The network of receptors characterize B cell receptor micro- and macroclustering in a Monte Carlo model.

The network of receptors characterize B cell receptor micro- and macroclustering in a Monte Carlo model.
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受体网络表征了蒙特卡罗模型中 B 细胞受体微观和宏观聚类的特征。

DOI:
10.1021/jp9079074
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发表时间:
2010
期刊:
The journal of physical chemistry. B
影响因子:
--
通讯作者:
Raychaudhuri,Subhadip
Raychaudhuri,Subhadip
中科院分区:
--
文献类型:
--
作者:
Reddy,ASrinivas;Chilukuri,Sandeep;Raychaudhuri,Subhadip

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在识别可溶性抗原的过程中,已知B细胞受体(BCR)形成信号簇,其可以关键地调节细胞内活化途径和B细胞应答。对于可溶性抗原,受体簇的确切性质及其形成机制知之甚少。最初的实验表明,B细胞受体首先在与可溶性抗原连接后形成微簇,然后在B细胞的一极粗化成宏观的帽结构。这种相互的受体-受体吸引力可以局部产生,这是由于可溶性抗原的交联以及其他可能性。我们开发了一个基于能量的Monte Carlo模型来研究B细胞受体与可溶性抗原连接后聚集的机制。我们的研究结果表明,最近邻受体对之间的相互吸引可以导致B细胞受体的微聚集,但它是不充分的受体的宏观聚集。一个简单的偏置扩散模型,其中BCR分子经历一个偏向最大的集群定向运动,然后应用,这导致在一个单一的受体分子的macrocluster。使用开发的基于网络的指标,如任何对受体之间的平均距离,分析各种类型的受体簇。
During the recognition of soluble antigens, B cell receptors (BCR) are known to form signaling clusters that can crucially modulate intracellular activation pathways and B cell response. Little is known about the precise nature of receptor cluster and its formation mechanism for the case of soluble antigens. Initial experiments have shown that B cell receptors first microcluster upon ligation with soluble antigens, and then coarsen into a macroscopiccapstructure at one pole of a B cell. Such a mutual receptor−receptor attraction can arise locally due to cross-linking by soluble antigens among other possibilities. We develop an energy based Monte Carlo model to investigate the mechanism of B-cell receptor clustering upon ligation with soluble antigens. Our results show that mutual attraction between nearest neighbor receptor pairs can lead to microclustering of B cell receptors, but it is not sufficient for receptor macroclustering. A simple model of biased diffusion where BCR molecules experience a biased directed motion toward the largest cluster is then applied, which results in a single macrocluster of receptor molecules. The various types of receptor clusters are analyzed using the developed network-based metrics such as the average distance between any pairs of receptors.