Proteochemometric modeling of HIV protease susceptibility.

Proteochemometric modeling of HIV protease susceptibility.
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HIV蛋白酶易感性的蛋白化学调查模型。

DOI:
10.1186/1471-2105-9-181
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发表时间:
2008-04-10
期刊:
影响因子:
3
通讯作者:
Wikberg, Jarl E. S.
Wikberg, Jarl E. S.
中科院分区:
生物学4区
文献类型:
--
作者:
Lapins, Maris;Eklund, Martin;Spjuth, Ola;Prusis, Peteris;Wikberg, Jarl E. S.

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艾滋病毒治疗的一个主要障碍是病毒迅速变异为抗药性变种的能力。预测突变的HIV毒株对抗病毒药物的敏感性的方法将提供大量的临床益处,并促进新候选药物的开发。因此,我们使用蛋白质化学计量学来模拟HIV对目前使用的蛋白酶抑制剂的易感性,利用对突变的HIV蛋白酶的物理化学性质的描述和对这些酶抑制剂的3D结构性质的描述。这些描述与目前使用的七种蛋白酶抑制剂的828种独特的HIV蛋白酶变种的敏感性数据相关联;数据集包括4792种蛋白酶-抑制剂组合。该模型提供了很好的预测性(R2=0.92,Q2=0.87),并确定了耐药的一般特征和特殊特征。通过外部预测验证了该模型的预测能力,即从数据集中省略对七种抑制剂中每一种的敏感性,一次一个抑制剂,并使用其余六种化合物的数据来创建新的模型。这一分析表明,对省略的抑制剂的总体预测能力为Q2抑制剂=0.72。我们的结果表明,蛋白化学方法可以为新的抑制剂提供普遍的敏感性预测。我们的蛋白质化学计量学模型可以直接分析抑制物-蛋白酶的相互作用,并有助于基于病毒基因型的治疗选择。该模型可供公众使用,位于艾滋病毒药物研究中心。
A major obstacle in treatment of HIV is the ability of the virus to mutate rapidly into drug-resistant variants. A method for predicting the susceptibility of mutated HIV strains to antiviral agents would provide substantial clinical benefit as well as facilitate the development of new candidate drugs. Therefore, we used proteochemometrics to model the susceptibility of HIV to protease inhibitors in current use, utilizing descriptions of the physico-chemical properties of mutated HIV proteases and 3D structural property descriptions for the protease inhibitors. The descriptions were correlated to the susceptibility data of 828 unique HIV protease variants for seven protease inhibitors in current use; the data set comprised 4792 protease-inhibitor combinations. The model provided excellent predictability (R2 = 0.92, Q2 = 0.87) and identified general and specific features of drug resistance. The model's predictive ability was verified by external prediction in which the susceptibilities to each one of the seven inhibitors were omitted from the data set, one inhibitor at a time, and the data for the six remaining compounds were used to create new models. This analysis showed that the over all predictive ability for the omitted inhibitors was Q2 inhibitors = 0.72. Our results show that a proteochemometric approach can provide generalized susceptibility predictions for new inhibitors. Our proteochemometric model can directly analyze inhibitor-protease interactions and facilitate treatment selection based on viral genotype. The model is available for public use, and is located at HIV Drug Research Centre.
DOI: 10.1186/1471-2105-6-50
发表时间: 2005-03-10
期刊: BMC bioinformatics
影响因子: 3
作者:
Freyhult E;Prusis P;Lapinsh M;Wikberg JE;Moulton V;Gustafsson MG
通讯作者: Gustafsson MG
DOI: 10.1093/bioinformatics/19.1.98
发表时间: 2003-01-01
期刊: BIOINFORMATICS
影响因子: 5.8
作者:
Draghici, S;Potter, RB
通讯作者: Potter, RB
DOI: 10.1124/mol.104.002857
发表时间: 2005-01-01
影响因子: 3.6
作者:
Lapinsh, M;Veiksina, S;Wikberg, JES
通讯作者: Wikberg, JES
DOI: 10.1371/journal.pmed.0040036
发表时间: 2007-01-01
期刊: PLOS MEDICINE
影响因子: 15.8
作者:
Nijhuis, Monique;van Maarseveen, Noortje M.;Boucher, Charles A. B.
通讯作者: Boucher, Charles A. B.
DOI: 10.1021/bi0350405
发表时间: 2003-11-25
期刊: BIOCHEMISTRY
影响因子: 2.9
作者:
Ohtaka, H;Schön, A;Freire, E
通讯作者: Freire, E