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Computational design of specific binding proteins using Leave-One-Out

使用留一法进行特异性结合蛋白的计算设计

基本信息

批准号：
10224218
负责人：
CHRISTOPHER BYSTROFF
金额：
$ 30.57万
依托单位：
RENSSELAER POLYTECHNIC INSTITUTE
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：
2012-09-20 至 2023-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10224218
关键词：
Address Affinity Algorithm Design Amino Acid Sequence Animals Antibodies Appearance Award Bar Codes Binding Binding Proteins Biophysics Biosensor Cell Separation Communicable Diseases Computer Models Consumption Containment Culicidae Dengue Dengue Virus Detection Development Devices Diagnosis Disease Early Diagnosis Economics Emerging Communicable Diseases Engineering Escherichia coli Event Fiber Fluorescence Fluorescence Resonance Energy Transfer Fluorescence-Activated Cell Sorting Frustration Funding Genetic Goals Green Fluorescent Proteins Guidelines Health Hybridomas Image Immobilization In Vitro Influenza Kinetics Knowledge Label Ligand Binding Ligands Methods Modeling Molecular Nature Noise Pathogen detection Pathway interactions Peptides Physiologic pulse Process Production Protein Engineering Proteins Reporting Research Signal Transduction Silk Specific qualifier value Specificity Sum System Technology Testing Textiles Time Training Variant Virus Work Yeasts Zika Virus animal facility base biophysical properties chromophore clinical diagnostics computational pipelines density design diagnostic platform disorder prevention experimental study high throughput screening improved innovation interest multiplex detection novel novel strategies prevent protein folding protein function receptor screening sensor success vector mosquito

项目摘要

SUMMARY: Computational design of specific binding proteins using Leave-One-Out The goal of this research is to design a receptor protein to bind any protein target. Furthermore, the binding event will be signaled by the appearance of fluorescence. The novel binding protein will be able to sense and report the presence of a specific protein or peptide in a mixture of others, allowing the detection of any disease agent or protein of interest. The new approach takes advantage of the green fluorescent protein (GFP) what we know about its folding pathway. When GFP folds, it does in a specified order of events called a pathway. When it finishes folding, its fluorescence activity is immediately turned on. If we leave out one small piece of GFP so that the folding cannot finish folding, then it sits in an inactive state until the missing piece appears. Using this Leave-One-Out strategy, partially folded proteins become sensors for their missing pieces. Using computational design algorithms, a new amino acid sequence can be substituted for the missing piece, making the designed GFP a sensor for the new sequence. But accurate computational protein design is challenging because of inherent assumptions. Two approaches are proposed to overcome the weaknesses. First, thousands of candidates will be designed, synthesized in yeast and then screened for their biosensor function using high throughput cell sorting technology. Second, more knowledge about the folding pathway will be generated by pulse-labeling the protein as it folds, then finding out what parts of the protein fold first. This will improve the computational model for folding, and therefore improve the ability to design partially folded leave-one-out biosensors. A cautious, step-wise design strategy is proposed for screening, so that every experiment tests a specific hypothesis about GFP folding and function. A known drawback of the leave-one-out method is the necessity of a having a partially unfolded off-state protein that can aggregate an cause problems. To fix this, biosensor proteins will be genetically fused to a fiber-forming protein to create robust and stable biosensor fabrics that no longer have a problem with aggregation. The final product of this research will be is a silk-like biosensor fabric that is computationally designed to sense any protein target and glow green when the target is present.

总结：用留一法设计特异性结合蛋白这项研究的目标是设计一种受体蛋白来结合任何蛋白质靶点。此外，结合事件将通过荧光的出现发出信号。小说结合蛋白将能够感测和报告特定蛋白质或肽在细胞中的存在。其他物质的混合物，允许检测任何感兴趣的疾病因子或蛋白质。新这种方法利用了我们所知道的绿色荧光蛋白（GFP），折叠途径当GFP折叠时，它以一种特定的事件顺序进行，称为途径。当当它完成折叠时，它的荧光活性立即被激活。如果我们忽略一个小的 GFP片段，使得折叠不能完成折叠，然后它处于非活性状态，直到缺失的部分出现了。使用这种留一策略，部分折叠的蛋白质变成传感器来寻找它们丢失的部分使用计算设计算法，可以用新的氨基酸序列取代缺失的片段，使设计的GFP成为新序列的传感器。但准确由于固有的假设，计算蛋白质设计具有挑战性。两种方法提出了克服这些弱点的建议。首先，数千名候选人将被设计，然后使用高通量细胞筛选它们的生物传感器功能分选技术第二，更多关于折叠途径的知识将通过以下方式产生：在蛋白质折叠时对其进行脉冲标记，然后找出蛋白质的哪些部分首先折叠。这将改进折叠的计算模型，从而提高部分设计的能力折叠式留一法生物传感器提出了一种谨慎的、逐步的设计策略，筛选，以便每个实验测试关于GFP折叠和功能的特定假设。留一法的一个已知缺点是必须具有部分未折叠的关闭状态的蛋白质，可以聚集引起问题。为了解决这个问题，将被基因融合到纤维形成蛋白质中，以创建坚固稳定的生物传感器织物不再有聚合的问题。这项研究的最终产品将是一个一种类似丝绸的生物传感器织物，经过计算设计，可检测任何蛋白质目标并发光目标存在时为绿色。

项目成果

期刊论文数量（19）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Intrinsically disordered proteins play diverse roles in cell signaling.

DOI：
10.1186/s12964-022-00821-7
发表时间：
2022-02-17
期刊：
Cell communication and signaling : CCS
影响因子：
0
作者：
Bondos SE;Dunker AK;Uversky VN
通讯作者：
Uversky VN

Comparative void-volume analysis of psychrophilic and mesophilic enzymes: Structural bioinformatics of psychrophilic enzymes reveals sources of core flexibility.

DOI：
10.1186/1472-6807-11-42
发表时间：
2011-10-20
期刊：
BMC structural biology
影响因子：
0
作者：
Paredes DI;Watters K;Pitman DJ;Bystroff C;Dordick JS
通讯作者：
Dordick JS

Directed evolution of the quorum-sensing regulator EsaR for increased signal sensitivity.

DOI：
10.1021/cb3006402
发表时间：
2013-04-19
期刊：
ACS CHEMICAL BIOLOGY
影响因子：
4
作者：
Shong, Jasmine;Huang, Yao-Ming;Bystroff, Christopher;Collins, Cynthia H.
通讯作者：
Collins, Cynthia H.

The designability of protein switches by chemical rescue of structure: mechanisms of inactivation and reactivation.

通过结构的化学拯救来设计蛋白质开关：失活和再激活的机制。

DOI：
10.1021/ja407644b
发表时间：
2013
期刊：
Journal of the American Chemical Society
影响因子：
15
作者：
Xia,Yan;DiPrimio,Nina;Keppel,TheodoreR;Vo,Binh;Fraser,Keith;Battaile,KevinP;Egan,Chet;Bystroff,Christopher;Lovell,Scott;Weis,DavidD;Anderson,JChristopher;Karanicolas,John
通讯作者：
Karanicolas,John

Fast design of arbitrary length loops in proteins using InteractiveRosetta.

使用 InteractiveRosetta 快速设计蛋白质中的任意长度环。