School of Biological Sciences, Seoul National University, Seoul 08826, Korea.
These authors contributed equally to this work.
Mol Cells. 2022 Jul 31;45(7):444-453. doi: 10.14348/molcells.2022.0035. Epub 2022 Jun 27.
Multivalent macromolecular interactions underlie dynamic regulation of diverse biological processes in ever-changing cellular states. These interactions often involve binding of multiple proteins to a linear lattice including intrinsically disordered proteins and the chromosomal DNA with many repeating recognition motifs. Quantitative understanding of such multivalent interactions on a linear lattice is crucial for exploring their unique regulatory potentials in the cellular processes. In this review, the distinctive molecular features of the linear lattice system are first discussed with a particular focus on the overlapping nature of potential protein binding sites within a lattice. Then, we introduce two general quantitative frameworks, combinatorial and conditional probability models, dealing with the overlap problem and relating the binding parameters to the experimentally measurable properties of the linear lattice-protein interactions. To this end, we present two specific examples where the quantitative models have been applied and further extended to provide biological insights into specific cellular processes. In the first case, the conditional probability model was extended to highlight the significant impact of nonspecific binding of transcription factors to the chromosomal DNA on gene-specific transcriptional activities. The second case presents the recently developed combinatorial models to unravel the complex organization of target protein binding sites within an intrinsically disordered region (IDR) of a nucleoporin. In particular, these models have suggested a unique function of IDRs as a molecular switch coupling distinct cellular processes. The quantitative models reviewed here are envisioned to further advance for dissection and functional studies of more complex systems including phase-separated biomolecular condensates.
多价大分子相互作用是细胞状态不断变化下多种生物过程动态调控的基础。这些相互作用通常涉及多个蛋白质与线性晶格的结合，包括固有无序蛋白质和具有许多重复识别基序的染色体 DNA。在细胞过程中探索这些多价相互作用在线性晶格上的独特调节潜力，定量理解它们是至关重要的。在这篇综述中，首先讨论了线性晶格系统的独特分子特征，特别关注晶格内潜在蛋白质结合位点的重叠性质。然后，我们介绍了两种通用的定量框架，组合和条件概率模型，用于处理重叠问题，并将结合参数与线性晶格-蛋白质相互作用的可实验测量性质联系起来。为此，我们提出了两个具体的例子，其中定量模型已被应用并进一步扩展，以提供对特定细胞过程的生物学见解。在第一个案例中，条件概率模型被扩展，以强调转录因子与染色体 DNA 的非特异性结合对基因特异性转录活性的显著影响。第二个案例介绍了最近开发的组合模型，用于揭示核孔蛋白中无序区域 (IDR) 内靶蛋白结合位点的复杂组织。特别是，这些模型表明 IDR 作为一种分子开关，将不同的细胞过程偶联在一起，具有独特的功能。这里回顾的定量模型被设想为进一步推进更复杂系统的剖析和功能研究，包括相分离的生物分子凝聚物。
