Enzymes have been shaped by evolution over billions of years to catalyse the chemical reactions that support life on earth. Dispersed in the literature, or organised in online databases, knowledge about enzymes can be structured in distinct dimensions, either related to their quality as biological macromolecules, such as their sequence and structure, or related to their chemical functions, such as the catalytic site, kinetics, mechanism, and overall reaction. The evolution of enzymes can only be understood when each of these dimensions is considered. In addition, many of the properties of enzymes only make sense in the light of evolution. We start this review by outlining the main paradigms of enzyme evolution, including gene duplication and divergence, convergent evolution, and evolution by recombination of domains. In the second part, we overview the current collective knowledge about enzymes, as organised by different types of data and collected in several databases. We also highlight some increasingly powerful computational tools that can be used to close gaps in understanding, in particular for types of data that require laborious experimental protocols. We believe that recent advances in protein structure prediction will be a powerful catalyst for the prediction of binding, mechanism, and ultimately, chemical reactions. A comprehensive mapping of enzyme function and evolution may be attainable in the near future.

中文翻译：

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生物信息学视角下的酶功能和进化

酶经过数十亿年的进化而形成，可催化维持地球生命的化学反应。关于酶的知识分散在文献中，或组织在在线数据库中，可以在不同的维度上构建，或者与它们作为生物大分子的质量相关，例如它们的序列和结构，或者与它们的化学功能相关，例如催化位点，动力学、机理和总体反应。只有考虑到这些维度中的每一个维度，才能理解酶的进化。此外，酶的许多特性只有从进化的角度才有意义。我们首先概述酶进化的主要范式，包括基因复制和趋异、趋同进化和域重组进化。在第二部分中，我们概述了当前有关酶的集体知识，这些知识按不同类型的数据组织并收集在多个数据库中。我们还重点介绍了一些日益强大的计算工具，这些工具可用于缩小理解上的差距，特别是对于需要费力的实验协议的数据类型。我们相信，蛋白质结构预测的最新进展将成为预测结合、机制以及最终化学反应的强大催化剂。酶功能和进化的全面图谱可能在不久的将来就能实现。