Exploring Gatekeeper Mutations in EGFR through Computer Simulations
Exploring Gatekeeper Mutations in EGFR through Computer Simulations
复制标题
DOI：
10.1021/acs.jcim.9b00361
复制
发表时间：
2019-06-01
影响因子：
5.6
通讯作者：
Verma, Chandra S.
中科院分区：
文献类型：
--
作者：
Kannan, Srinivasaraghavan;Fox, Stephen J.;Verma, Chandra S.
对抑制特定蛋白质的药物产生抗药性是靶向治疗中的一个主要问题。显然需要严格的方法来预测因药物结合而产生的特定耐药突变的可能性。在这项工作中，我们试图开发一种稳健的计算方法来预测EGFR中守门人位置(T790)的耐药突变。我们探索该位点的突变如何影响与ATP和目前临床使用的三种药物的相互作用。正如预期的那样，我们发现某些突变在结构上是不能容忍的，而其他一些突变会干扰自然底物，因此不太可能被选择。然而，我们发现了五种可能的突变，它们在结构和能量上都可以很好地容忍。正如早先报道的那样，其中两个突变被预测比ATP对药物的亲和力更高。通过再现数据的实验结合亲和力的趋势，这里选择的方法能够正确地预测这些突变对药物结合亲和力的影响。然而，亲和力的增加并不总是转化为有效性的增加，因为有效性受到其他几个因素的影响，例如结合动力学、与ATP的竞争和停留时间。目前研究中使用的计算方法能够重现或预测突变对结合亲和力的影响。然而，需要一套不同的方法来预测药物结合的动力学。
The emergence of resistance against drugs that inhibit a particular protein is a major problem in targeted therapy. There is a clear need for rigorous methods to predict the likelihood of specific drug-resistance mutations arising in response to the binding of a drug. In this work we attempt to develop a robust computational protocol for predicting drug resistant mutations at the gatekeeper position (T790) in EGFR. We explore how mutations at this site affects interactions with ATP and three drugs that are currently used in clinics. We found, as expected, that certain mutations are not tolerated structurally, while some other mutations interfere with the natural substrate and hence are unlikely to be selected for. However, we found five possible mutations that are well tolerated structurally and energetically. Two of these mutations were predicted to have increased affinity for the drugs over ATP, as has been reported earlier. By reproducing the trends in the experimental binding affinities of the data, the methods chosen here are able to correctly predict the effects of these mutations on the binding affinities of the drugs. However, the increased affinity does not always translate into increased efficacy, because the efficacy is affected by several other factors such as binding kinetics, competition with ATP, and residence times. The computational methods used in the current study are able to reproduce or predict the effects of mutations on the binding affinities. However, a different set of methods is required to predict the kinetics of drug binding.