School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
PLoS Comput Biol. 2009 Dec;5(12):e1000627. doi: 10.1371/journal.pcbi.1000627. Epub 2009 Dec 24.
Natural proteins often partake in several highly specific protein-protein interactions. They are thus subject to multiple opposing forces during evolutionary selection. To be functional, such multispecific proteins need to be stable in complex with each interaction partner, and, at the same time, to maintain affinity toward all partners. How is this multispecificity acquired through natural evolution? To answer this compelling question, we study a prototypical multispecific protein, calmodulin (CaM), which has evolved to interact with hundreds of target proteins. Starting from high-resolution structures of sixteen CaM-target complexes, we employ state-of-the-art computational methods to predict a hundred CaM sequences best suited for interaction with each individual CaM target. Then, we design CaM sequences most compatible with each possible combination of two, three, and all sixteen targets simultaneously, producing almost 70,000 low energy CaM sequences. By comparing these sequences and their energies, we gain insight into how nature has managed to find the compromise between the need for favorable interaction energies and the need for multispecificity. We observe that designing for more partners simultaneously yields CaM sequences that better match natural sequence profiles, thus emphasizing the importance of such strategies in nature. Furthermore, we show that the CaM binding interface can be nicely partitioned into positions that are critical for the affinity of all CaM-target complexes and those that are molded to provide interaction specificity. We reveal several basic categories of sequence-level tradeoffs that enable the compromise necessary for the promiscuity of this protein. We also thoroughly quantify the tradeoff between interaction energetics and multispecificity and find that facilitating seemingly competing interactions requires only a small deviation from optimal energies. We conclude that multispecific proteins have been subjected to a rigorous optimization process that has fine-tuned their sequences for interactions with a precise set of targets, thus conferring their multiple cellular functions.
天然蛋白质通常参与多种高度特异性的蛋白质-蛋白质相互作用。因此，它们在进化选择过程中受到多种相反力量的影响。为了发挥功能，这种多特异性蛋白质需要在与每个相互作用伙伴的复合物中稳定，同时保持对所有伙伴的亲和力。这种多特异性是如何通过自然进化获得的？为了回答这个引人入胜的问题，我们研究了一种典型的多特异性蛋白质，钙调蛋白（CaM），它已经进化到与数百种靶蛋白相互作用。从十六个 CaM-靶标复合物的高分辨率结构开始，我们采用最先进的计算方法来预测最适合与每个单独的 CaM 靶标相互作用的一百个 CaM 序列。然后，我们设计最适合与两个、三个和所有十六个靶标同时组合的 CaM 序列，生成近 70000 个低能量 CaM 序列。通过比较这些序列及其能量，我们深入了解了自然界如何在需要有利的相互作用能量和多特异性之间取得平衡。我们观察到，同时为更多的伙伴进行设计会产生更好地匹配自然序列特征的 CaM 序列，从而强调了这种策略在自然界中的重要性。此外，我们表明 CaM 结合界面可以很好地划分为对所有 CaM-靶标复合物的亲和力至关重要的位置和那些为提供相互作用特异性而塑造的位置。我们揭示了几种基本的序列级权衡类别，这些类别使这种蛋白质的混杂性所必需的折衷成为可能。我们还彻底量化了相互作用能量学和多特异性之间的权衡，并发现促进看似竞争的相互作用只需要从最佳能量稍微偏离。我们得出的结论是，多特异性蛋白质已经经历了严格的优化过程，为与精确的靶标集相互作用而微调了它们的序列，从而赋予了它们多种细胞功能。
