees in an analysis of 276 structurally defined enzyme superfamilies, and used these to study how enzyme functions have evolved. We describe in detail the analysis of two superfamilies to illustrate different paradigms of enzyme evolution. Gathering together data from all the superfamilies supports and develops the observation that they have all evolved to act on a diverse set of substrates, whilst the evolution of new chemistry is much less common. Despite that, by bringing together so much data, we can provide a comprehensive overview of the most common and rare types of changes in function. Our analysis demonstrates on a larger scale than previously studied, that modifications in overall chemistry still occur, with all possible changes at the primary level of the Enzyme Commission (E.C.) classification observed to a greater or lesser extent. The phylogenetic trees map out the evolutionary route taken within a superfamily, as well as all the possible changes within a superfamily. This has been used to generate a matrix of observed exchanges from one enzyme function to another, revealing the scale and nature of enzyme evolution and that some types of exchanges between and within E.C. classes are more prevalent than others. Surprisingly a large proportion (71%) of all known enzyme functions are performed by this relatively small set of 276 superfamilies. This reinforces the hypothesis that relatively few ancient enzymatic domain superfamilies were progenitors for most of the chemistry required for life. Enzymes, as biological catalysts, are crucial to life. Understanding how enzymes have evolved to perform the wide variety of reactions found across all kingdoms of life is fundamental to a broad range of biological studies, especially those leading to new therapeutics. To unravel the evolution of novel enzyme function requires combining information on protein structure, sequence, phylogeny and chemistry (in terms of interacting small molecules and reaction mechanisms). We have developed a protocol for integrating this wide range of data, which we have applied to a relatively large number of families comprising some very diverse relatives. This has permitted us to present an initial overview of the evolution of novel enzyme functions, in which we observe that some changes in function between relatives are more common than others, with most of the functionality observed in nature confined to relatively few families. Moreover, we are able to identify the evolutionary route taken within a superfamily to change the enzyme function from one reaction to another. This information may help in predicting the function of an enzyme that has yet to be experimentally characterised as well as in designing new enzymes for industrial and medical purposes.
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影响因子：
6.8
作者：
Dessailly, Benoit H.;Redfern, Oliver C.;Cuff, Alison;Orengo, Christine A.
通讯作者：
Orengo, Christine A.
影响因子：
12.3
作者：
Brown, Shoshana D;Gerlt, John A;Seffernick, Jennifer L;Babbitt, Patricia C
通讯作者：
Babbitt, Patricia C
影响因子：
14.9
作者：
UniProt Consortium
通讯作者：
UniProt Consortium
影响因子：
4.8
作者：
Heinemeyer, W;Fischer, M;Wolf, DH
通讯作者：
Wolf, DH
影响因子：
14.9
作者：
Holliday GL;Almonacid DE;Bartlett GJ;O'Boyle NM;Torrance JW;Murray-Rust P;Mitchell JB;Thornton JM
通讯作者：
Thornton JM