Department of Chemistry and Biochemistry, University of California, Santa Barbara, California 93106, USA.
J Am Chem Soc. 2012 Feb 15;134(6):2876-9. doi: 10.1021/ja209850j. Epub 2012 Feb 6.
Biomolecular recognition has long been an important theme in artificial sensing technologies. A current limitation of protein- and nucleic acid-based recognition, however, is that the useful dynamic range of single-site binding typically spans an 81-fold change in target concentration, an effect that limits the utility of biosensors in applications calling for either great sensitivity (a steeper relationship between target concentration and output signal) or the quantification of more wide-ranging concentrations. In response, we have adapted strategies employed by nature to modulate the input-output response of its biorecognition systems to rationally edit the useful dynamic range of an artificial biosensor. By engineering a structure-switching mechanism to tune the affinity of a receptor molecule, we first generated a set of receptor variants displaying similar specificities but different target affinities. Using combinations of these receptor variants (signaling and nonsignaling), we then rationally extended (to 900000-fold), narrowed (to 5-fold), and edited (three-state) the normally 81-fold dynamic range of a representative biosensor. We believe that these strategies may be widely applicable to technologies reliant on biorecognition.
生物分子识别长期以来一直是人工传感技术的一个重要主题。然而,基于蛋白质和核酸的识别的一个当前限制是,单个结合位点的有用动态范围通常跨越目标浓度的 81 倍变化,这种效应限制了生物传感器在需要高灵敏度(目标浓度与输出信号之间的关系更陡峭)或更广泛浓度定量的应用中的实用性。作为回应,我们采用了自然界用来调节其生物识别系统的输入-输出响应的策略,以合理地编辑人工生物传感器的有用动态范围。通过设计一种结构切换机制来调节受体分子的亲和力,我们首先生成了一组显示相似特异性但不同目标亲和力的受体变体。然后,我们使用这些受体变体的组合(信号和非信号),合理地扩展(至 900000 倍)、缩小(至 5 倍)和编辑(三态)了代表性生物传感器的通常 81 倍的动态范围。我们相信,这些策略可能广泛适用于依赖生物识别的技术。