Computation and Repurposing to identfy antivirals directed against dominant
计算和重新利用以确定针对显性病毒的抗病毒药物
基本信息
- 批准号:8643867
- 负责人:
- 金额:$ 71.76万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2014
- 资助国家:美国
- 起止时间:2014-04-10 至 2019-03-31
- 项目状态:已结题
- 来源:
- 关键词:Antiviral AgentsBindingCapsidCellsChagas DiseaseChemicalsClinicClinical TrialsComplexComputing MethodologiesCore ProteinDatabasesDengueDengue VirusDevelopmentDockingDrug TargetingDrug resistanceEffectivenessEnterovirus 71EvolutionFrequenciesGenomeGrowthHIVHIV InfectionsHepatitis AHepatitis A VirusHepatitis CHepatitis C virusHomoHomology ModelingHumanHuman poliovirusHybridsInfectionIntegration Host FactorsLaboratoriesLeadLegalLigandsMalariaMiningModelingMolecularMutationOutcomePharmaceutical PreparationsPharmacologic SubstancePharmacotherapyPoliovirusesPopulationProteinsRNARNA VirusesResistanceRiskSchemeStructureTechniquesTestingViralViral ProteinsVirusVirus Diseasesbasecheminformaticsdrug resistant virusenv Gene Productsgenetic analysisimprovedinhibitor/antagonistinnovationloss of functionmonomermouse modelnovelpharmacophorepressureprotein protein interactionprotein structureresearch studysmall moleculesuccesstheoriestissue culturevirus envelope
项目摘要
The rapid evolution of drug-resistant viruses is the single greatest reason that there are so few effective compounds available to treat RNA viral infections. Several approaches to circumvent the high frequencies of drug resistance have been pursued. Targeting host factors is an excellent strategy represented by several proposals in the present consortium. Multi-drug therapy is being used successfully to treat HIV infections, but obviously requires the existence of multiple drugs. We are developing a new paradigm, to develop inhibitors of 'dominant drug targets': those viral products that, when drug-bound, dominantly interfere with the growth of drug-resistant products within the same cell. The premise here is that drug-resistant viruses will always be made, but that it is possible to blunt the selection pressure on them by targeting oligomeric proteins that will be chimeric mixtures of drug-resistant and drug-susceptible subunits. To this end, we have identified five potential dominant drug targets on which to focus structure-based modeling. These highly oligomeric targets are the core protein structures of HCV and Dengue viruses, the icosahedrally symmetric Dengue virus envelope and the capsid structures of hepatitis A and enterovirus 71. For each modeling project, a unique approache will be the use of a heavily curated data base of known or approved drugs, termed WONTKILL (World of Non-Toxic Khemicals, ILIegal and Legal). This database has recently been mined to identify a repurposed compound currently in clinical trials for Trypanosma cruzi infections. Innovative mining techniques developed in the Pande laboratory include molecular similarity and rapid cheminformatics approaches. Selected potential compounds will be evaluated for efficacy in inhibiting viral growth and, just as importantly, the frequency of emergence of drug resistance in tissue culture and mouse models. Successful completion of these experiments will yield novel or, even better, repurposed compounds that both inhibit the target RNA viruses and display lowered risk of being rendered useless by the emergence of drug resistance.
抗药性病毒的快速进化是治疗RNA病毒感染的有效化合物如此之少的唯一最大原因。已经采取了几种方法来避免高频率的耐药性。针对东道国因素是一项极好的战略,本联合体的几项提案就是这一战略的代表。多种药物疗法正在成功地用于治疗艾滋病毒感染,但显然需要多种药物的存在。我们正在开发一种新的模式,开发“主要药物靶点”的抑制剂:当药物结合时,这些病毒产物主要干扰同一细胞内耐药产物的生长。这里的前提是,抗药性病毒总是会被制造出来,但是通过靶向寡聚蛋白质来减弱对它们的选择压力是可能的,寡聚蛋白质将是抗药性和药物敏感性亚基的嵌合混合物。为此,我们已经确定了五个潜在的主要药物靶点,重点是基于结构的建模。这些高度寡聚的靶标是HCV和登革病毒的核心蛋白结构、二十面体对称的登革病毒包膜以及甲型肝炎和肠道病毒71的衣壳结构。对于每个建模项目,一个独特的方法将是使用一个已知或批准的药物,称为Wontkill(无毒化学品,非法和法律的世界)精心策划的数据库。该数据库最近已被挖掘,以确定目前在临床试验中用于克氏锥虫感染的再利用化合物。Pande实验室开发的创新采矿技术包括分子相似性和快速化学信息学方法。将评价选定的潜在化合物在抑制病毒生长方面的功效,以及同样重要的是,在组织培养和小鼠模型中出现耐药性的频率。这些实验的成功完成将产生新的,甚至更好的,重新利用的化合物,既能抑制靶RNA病毒,又能降低因耐药性出现而变得无用的风险。
项目成果
期刊论文数量(0)
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VIJAY S PANDE其他文献
VIJAY S PANDE的其他文献
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{{ truncateString('VIJAY S PANDE', 18)}}的其他基金
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FOLDING@HOME:使用大规模并行分布式 CO 模拟蛋白质折叠
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8364247 - 财政年份:2011
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$ 71.76万 - 项目类别:
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8364333 - 财政年份:2011
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$ 71.76万 - 项目类别:
FOLDING@HOME: SIMULATING PROTEIN FOLDING WITH MASSIVELY PARALLEL DISTRIBUTED CO
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8171825 - 财政年份:2010
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$ 71.76万 - 项目类别:
FOLDING@HOME: SIMULATING PROTEIN FOLDING WITH MASSIVELY PARALLEL DISTRIBUTED CO
FOLDING@HOME:使用大规模并行分布式 CO 模拟蛋白质折叠
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FOLDING@HOME: SIMULATING PROTEIN FOLDING WITH MASSIVELY PARALLEL DISTRIBUTED CO
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