Rational design of viral inhibitors: Application to SARS
Rational design of viral inhibitors: Application to SARS
批准号:
7649123
负责人:
VINCENT J. HILSER
金额:
$13.18万
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-03-01 至 2009-02-28
关键词:
AddressAffinityAnimal ModelAnimalsAntiviral AgentsBindingBinding ProteinsBinding SitesBiological AssayCalorimetryCategoriesCellsChimeric ProteinsClassCollaborationsCompatibleComplexComputer SimulationCoronavirusCyclic PeptidesDataDengueDevelopmentDisulfidesFundingGenerationsGeneric DrugsGoalsGrantHumanIn VitroInfectionInstructionLeadLibrariesLifeLigandsModelingMolecular ConformationNational Institute of Allergy and Infectious DiseaseNaturePeptidesPrionsProtein ConformationProtein DynamicsProteinsRangeSevere Acute Respiratory SyndromeSiteStructureSystemTechnologyTestingTherapeuticThermodynamicsTitrationsValidationVariantViral ProteinsVirusVirus DiseasesVirus InhibitorsX-Ray Crystallographyamyloid formationanalogbasecrosslinkdesignenv Gene Productsexperiencein vivoinhibitor/antagonistnovelpathogenpeptide analogpreventreceptor bindingsuccesstool
中文摘要
发展合理的方法,可以有效地靶向和预防病毒感染是一个重要的问题。
这是WRC的战略目标。虽然理性设计的努力偶尔会取得成功,但关键是
缺点是与蛋白质构象的动态性质相关的困难。也就是说,
蛋白质靶点(通常是包膜蛋白)并不表现为用于描述
他们相反,这些蛋白质是动态的,经历构象波动。这就构成了
与设计用于结构异质性靶的配体相关的明显困难-配体必须
与蛋白质的一种低能构象或多种高能构象相容
以便产生足够高的结合亲和力。在这里,这个问题是解决了一个独特的
计算方法,称为COREX_Design,已在过去十年中开发,
将蛋白质和肽建模为构象状态的集合。
最近的研究设计的抑制剂,以人类朊病毒蛋白(PrP),和冠状病毒的代理,
严重急性呼吸综合征(SARS)(SCoV),提供了COREX_Design是
能够:1)鉴定“化学相容的”潜在结合位点,2)设计构象上相容的结合位点,
结构上与该位点相容的受约束的二硫键交联的环肽配体,和3)
优化序列以使蛋白质和肽之间的构象相容性最大化。
利用这个工具,我们能够成功地设计出PrP形成淀粉样蛋白的有效抑制剂,
已经收集了针对SCoV的抗病毒活性的强有力的初步结果,SCoV是本研究的目标之一。
提议
本项目的目标是证明COREX_Design可以作为一种通用策略应用于
抗病毒剂的发展。虽然这种新的设计工具原则上可以应用于任何系统
在已知靶的结构信息的情况下,将其应用于包膜蛋白的结构域3
登革2型病毒(DN 2 V)和SCoV的刺突蛋白(S)。在资助期间,我们将
证明了设计的肽在基于细胞的测定中的功效,并且在资助的过程中,
将在动物实验中测试铅化合物。
相关性(参见说明):
NIAID A、B和C类病毒每年造成数百万例感染。很少有抗病毒药物
可获得治疗这些感染的治疗剂。这里描述的方法利用了一个独特的
计算机建模策略应用于抗病毒剂的开发。这种方法的成功
可以为抗击感染提供新的途径,从而拯救生命
英文摘要
The development of rational approaches that can effectively target and prevent viral infection is a
strategic objective of the WRCE. Although rational design efforts have met with occasional success, a key
shortcoming is the difficulty associated with the dynamic nature of protein conformation. Namely, the viral
protein targets (usually envelope proteins) do not behave as the static structures that are used to depict
them. Instead, these proteins are dynamic and experience conformational fluctuations. This poses the
obvious difficulty associated with designing a ligand for a structurally heterogeneous target-the ligand must
be compatible with either one low energy conformation of the protein or multiple higher energy conformations
in order to result in a high enough binding affinity. Here, this problem is addressed with a unique
computational approach, called COREX_Design, that has been developed over the past decade, and which
models proteins and peptides as ensembles of conformational states.
Recent studies on the design of inhibitors to the human prion protein (PrP), and the coronavirus agent of
severe acute respiratory syndrome (SARS) (SCoV), have provided proof-of-principle that COREX_Design is
able to; 1) identify "thermodynamically compatible" potential binding site(s), 2) design a conformationally
constrained, disulfide cross-linked cyclic peptide ligand that is structurally compatible with this site, and 3)
optimize the sequence to maximize the conformational compatibility between the protein and the peptide.
Using this tool, we were able to successfully design potent inhibitors of amyloid formation by PrP, and we
have collected strong preliminary results for antiviral activity against SCoV, one of the targets of this
proposal.
The goal of this project is to demonstrate that COREX_Design can be applied as a general strategy to
the development of antiviral agents. Although this new design tool can in principle be applied to any system
where structural information is known about the target, it is applied here to domain 3 of the envelope protein
of dengue 2 virus (DN2V) and the spike (S) protein of SCoV. During the period of funding, we will
demonstrate the efficacy of the designed peptides in cell based assays, and over the course of the grant we
will test lead compounds in animal studies.
RELEVANCE (See instructions):
NIAID Category A, B and C viruses are responsible for millions of infections each year. Few antiviral
therapeutics are available to treat these infections. The approach described here leverages a unique
computational modeling strategy into the development of antiviral agents. The success of this approach
could offer new avenues for combating infections and thus saving lives
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