Novel soluble nanopolymers for enrichment of low abundant phosphoproteins
用于富集低丰度磷蛋白的新型可溶性纳米聚合物
基本信息
- 批准号:8546309
- 负责人:
- 金额:$ 14.42万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-09-17 至 2015-08-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAffinityBindingBiological AssayBiological MarkersCancer BiologyClinicalComplexCoupledDendrimersDetectionDevelopmentDiseaseEnvironmentEventFractionationGoalsHumanIonsLabelLaboratoriesLocationMalignant NeoplasmsMass Spectrum AnalysisMetalsMethodsModelingModificationMonitorNaturePhasePhospho-Specific AntibodiesPhosphopeptidesPhosphoproteinsPhosphorylationPhosphorylation SitePlasmaPolymersProceduresPropertyProteinsProtocols documentationQuality ControlRadioactiveReagentRecoveryReproducibilityResearchResearch PersonnelSamplingSepharoseSignal PathwaySignal TransductionSignaling ProteinSiteSmall Business Innovation Research GrantSolidSolutionsSourceSystemTechniquesTechnologyTitaniaTitaniumTranslational ResearchUnited States National Institutes of HealthWateranticancer researchaqueousbasecancer proteomicscancer typechelationcombatdesignfunctional groupimprovedinnovative technologiesmetal oxidenanoparticlenanopolymernovelphase 1 studyphase 2 studyproduct developmenttool
项目摘要
DESCRIPTION (provided by applicant): With recent technical advances, multiple important signaling pathways that may be the causes of human malignancy have continuously been discovered and dissected. The vast majority of these signaling pathways involve reversible protein phosphorylation, and the information on the location and dynamics of phosphorylation provides important mechanisms on how the signaling networks function and interact. While translational research gradually shifts from lab models to clinical samples, with the ultimate goal
of identifying cancer biomarkers, a simple and reliable phosphorylation assay method is still missing for routine detection of phosphorylation in complex and typically heterogeneous clinical samples. Through this NIH SBIR Phase I study we will develop soluble nanopolymer-based reagents, termed PolyMAC (Polymer-based Metal Ion Affinity Capture), into commercial products for the highly efficient isolation of phosphopeptides. This novel design takes advantage of not only the properties of multifunctionalized nanoparticles, but more importantly, the soluble nature of the molecule, allowing for the chelation of a limited amount of phosphopeptides in the solution phase for optimum efficiency and maximum yield. We propose to finalize optimization and scalability of the reagents as commercial products. In addition, high throughput formats for comprehensive phosphoproteomic analyses will be developed to address needs of many cancer biology and proteomics research labs/facilities.
描述(申请人提供):随着最近的技术进步,可能导致人类恶性肿瘤的多种重要信号通路不断被发现和解剖。这些信号通路中的绝大多数涉及可逆的蛋白质磷酸化,而有关磷酸化位置和动力学的信息为信号网络如何运作和相互作用提供了重要的机制。而转化性研究逐渐从实验室模型转移到临床样本,最终目标是
在识别癌症生物标志物方面,目前还缺乏一种简单可靠的磷酸化分析方法来常规检测复杂且典型的异质性临床样本中的磷酸化。通过这项NIH SBIR第一阶段研究,我们将开发基于可溶纳米聚合物的试剂,称为PolyMAC(基于聚合物的金属离子亲和力捕获),用于高效分离磷酸肽的商业产品。这种新颖的设计不仅利用了多功能纳米颗粒的特性,更重要的是利用了分子的溶解性质,允许在溶液相中螯合有限数量的磷肽,以实现最佳效率和最大产率。我们建议将试剂的优化和可扩展性最终确定为商业化产品。此外,还将开发用于综合磷酸蛋白质组分析的高通量格式,以满足许多癌症生物学和蛋白质组学研究实验室/设施的需求。
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Identification of Phosphorylated Proteins on a Global Scale.
- DOI:10.1002/cpch.48
- 发表时间:2018-09
- 期刊:
- 影响因子:0
- 作者:Iliuk A
- 通讯作者:Iliuk A
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Anton Iliuk其他文献
Anton Iliuk的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Anton Iliuk', 18)}}的其他基金
Development of lavage EV protein biomarkers for minimally-invasive detection of endometrial cancer
开发用于子宫内膜癌微创检测的灌洗EV蛋白生物标志物
- 批准号:
10540917 - 财政年份:2022
- 资助金额:
$ 14.42万 - 项目类别:
Development of companion diagnostics for dasatinib-based personalized therapy for T-ALL
开发基于达沙替尼的 T-ALL 个性化治疗伴随诊断
- 批准号:
10256123 - 财政年份:2021
- 资助金额:
$ 14.42万 - 项目类别:
Development of non-invasive biomarker discovery and diagnostics approach for bladder cancer based on urine proteome and phosphoproteome
基于尿液蛋白质组和磷酸蛋白质组的膀胱癌非侵入性生物标志物发现和诊断方法的开发
- 批准号:
10264130 - 财政年份:2019
- 资助金额:
$ 14.42万 - 项目类别:
Development of non-invasive biomarker discovery and diagnostics approach for bladder cancer based on urine proteome and phosphoproteome
基于尿液蛋白质组和磷酸蛋白质组的膀胱癌非侵入性生物标志物发现和诊断方法的开发
- 批准号:
10251415 - 财政年份:2019
- 资助金额:
$ 14.42万 - 项目类别:
Developing gel-based platform for quantitative phosphoproteomics
开发基于凝胶的定量磷酸蛋白质组学平台
- 批准号:
8976425 - 财政年份:2015
- 资助金额:
$ 14.42万 - 项目类别:
Multiplexed detection and imaging of protein phosphorylation based on soluble nan
基于可溶性纳米粒子的蛋白质磷酸化多重检测和成像
- 批准号:
8394092 - 财政年份:2012
- 资助金额:
$ 14.42万 - 项目类别:
Novel soluble nanopolymers for enrichment of low abundant phosphoproteins
用于富集低丰度磷蛋白的新型可溶性纳米聚合物
- 批准号:
8314461 - 财政年份:2012
- 资助金额:
$ 14.42万 - 项目类别:
相似海外基金
Applications of Deep Learning for Binding Affinity Prediction
深度学习在结合亲和力预测中的应用
- 批准号:
2887848 - 财政年份:2023
- 资助金额:
$ 14.42万 - 项目类别:
Studentship
Metalloenzyme binding affinity prediction with VM2
使用 VM2 预测金属酶结合亲和力
- 批准号:
10697593 - 财政年份:2023
- 资助金额:
$ 14.42万 - 项目类别:
Building a binding community - Capacity and capability for affinity and kinetic analysis of molecular interactions.
建立结合社区 - 分子相互作用的亲和力和动力学分析的能力和能力。
- 批准号:
MR/X013227/1 - 财政年份:2022
- 资助金额:
$ 14.42万 - 项目类别:
Research Grant
Using dynamic network models to quantitatively predict changes in binding affinity/specificity that arise from long-range amino acid substitutions
使用动态网络模型定量预测由长程氨基酸取代引起的结合亲和力/特异性的变化
- 批准号:
10797940 - 财政年份:2022
- 资助金额:
$ 14.42万 - 项目类别:
Using dynamic network models to quantitatively predict changes in binding affinity/specificity that arise from long-range amino acid substitutions
使用动态网络模型定量预测由长距离氨基酸取代引起的结合亲和力/特异性的变化
- 批准号:
10502084 - 财政年份:2022
- 资助金额:
$ 14.42万 - 项目类别:
Using dynamic network models to quantitatively predict changes in binding affinity/specificity that arise from long-range amino acid substitutions
使用动态网络模型定量预测由长距离氨基酸取代引起的结合亲和力/特异性的变化
- 批准号:
10707418 - 财政年份:2022
- 资助金额:
$ 14.42万 - 项目类别:
Binding affinity of inositol phosphate analogs to protein toxin TcdB
磷酸肌醇类似物与蛋白质毒素 TcdB 的结合亲和力
- 批准号:
573604-2022 - 财政年份:2022
- 资助金额:
$ 14.42万 - 项目类别:
University Undergraduate Student Research Awards
Computational predictions of thermostability and binding affinity changes in enzymes
酶热稳定性和结合亲和力变化的计算预测
- 批准号:
2610945 - 财政年份:2021
- 资助金额:
$ 14.42万 - 项目类别:
Studentship
I-Corps: Physics-Based Binding Affinity Estimator
I-Corps:基于物理的结合亲和力估计器
- 批准号:
2138667 - 财政年份:2021
- 资助金额:
$ 14.42万 - 项目类别:
Standard Grant
Computational modelling and simulation of antibodies to enhance binding affinity of a potential Burkholderia pseudomallei therapeutic
抗体的计算模型和模拟,以增强潜在的鼻疽伯克霍尔德氏菌治疗剂的结合亲和力
- 批准号:
2750554 - 财政年份:2021
- 资助金额:
$ 14.42万 - 项目类别:
Studentship