Correlated electrostatic mutations provide a reservoir of stability in HIV protease.
Correlated electrostatic mutations provide a reservoir of stability in HIV protease.
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DOI：
10.1371/journal.pcbi.1002675
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发表时间：
2012
影响因子：
4.3
通讯作者：
Levy RM
中科院分区：
文献类型：
--
作者：
Haq O;Andrec M;Morozov AV;Levy RM
HIV蛋白酶是一种对HIV生命周期至关重要的乙酰基蛋白酶，是许多药物开发计划的目标。虽然市场上有许多蛋白酶抑制剂，但蛋白酶最终会通过快速突变和建立耐药性来逃避这些药物。耐药突变，称为原发性突变，通常会破坏酶的稳定性，这种稳定性的损失必须得到补偿。使用粗粒度的生物物理能量模型与统计推断方法，我们观察到，充电残基的辅助突变增加蛋白质的稳定性，在补偿不稳定的原发性耐药突变中起着关键作用。增加的稳定性与静电突变之间的相关性密切相关-不相关的突变会强烈地破坏酶的稳定性。此外，统计建模表明，相关的静电突变网络具有简单的拓扑结构，并已发展到最小化挫折的相互作用。该模型的统计耦合参数反映了这种缺乏挫折，并强烈区分最显着相关的双突变体的电荷静电相互作用从不喜欢的电荷相互作用。最后，我们证明了我们的模型具有相当大的预测能力，可用于预测复杂的突变模式，由于有限的样本量效应，尚未观察到这些突变模式，并且这些突变模式可能存在于病毒尚未测序的较大患者群体中。艾滋病毒是不可治愈的，因为它的酶通过对逆转录病毒抑制剂产生耐药性突变而迅速进化。大多数这些突变协同工作，但其合作背后的生物物理基础还没有得到很好的理解。我们的工作解决了这些重要的问题，通过弥合HIV蛋白酶亚型B序列的统计建模与带电氨基酸突变的能量学之间的差距，表明静电稳定性与相关性密切相关。此外，我们证明了我们的统计模型具有相当大的预测能力，可以用来预测复杂的突变模式，尚未观察到由于目前的序列数据库的有限大小。换句话说，随着数据库大小的增加，我们的模型有能力预测更有可能被观察到的高概率突变模式的身份。了解哪些目前未观察到的突变更有可能被观察到，这对防治疾病非常有利。
HIV protease, an aspartyl protease crucial to the life cycle of HIV, is the target of many drug development programs. Though many protease inhibitors are on the market, protease eventually evades these drugs by mutating at a rapid pace and building drug resistance. The drug resistance mutations, called primary mutations, are often destabilizing to the enzyme and this loss of stability has to be compensated for. Using a coarse-grained biophysical energy model together with statistical inference methods, we observe that accessory mutations of charged residues increase protein stability, playing a key role in compensating for destabilizing primary drug resistance mutations. Increased stability is intimately related to correlations between electrostatic mutations – uncorrelated mutations would strongly destabilize the enzyme. Additionally, statistical modeling indicates that the network of correlated electrostatic mutations has a simple topology and has evolved to minimize frustrated interactions. The model's statistical coupling parameters reflect this lack of frustration and strongly distinguish like-charge electrostatic interactions from unlike-charge interactions for of the most significantly correlated double mutants. Finally, we demonstrate that our model has considerable predictive power and can be used to predict complex mutation patterns, that have not yet been observed due to finite sample size effects, and which are likely to exist within the larger patient population whose virus has not yet been sequenced. HIV is incurable because its enzymes evolve rapidly by developing resistance mutations to retroviral inhibitors. Most of these mutations work synergistically, but the biophysical basis behind their cooperation is not well understood. Our work addresses these important issues by bridging the gap between the statistical modeling of HIV protease subtype B sequences with the energetics of mutations involving charged amino acids by showing that electrostatic stability is intimately related to correlations. Moreover, we demonstrate that our statistical model has considerable predictive power and can be used to predict complex mutation patterns that have not yet been observed due to the finite sizes of the current sequence databases. In other words, as the database size increases, our model has the ability to predict the identities of the high probability mutations patterns, which are more likely to be observed. Knowing which currently unobserved mutations are more likely to be observed can be very advantageous in combating the disease.
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影响因子：
2.9
作者：
Hendsch, ZS;Jonsson, T;Tidor, B
通讯作者：
Tidor, B
影响因子：
20.6
作者：
JAYNES, ET
通讯作者：
JAYNES, ET
影响因子：
2.9
作者：
Balakrishnan, Sivaraman;Kamisetty, Hetunandan;Langmead, Christopher James
通讯作者：
Langmead, Christopher James
DOI：
10.1126/science.1187816
发表时间：
2010-06-04
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Bloom JD;Gong LI;Baltimore D
通讯作者：
Baltimore D
DOI：
10.1073/pnas.97.19.10383
发表时间：
2000-09-12
影响因子：
11.1
作者：
Kuhlman, B;Baker, D
通讯作者：
Baker, D