PDF(Pubmed)
Abstract：
Mutations in protein active sites can dramatically improve function. The active site, however, is densely packed and extremely sensitive to mutations. Therefore, some mutations may only be tolerated in combination with others in a phenomenon known as epistasis. Epistasis reduces the likelihood of obtaining improved functional variants and dramatically slows natural and lab evolutionary processes. Research has shed light on the molecular origins of epistasis and its role in shaping evolutionary trajectories and outcomes. In addition, sequence- and AI-based strategies that infer epistatic relationships from mutational patterns in natural or experimental evolution data have been used to design functional protein variants. In recent years, combinations of such approaches and atomistic design calculations have successfully predicted highly functional combinatorial mutations in active sites. These were used to design thousands of functional active-site variants, demonstrating that, while our understanding of epistasis remains incomplete, some of the determinants that are critical for accurate design are now sufficiently understood. We conclude that the space of active-site variants that has been explored by evolution may be expanded dramatically to enhance natural activities or discover new ones. Furthermore, design opens the way to systematically exploring sequence and structure space and mutational impacts on function, deepening our understanding and control over protein activity.
摘要：
蛋白质活性位点的突变可以显着改善功能。活跃的网站，然而,密集堆积，对突变极其敏感。因此,某些突变可能仅与其他突变一起被耐受，这种现象被称为上位症。Epitasis降低了获得改善的功能变体的可能性，并显着减慢了自然和实验室进化过程。研究揭示了上位性的分子起源及其在塑造进化轨迹和结果中的作用。此外,基于序列和AI的策略从自然或实验进化数据中的突变模式推断上位性关系已用于设计功能性蛋白质变体。近年来,这些方法和原子设计计算的组合已经成功地预测了活性位点中的高功能组合突变。这些被用来设计成千上万的功能性活性位点变体，证明了这一点,虽然我们对上位的理解仍然不完整，一些对精确设计至关重要的决定因素现在已被充分理解。我们得出的结论是，通过进化探索的活性位点变体的空间可能会大大扩展，以增强自然活动或发现新的活动。此外，设计为系统地探索序列和结构空间以及突变对功能的影响开辟了道路，加深我们对蛋白质活性的理解和控制。
