An information ratchet improves selectivity in molecular recognition under non-equilibrium conditions

IF 34.9 1区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Benjamin M. W. Roberts, Erica Del Grosso, Emanuele Penocchio, Francesco Ricci, Leonard J. Prins
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引用次数: 0

Abstract

Molecular recognition is essential for controlling chemical processes, passing molecular instructions to elicit responses including structure formation, signalling and replication. Usually, the selectivity of molecular recognition is under thermodynamic control; however, when a higher fidelity is required, nature improves recognition selectivity by an error correction mechanism under an energy-dissipating kinetic-control regime. Here, exploiting DNA hybridization as a model, we present an abiotic example of an information ratchet mechanism that increases selectivity for the ‘correct’ duplex from 2:1 at equilibrium to 6:1 under energy-dissipating conditions. Structural asymmetry in the DNA strands introduces kinetic asymmetry in the reaction network, enabling enrichment under non-equilibrium conditions. We quantify the free-energy cost associated with enhanced selectivity using Shannon entropy formalism, finding that an increase in information of 0.33 bits is associated with at least 3.0 kJ mol−1 of free energy. Moreover, the minimalistic structures of our error reduction system demonstrates that biomachinery is not necessary to increase molecular recognition fidelities above the thermodynamically expected values, thereby pointing a way towards solving Eigen’s paradox.

Abstract Image

信息棘轮提高了非平衡条件下分子识别的选择性
分子识别对于控制化学过程、传递分子指令以引发包括结构形成、信号传导和复制在内的反应至关重要。通常,分子识别的选择性受热力学控制;然而,当需要更高的保真度时,在能量耗散的动力学控制机制下,大自然通过误差校正机制提高了识别选择性。在这里,利用DNA杂交作为模型,我们提出了一个非生物的信息棘轮机制的例子,该机制将“正确”双工的选择性从平衡时的2:1增加到能量耗散条件下的6:1。DNA链的结构不对称引入了反应网络的动力学不对称,使非平衡条件下的富集成为可能。我们使用香农熵形式量化了与选择性增强相关的自由能成本,发现每增加0.33比特的信息至少与3.0 kJ mol−1的自由能相关。此外,我们的误差减少系统的极简结构表明,生物机械并不需要将分子识别保真度提高到热力学期望值以上,从而为解决Eigen悖论指明了一条道路。
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来源期刊
Nature nanotechnology
Nature nanotechnology 工程技术-材料科学:综合
CiteScore
59.70
自引率
0.80%
发文量
196
审稿时长
4-8 weeks
期刊介绍: Nature Nanotechnology is a prestigious journal that publishes high-quality papers in various areas of nanoscience and nanotechnology. The journal focuses on the design, characterization, and production of structures, devices, and systems that manipulate and control materials at atomic, molecular, and macromolecular scales. It encompasses both bottom-up and top-down approaches, as well as their combinations. Furthermore, Nature Nanotechnology fosters the exchange of ideas among researchers from diverse disciplines such as chemistry, physics, material science, biomedical research, engineering, and more. It promotes collaboration at the forefront of this multidisciplinary field. The journal covers a wide range of topics, from fundamental research in physics, chemistry, and biology, including computational work and simulations, to the development of innovative devices and technologies for various industrial sectors such as information technology, medicine, manufacturing, high-performance materials, energy, and environmental technologies. It includes coverage of organic, inorganic, and hybrid materials.
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