High-affinity biomolecular interactions are modulated by low-affinity binders.

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY NPJ Systems Biology and Applications Pub Date : 2024-08-10 DOI:10.1038/s41540-024-00410-z
S Mukundan, Girish Deshpande, M S Madhusudhan
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Abstract

The strength of molecular interactions is characterized by their dissociation constants (KD). Only high-affinity interactions (KD ≤ 10-8 M) are extensively investigated and support binary on/off switches. However, such analyses have discounted the presence of low-affinity binders (KD > 10-5 M) in the cellular environment. We assess the potential influence of low-affinity binders on high-affinity interactions. By employing Gillespie stochastic simulations and continuous methods, we demonstrate that the presence of low-affinity binders can alter the kinetics and the steady state of high-affinity interactions. We refer to this effect as 'herd regulation' and have evaluated its possible impact in two different contexts including sex determination in Drosophila melanogaster and in signalling systems that employ molecular thresholds. We have also suggested experiments to validate herd regulation in vitro. We speculate that low-affinity binders are prevalent in biological contexts where the outcomes depend on molecular thresholds impacting homoeostatic regulation.

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高亲和力生物分子相互作用受低亲和力粘合剂的调节。
分子相互作用的强度以其解离常数(KD)为特征。只有高亲和力的相互作用(KD ≤ 10-8 M)才被广泛研究,并支持二元开/关开关。然而,这些分析忽略了细胞环境中低亲和力粘合剂(KD > 10-5 M)的存在。我们评估了低亲和力结合剂对高亲和力相互作用的潜在影响。通过采用 Gillespie 随机模拟和连续方法,我们证明了低亲和力结合剂的存在会改变高亲和力相互作用的动力学和稳定状态。我们将这种效应称为 "群体调节",并评估了它在两种不同情况下可能产生的影响,包括黑腹果蝇的性别决定和采用分子阈值的信号系统。我们还提出了在体外验证群体调节的实验建议。我们推测,低亲和力结合剂普遍存在于生物环境中,其结果取决于影响同态调节的分子阈值。
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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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