Translating HIV sequences into quantitative fitness landscapes predicts viral vulnerabilities for rational immunogen design.
Translating HIV sequences into quantitative fitness landscapes predicts viral vulnerabilities for rational immunogen design.
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DOI：
10.1016/j.immuni.2012.11.022
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发表时间：
2013-03-21
期刊：
影响因子：
32.4
通讯作者：
Chakraborty AK
中科院分区：
文献类型：
--
作者：
Ferguson AL;Mann JK;Omarjee S;Ndung'u T;Walker BD;Chakraborty AK
预防性或治疗性疫苗是遏制艾滋病毒/艾滋病在撒哈拉以南非洲肆虐的最大希望，但仍然难以捉摸。一个主要的挑战是毒株之间病毒序列的极端可变性。目前还没有系统的方法来指导针对艾滋病毒等高度可变病原体的免疫原设计。利用计算模型，我们开发了一种方法，将可用的病毒序列数据转化为病毒适合度的定量景观，作为其组成蛋白氨基酸序列的函数。从我们计算定义的HIV-1进化支B Gag蛋白景观中出现的预测，与新的体外适应度测量结果进行了阳性测试，并且与先前定义的体外测量结果和临床观察结果一致。随着蛋白质序列的变化，这些景观绘制了病毒适应性的高峰和低谷，并为免疫原的设计和治疗提供了信息，这些免疫原和治疗可以针对病毒最容易受到选择压力的区域。
A prophylactic or therapeutic vaccine offers the best hope to curb the HIV-AIDS epidemic gripping sub-Saharan Africa, but remains elusive. A major challenge is the extreme viral sequence variability among strains. Systematic means to guide immunogen design for highly variable pathogens like HIV are not available. Using computational models, we have developed an approach to translate available viral sequence data into quantitative landscapes of viral fitness as a function of the amino acid sequences of its constituent proteins. Predictions emerging from our computationally defined landscapes for the proteins of HIV-1 clade B Gag were positively tested against new in vitro fitness measurements, and were consistent with previously defined in vitro measurements and clinical observations. These landscapes chart the peaks and valleys of viral fitness as protein sequences change, and inform the design of immunogens and therapies that can target regions of the virus most vulnerable to selection pressure.
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