Inference of Epistatic Effects Leading to Entrenchment and Drug Resistance in HIV-1 Protease.
Inference of Epistatic Effects Leading to Entrenchment and Drug Resistance in HIV-1 Protease.
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DOI：
10.1093/molbev/msx095
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发表时间：
2017-06-01
影响因子：
10.7
通讯作者：
Levy RM
中科院分区：
文献类型：
--
作者：
Flynn WF;Haldane A;Torbett BE;Levy RM
了解产生耐药病毒株的复杂突变模式为开发更有效的艾滋病毒/艾滋病治疗策略奠定了基础。药物经历的HIV-1蛋白酶序列的多重序列比对包含许多对相关性的网络，这些网络可用于构建这些突变模式的（Potts）Hamilton模型。使用这个哈密顿模型，我们将HIV-1蛋白酶序列协变数据转化为观察到的特定突变模式的概率的定量预测，这些突变模式与观察到的序列统计数据一致。我们发现，Potts模型的统计能量与含有治疗相关突变的个体蛋白质的适应性相关，所述个体蛋白质通过体外测量蛋白质稳定性和病毒感染性来估计。我们表明，获得原发性耐药突变的惩罚取决于与序列背景的上位相互作用。导致耐药性的原发性突变可以通过响应于药物治疗而出现的复杂突变模式变得非常有利（或根深蒂固），尽管在野生型背景中是不稳定的。预测上位效应对于未来蛋白酶抑制剂疗法的设计是重要的。
Understanding the complex mutation patterns that give rise to drug resistant viral strains provides a foundation for developing more effective treatment strategies for HIV/AIDS. Multiple sequence alignments of drug-experienced HIV-1 protease sequences contain networks of many pair correlations which can be used to build a (Potts) Hamiltonian model of these mutation patterns. Using this Hamiltonian model, we translate HIV-1 protease sequence covariation data into quantitative predictions for the probability of observing specific mutation patterns which are in agreement with the observed sequence statistics. We find that the statistical energies of the Potts model are correlated with the fitness of individual proteins containing therapy-associated mutations as estimated by in vitro measurements of protein stability and viral infectivity. We show that the penalty for acquiring primary resistance mutations depends on the epistatic interactions with the sequence background. Primary mutations which lead to drug resistance can become highly advantageous (or entrenched) by the complex mutation patterns which arise in response to drug therapy despite being destabilizing in the wildtype background. Anticipating epistatic effects is important for the design of future protease inhibitor therapies.