Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.
Swiss Institute of Bioinformatics, Lausanne, Switzerland.
J Mol Evol. 2024 Apr;92(2):104-120. doi: 10.1007/s00239-024-10161-4. Epub 2024 Mar 12.
Virtually all enzymes catalyse more than one reaction, a phenomenon known as enzyme promiscuity. It is unclear whether promiscuous enzymes are more often generalists that catalyse multiple reactions at similar rates or specialists that catalyse one reaction much more efficiently than other reactions. In addition, the factors that shape whether an enzyme evolves to be a generalist or a specialist are poorly understood. To address these questions, we follow a three-pronged approach. First, we examine the distribution of promiscuity in empirical enzymes reported in the BRENDA database. We find that the promiscuity distribution of empirical enzymes is bimodal. In other words, a large fraction of promiscuous enzymes are either generalists or specialists, with few intermediates. Second, we demonstrate that enzyme biophysics is not sufficient to explain this bimodal distribution. Third, we devise a constraint-based model of promiscuous enzymes undergoing duplication and facing selection pressures favouring subfunctionalization. The model posits the existence of constraints between the catalytic efficiencies of an enzyme for different reactions and is inspired by empirical case studies. The promiscuity distribution predicted by our constraint-based model is consistent with the empirical bimodal distribution. Our results suggest that subfunctionalization is possible and beneficial only in certain enzymes. Furthermore, the model predicts that conflicting constraints and selection pressures can cause promiscuous enzymes to enter a 'frustrated' state, in which competing interactions limit the specialisation of enzymes. We find that frustration can be both a driver and an inhibitor of enzyme evolution by duplication and subfunctionalization. In addition, our model predicts that frustration becomes more likely as enzymes catalyse more reactions, implying that natural selection may prefer catalytically simple enzymes. In sum, our results suggest that frustration may play an important role in enzyme evolution.
实际上，几乎所有的酶都能催化不止一种反应，这种现象被称为酶的多功能性。目前还不清楚多功能酶是催化多种反应速度相似的多面手，还是催化一种反应比其他反应效率更高的专家。此外，影响酶是进化为多面手还是专家的因素还知之甚少。为了解决这些问题，我们采用了三管齐下的方法。首先，我们检查了 BRENDA 数据库中报告的经验酶的多功能性分布。我们发现，经验酶的多功能性分布是双峰的。换句话说，很大一部分多功能酶要么是多面手，要么是专家，很少有中间状态。其次，我们证明酶的生物物理学不足以解释这种双峰分布。第三，我们设计了一个基于约束的模型，用于研究经历复制并面临有利于亚功能化选择压力的多功能酶。该模型假设酶对不同反应的催化效率之间存在约束关系，这是受到经验案例研究的启发。我们的基于约束的模型预测的多功能性分布与经验双峰分布一致。我们的结果表明，亚功能化只有在某些酶中才是可能的和有益的。此外，该模型预测，相互冲突的约束和选择压力会导致多功能酶进入“受挫”状态，在这种状态下，竞争相互作用会限制酶的专业化。我们发现，通过复制和亚功能化，挫折既可以成为酶进化的驱动力，也可以成为抑制剂。此外，我们的模型预测，随着酶催化的反应越多，挫折的可能性就越大，这意味着自然选择可能更喜欢催化简单的酶。总之，我们的研究结果表明，挫折可能在酶进化中发挥重要作用。
