A quantitative view of strategies to engineer cell-selective ligand binding.

IF 1.5 4区 生物学 Q4 CELL BIOLOGY Integrative Biology Pub Date : 2021-12-30 DOI:10.1093/intbio/zyab019
Zhixin Cyrillus Tan, Brian T Orcutt-Jahns, Aaron S Meyer
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引用次数: 2

Abstract

A critical property of many therapies is their selective binding to target populations. Exceptional specificity can arise from high-affinity binding to surface targets expressed exclusively on target cell types. In many cases, however, therapeutic targets are only expressed at subtly different levels relative to off-target cells. More complex binding strategies have been developed to overcome this limitation, including multi-specific and multivalent molecules, creating a combinatorial explosion of design possibilities. Guiding strategies for developing cell-specific binding are critical to employ these tools. Here, we employ a uniquely general multivalent binding model to dissect multi-ligand and multi-receptor interactions. This model allows us to analyze and explore a series of mechanisms to engineer cell selectivity, including mixtures of molecules, affinity adjustments, valency changes, multi-specific molecules and ligand competition. Each of these strategies can optimize selectivity in distinct cases, leading to enhanced selectivity when employed together. The proposed model, therefore, provides a comprehensive toolkit for the model-driven design of selectively binding therapies.

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设计细胞选择性配体结合策略的定量观点。
许多疗法的一个关键特性是它们与目标人群的选择性结合。特殊的特异性可以产生高亲和力结合的表面目标表达的目标细胞类型。然而,在许多情况下,治疗靶点仅在相对于脱靶细胞的细微差异水平上表达。为了克服这一限制,已经开发出了更复杂的结合策略,包括多特异性和多价分子,创造了设计可能性的组合爆炸。开发细胞特异性结合的指导策略对于使用这些工具至关重要。在这里,我们采用一种独特的通用多价结合模型来剖析多配体和多受体的相互作用。该模型使我们能够分析和探索一系列机制来设计细胞选择性,包括分子混合物、亲和调节、价变化、多特异性分子和配体竞争。这些策略中的每一种都可以在不同的情况下优化选择性,从而在一起使用时提高选择性。因此,提出的模型为选择性结合疗法的模型驱动设计提供了一个全面的工具包。
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来源期刊
Integrative Biology
Integrative Biology 生物-细胞生物学
CiteScore
4.90
自引率
0.00%
发文量
15
审稿时长
1 months
期刊介绍: Integrative Biology publishes original biological research based on innovative experimental and theoretical methodologies that answer biological questions. The journal is multi- and inter-disciplinary, calling upon expertise and technologies from the physical sciences, engineering, computation, imaging, and mathematics to address critical questions in biological systems. Research using experimental or computational quantitative technologies to characterise biological systems at the molecular, cellular, tissue and population levels is welcomed. Of particular interest are submissions contributing to quantitative understanding of how component properties at one level in the dimensional scale (nano to micro) determine system behaviour at a higher level of complexity. Studies of synthetic systems, whether used to elucidate fundamental principles of biological function or as the basis for novel applications are also of interest.
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