Ivanisenko N V, Mishchenko E L, Akberdin I R, Demenkov P S, Likhoshvai V A, Kozlov K N, Todorov D I, Samsonova M G, Samsonov A M, Kolchanov N A, Ivanisenko V A
Biofizika. 2013 Sep-Oct;58(5):758-74.
The hepatitis C virus (HCV) belongs to Flaviviridae family and causes hazardous liver diseases leading frequently to cirrhosis and hepatocellular carcinoma. HCV is able to rapidly acquire drug resistance and for this reason there is currently no effective anti-HCV therapy in spite of appearance of new potential drugs. Mathematical models are relevant to predict the efficacy of potential drugs against virus or host targets. One of the promising targets for development of new drugs is the viral NS3 protease. Here we developed a stochastic model of the subgenomic HCV replicon replication in Huh-7 cells and in the presence of the NS3 protease inhibitors. Along with consideration of the stochastic nature of the subgenomic HCV replicon replication the model takes into account the existence and generation of main NS3 protease drug resistant mutants, namely BILN-2061 (A156T, D168V, R155Q), VX-950 (A156S, A156T, T54A) and SCH-503034 (A156T, A156S, T54A). The model reproduces well the viral RNA kinetics in the cell from the moment of the subgenomic HCV replicon transfection to steady state, as well as the viral RNA suppression kinetics in the presence of NS3 protease inhibitors BILN-2061, VX-950 and SCH-503034. We showed that the resistant mutants should be taken into account for the correct description of biphasic kinetics of the viral RNA suppression. The mutants selected in the presence of different inhibitor concentrations have maximal replication capacity in the given inhibitor concentration range. Our model can be used to interpret the results of the new anti-HCV drug testing in replicon systems, as well as to predict the efficacy of new potential drugs and optimize the regimen of their use.
丙型肝炎病毒(HCV)属于黄病毒科,可引发严重的肝脏疾病,常导致肝硬化和肝细胞癌。HCV能够迅速产生耐药性,因此尽管出现了新的潜在药物,但目前仍没有有效的抗HCV疗法。数学模型有助于预测潜在药物针对病毒或宿主靶点的疗效。新型药物开发的一个有前景的靶点是病毒NS3蛋白酶。在此,我们建立了一个亚基因组HCV复制子在Huh-7细胞中以及存在NS3蛋白酶抑制剂情况下复制的随机模型。该模型除了考虑亚基因组HCV复制子复制的随机性外,还考虑了主要NS3蛋白酶耐药突变体的存在和产生,即BILN-2061(A156T、D168V、R155Q)、VX-950(A156S、A156T、T54A)和SCH-503034(A156T、A156S、T54A)。该模型很好地再现了从亚基因组HCV复制子转染到稳态时细胞内病毒RNA的动力学,以及存在NS3蛋白酶抑制剂BILN-2061、VX-950和SCH-503034时病毒RNA的抑制动力学。我们表明,为了正确描述病毒RNA抑制的双相动力学,应考虑耐药突变体。在不同抑制剂浓度下选择的突变体在给定抑制剂浓度范围内具有最大复制能力。我们的模型可用于解释复制子系统中新型抗HCV药物测试的结果,以及预测新潜在药物的疗效并优化其使用方案。