An adaptive coarse graining method for signal transduction in three dimensions.

IF 0.4 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Michelle N Archuleta, Jason E McDermott, Jeremy S Edwards, Haluk Resat
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引用次数: 0

Abstract

The spatio-temporal landscape of the plasma membrane regulates activation and signal transduction of membrane bound receptors by restricting their two-dimensional mobility and by inducing receptor clustering. This regulation also extends to complex formation between receptors and adaptor proteins, which are the intermediate signaling molecules involved in cellular signaling that relay the received cues from cell surface to cytoplasm and eventually to the nucleus. Although their investigation poses challenging technical difficulties, there is a crucial need to understand the impact of the receptor diffusivity, clustering, and spatial heterogeneity, and of receptor-adaptor protein complex formation on the cellular signal transduction patterns. Building upon our earlier studies, we have developed an adaptive coarse-grained Monte Carlo method that can be used to investigate the role of diffusion, clustering and membrane corralling on receptor association and receptor-adaptor protein complex formation dynamics in three dimensions. The new Monte Carlo lattice based approach allowed us to introduce spatial resolution on the 2-D plasma membrane and to model the cytoplasm in three-dimensions. Being a multi-resolution approach, our new method makes it possible to represent various parts of the cellular system at different levels of detail and enabled us to utilize the locally homogeneous assumption when justified (e.g., cytoplasmic region away from the cell membrane) and avoid its use when high spatial resolution is needed (e.g., cell membrane and cytoplasmic region near the membrane) while keeping the required computational complexity manageable. Our results have shown that diffusion has a significant impact on receptor-receptor dimerization and receptor-adaptor protein complex formation kinetics. We have observed an "adaptor protein hopping" mechanism where the receptor binding proteins may hop between receptors to form short-lived transient complexes. This increased residence time of the adaptor proteins near cell membrane and their ability to frequently change signaling partners may explain the increase in signaling efficiency when receptors are clustered. We also hypothesize that the adaptor protein hopping mechanism can cause concurrent or sequential activation of multiple signaling pathways, thus leading to crosstalk between diverse biological functions.

三维信号转导的自适应粗粒化方法。
细胞膜的时空格局通过限制膜结合受体的二维迁移和诱导受体聚集来调节膜结合受体的激活和信号转导。这种调节也延伸到受体和接头蛋白之间的复杂形成,接头蛋白是参与细胞信号传递的中间信号分子,将接收到的信号从细胞表面传递到细胞质并最终传递到细胞核。尽管他们的研究面临着具有挑战性的技术困难,但仍然需要了解受体扩散性、聚类和空间异质性以及受体-接头蛋白复合物形成对细胞信号转导模式的影响。在我们早期研究的基础上,我们开发了一种自适应粗粒度蒙特卡罗方法,可用于在三维空间中研究扩散、聚类和膜聚集在受体结合和受体-接头蛋白复合物形成动力学中的作用。新的基于蒙特卡罗晶格的方法使我们能够在二维质膜上引入空间分辨率,并在三维空间中模拟细胞质。作为一种多分辨率方法,我们的新方法可以在不同的细节水平上表示细胞系统的各个部分,并使我们能够在合理的情况下使用局部均匀假设(例如,细胞质区域远离细胞膜),并避免在需要高空间分辨率时使用它(例如,细胞膜和细胞质区域靠近细胞膜),同时保持所需的计算复杂性可管理。我们的研究结果表明,扩散对受体-受体二聚化和受体-接头蛋白复合物形成动力学有显著影响。我们观察到一种“衔接蛋白跳跃”机制,即受体结合蛋白可以在受体之间跳跃,形成短暂的瞬态复合物。这种接合蛋白在细胞膜附近停留时间的增加以及它们频繁改变信号伙伴的能力可能解释了当受体聚集时信号效率的增加。我们还假设接头蛋白跳跃机制可以引起多个信号通路的并发或顺序激活,从而导致不同生物功能之间的串扰。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Fundamenta Informaticae
Fundamenta Informaticae 工程技术-计算机:软件工程
CiteScore
2.00
自引率
0.00%
发文量
61
审稿时长
9.8 months
期刊介绍: Fundamenta Informaticae is an international journal publishing original research results in all areas of theoretical computer science. Papers are encouraged contributing: solutions by mathematical methods of problems emerging in computer science solutions of mathematical problems inspired by computer science. Topics of interest include (but are not restricted to): theory of computing, complexity theory, algorithms and data structures, computational aspects of combinatorics and graph theory, programming language theory, theoretical aspects of programming languages, computer-aided verification, computer science logic, database theory, logic programming, automated deduction, formal languages and automata theory, concurrency and distributed computing, cryptography and security, theoretical issues in artificial intelligence, machine learning, pattern recognition, algorithmic game theory, bioinformatics and computational biology, quantum computing, probabilistic methods, algebraic and categorical methods.
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