Abadias Luciano, Estrada-Rodriguez Gissell, Estrada Ernesto
Departamento de Matemáticas, Facultad de Ciencias Universidad de Zaragoza, 50009 Zaragoza, Spain.
Instituto Universitario de Matemáticas y Aplicaciones, Universidad de Zaragoza, 50009 Zaragoza, Spain.
Fract Calc Appl Anal. 2020;23(3):635-655. doi: 10.1515/fca-2020-0033. Epub 2020 Jul 11.
We propose a model for the transmission of perturbations across the amino acids of a protein represented as an interaction network. The dynamics consists of a Susceptible-Infected (SI) model based on the Caputo fractional-order derivative. We find an upper bound to the analytical solution of this model which represents the worse-case scenario on the propagation of perturbations across a protein residue network. This upper bound is expressed in terms of Mittag-Leffler functions of the adjacency matrix of the network of inter-amino acids interactions. We then apply this model to the analysis of the propagation of perturbations produced by inhibitors of the main protease of SARS CoV-2. We find that the perturbations produced by strong inhibitors of the protease are propagated far away from the binding site, confirming the long-range nature of intra-protein communication. On the contrary, the weakest inhibitors only transmit their perturbations across a close environment around the binding site. These findings may help to the design of drug candidates against this new coronavirus.
我们提出了一个模型,用于描述扰动在表示为相互作用网络的蛋白质氨基酸之间的传播。动力学由基于卡普托分数阶导数的易感-感染(SI)模型组成。我们找到了该模型解析解的一个上界,它代表了扰动在蛋白质残基网络中传播的最坏情况。这个上界用氨基酸间相互作用网络邻接矩阵的米塔格-莱夫勒函数来表示。然后,我们将这个模型应用于分析由严重急性呼吸综合征冠状病毒2(SARS-CoV-2)主要蛋白酶抑制剂产生的扰动的传播。我们发现,蛋白酶强抑制剂产生的扰动会传播到远离结合位点的地方,这证实了蛋白质内通信的长程性质。相反,最弱的抑制剂只会在结合位点周围的紧密环境中传播其扰动。这些发现可能有助于设计针对这种新型冠状病毒的候选药物。