Prediction of mutational tolerance in HIV-1 protease and reverse transcriptase using flexible backbone protein design.
Prediction of mutational tolerance in HIV-1 protease and reverse transcriptase using flexible backbone protein design.
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DOI：
10.1371/journal.pcbi.1002639
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发表时间：
2012
影响因子：
4.3
通讯作者：
Kortemme T
中科院分区：
文献类型：
--
作者：
Humphris-Narayanan E;Akiva E;Varela R;Ó Conchúir S;Kortemme T
预测蛋白质在维持其结构和功能的同时耐受哪些突变对于模拟蛋白质的基本特性及其进化具有重要的应用；它还推动了蛋白质设计的进步。在这里，我们开发了一个计算模型来预测单突变可达到的 HIV-1 蛋白酶的耐受序列空间。我们通过与 50,000 多个 HIV-1 蛋白酶序列中观察到的变异性进行比较来评估该模型，这是关于耐受序列空间的最全面的数据集之一。然后我们将模型扩展到第二种蛋白质，即逆转录酶。该模型集成了作用于蛋白质的多种结构和功能约束，并使用蛋白质构象的集合。我们发现该模型正确捕获了相当大一部分的蛋白酶和逆转录酶突变耐受性，并且使用实验确定或计算生成的结构整体显示出相当的准确性。该模型提供的耐受序列空间的预测提供了对抗性突变出现时的稳定性功能权衡以及计算模型的优点和局限性的见解。许多相关的蛋白质序列可以与给定蛋白质的结构和功能一致，这表明蛋白质可能对突变相当稳健。这种对突变的耐受性经常被病原体利用。特别是，病原体可以快速进化出具有新功能（对治疗性抑制剂具有抵抗力）的突变蛋白质，而不会放弃病原体所必需的其他功能。这一原则也可能更普遍地成立：耐受突变变化的蛋白质可以更容易地获得新功能，同时保持其现有特性。因此，预测蛋白质对突变的耐受性的能力可以帮助分析病原体中抗性突变的出现，并设计具有新功能的蛋白质。在这里，我们开发了一个计算模型来预测对单核苷酸变化可实现的点突变的蛋白质突变耐受性，并使用两种重要的致病蛋白和治疗靶点（HIV-1 的蛋白酶和逆转录酶）对其进行验证。该模型提供了有关耐药性如何出现的见解，并对尚未发现的突变做出可测试的预测。类似的突变耐受模型对于表征和重新设计其他具有三维结构的蛋白质的功能应该很有用。
Predicting which mutations proteins tolerate while maintaining their structure and function has important applications for modeling fundamental properties of proteins and their evolution; it also drives progress in protein design. Here we develop a computational model to predict the tolerated sequence space of HIV-1 protease reachable by single mutations. We assess the model by comparison to the observed variability in more than 50,000 HIV-1 protease sequences, one of the most comprehensive datasets on tolerated sequence space. We then extend the model to a second protein, reverse transcriptase. The model integrates multiple structural and functional constraints acting on a protein and uses ensembles of protein conformations. We find the model correctly captures a considerable fraction of protease and reverse-transcriptase mutational tolerance and shows comparable accuracy using either experimentally determined or computationally generated structural ensembles. Predictions of tolerated sequence space afforded by the model provide insights into stability-function tradeoffs in the emergence of resistance mutations and into strengths and limitations of the computational model. Many related protein sequences can be consistent with the structure and function of a given protein, suggesting that proteins may be quite robust to mutations. This tolerance to mutations is frequently exploited by pathogens. In particular, pathogens can rapidly evolve mutated proteins that have a new function - resistance against a therapeutic inhibitor - without abandoning other functions essential for the pathogen. This principle may also hold more generally: Proteins tolerant to mutational changes can more easily acquire new functions while maintaining their existing properties. The ability to predict the tolerance of proteins to mutation could thus help both to analyze the emergence of resistance mutations in pathogens and to engineer proteins with new functions. Here we develop a computational model to predict protein mutational tolerance towards point mutations accessible by single nucleotide changes, and validate it using two important pathogenic proteins and therapeutic targets: the protease and reverse transcriptase from HIV-1. The model provides insights into how resistance emerges and makes testable predictions on mutations that have not been seen yet. Similar models of mutational tolerance should be useful for characterizing and reengineering the functions of other proteins for which a three-dimensional structure is available.
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影响因子：
5.6
作者：
Guerois, R;Nielsen, JE;Serrano, L
通讯作者：
Serrano, L
影响因子：
56.9
作者：
COFFIN, JM
通讯作者：
COFFIN, JM
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1.5
作者：
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Bennett DE;Camacho RJ;Otelea D;Kuritzkes DR;Fleury H;Kiuchi M;Heneine W;Kantor R;Jordan MR;Schapiro JM;Vandamme AM;Sandstrom P;Boucher CA;van de Vijver D;Rhee SY;Liu TF;Pillay D;Shafer RW
通讯作者：
Shafer RW
影响因子：
4.8
作者：
Beard, WA;Minnick, DT;Wilson, SH
通讯作者：
Wilson, SH