Molecular Design and Structural Basis of Peptide Inhibitors against Amyloid-beta Aggregation
Molecular Design and Structural Basis of Peptide Inhibitors against Amyloid-beta Aggregation
批准号:
1158447
负责人:
Jie Zheng
金额:
$29.81万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-07-01 至 2015-06-30
中文摘要
点击翻译按钮获取中文摘要
英文摘要
1158447 ZhengAmyloids are highly ordered protein aggregates associated with many neurodegenerative diseases including Alzheimer and Parkinson diseases. Accumulating evidences suggest that soluble amyloid oligomers are major toxic specie responsible for neuronal dysfunction and cell death. Thus, inhibiting initial amyloid oligomerization and aggregation at the very early stage could be an effective (pre)clinical treatment for preventing or delaying the onset of neurodegenerative diseases. But, the lacks of high-resolution structures of amyloid oligomers, atomic details of amyloid-inhibitor interactions, and cost-effective high-throughput screening methods lead to the difficulty in the rational design of structural-based inhibitors and in the fundamental understanding of amyloid inhibition mechanism.Intellectual Merits: The proposed work combines bioinformatics models, molecular simulations, and biophysical experiments to screen/design, characterize, and identify a series of small hexapeptides to disrupt or prevent amyloid-â (Aâ) oligomerization, fibrillogenesis, and toxicity associated with Alzheimer disease. With assistance of atomic structures of Aâ oligomers determined by the PI's lab and validated by atomic force microscopy (AFM), electron microscopy (EM), and nuclear magnetic resonance (NMR) data, the synergistic three-step computational approaches of 3D-QSAR (3D-Quantitative Structure-Activity Relationship), molecular docking, and molecular dynamics simulation is developed to systematically and efficiently screen and design hexapeptide inhibitors from the first principle. Computationally designed inhibitors are then validated for their inhibition activity by biophysical experiments. To reach its goal, three specific aims are: (1) to develop an efficient and novel 3D-QSAR model to virtually screen and rationally design Aâ inhibitors; (2) to computationally examine inhibitory activity of peptides that disrupt or bind to Aâ oligomers; and (3) to experimentally test inhibitory ability of computationally designed peptides to prevent Aâ aggregation and toxicity. Through these aims, we strive to rationally design of effective peptide inhibitors, to establish the predictive relationship among sequence, structure, and inhibitory activity of inhibitors, and to better understand the inhibition mechanisms between inhibitors and Aâ oligomers at the atomic level, and eventually to provide a hexapeptide inhibitor database with well-characterized structural and biological data. The proposed work can be transformative in other biological systems involving protein folding, binding, and protein function.Broad Impacts: The success of this anti-amyloid project will bridge the gap between a fundamental understanding of Aâ structure, aggregation, toxicity, and inhibition mechanism at molecular level and a practical design principle of Aâ inhibitors, both critical for the development of medical diagnostics and automated high-throughput devices against Alzheimer's disease. The proposed approach can also be generally applicable to designing peptide inhibitors against other amyloidogenic diseases such as Parkinson's and diabetes type II, benefiting both scientific community and entire society. The interdisciplinary nature of the project provides a unique opportunity for all-level students, particularly those from underrepresented groups, to learn the concepts and tools in general biology, structural biology, bioinformatics, and drug design and to carry out a fundamental research project important for public health. The results from this proposal will continuously contribute to two new courses of "Molecular Modeling and Simulation of Biological Systems" and "Biomaterials and Bionanotechnology". The knowledge will also be disseminated through high-impact papers, conference presentations, curriculum courses, summer internships, and other outreach activities. In addition, amyloids also represent a general class of nanomaterials with well-defined nanostructures, which can be used as templates to produce novel protein-based self-assembled nano-/bio-materials with desirable functionalities. Molecular understanding of the abnormal self-assembly of amyloid peptides into such well-defined nanoarchitectures and the role of their interactions with inhibitors is essential for the rational design of novel drugs for prevention or treatment of neurodegenerative disorders.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Mechanistic Design and Understanding of Fully Polymeric Antifreezing and Tough Hydrogels
-
批准号:2311985
-
项目类别:Standard Grant
-
资助金额:$41.8万
-
财政年份:2023
-
负责人:Jie Zheng
-
依托单位:
Rational Design and Fundamental Understanding of Multimodal Amyloid Probes
-
批准号:2107619
-
项目类别:Standard Grant
-
资助金额:$36.2万
-
财政年份:2021
-
负责人:Jie Zheng
-
依托单位:
MRI: Acquisition of A High-sensitivity Electrospray Ionization Mass Spectrometer for Research and Education at the University of Texas at Dallas
-
批准号:2018188
-
项目类别:Standard Grant
-
资助金额:$24.31万
-
财政年份:2020
-
负责人:Jie Zheng
-
依托单位:
Combinatorial Design and Structure-Property Relationships of Antifouling Materials
-
批准号:1806138
-
项目类别:Continuing Grant
-
资助金额:$34.09万
-
财政年份:2018
-
负责人:Jie Zheng
-
依托单位:
Design of Force-Sensitive Hydrogels for Adhesives and Strain Sensors
-
批准号:1825122
-
项目类别:Standard Grant
-
资助金额:$30.21万
-
财政年份:2018
-
负责人:Jie Zheng
-
依托单位:
Molecular Understanding and Design of Physically-linked Double Network Hydrogels
-
批准号:1607475
-
项目类别:Continuing Grant
-
资助金额:$34.36万
-
财政年份:2016
-
负责人:Jie Zheng
-
依托单位:
UNS: Design of Self-Assembling Peptides and their Conjugates as Amyloid Inhibitors
-
批准号:1510099
-
项目类别:Standard Grant
-
资助金额:$29.01万
-
财政年份:2015
-
负责人:Jie Zheng
-
依托单位:
CAREER: Computational studies of the structure and biological activity of amyloid forming peptides
-
批准号:0952624
-
项目类别:Continuing Grant
-
资助金额:$40.0万
-
财政年份:2010
-
负责人:Jie Zheng
-
依托单位:
国内基金
海外基金
Applications of AI in Market Design
-
批准号:--
-
项目类别:外国青年学者研 究基金项目
-
资助金额:--
-
批准年份:2024
-
负责人:Manshu Khanna
-
依托单位:
基于“Design-Build-Test”循环策略的新型紫色杆菌素组合生物合成研究
-
批准号:
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2021
-
负责人:
-
依托单位:
在噪声和约束条件下的unitary design的理论研究
-
批准号:12147123
-
项目类别:专项基金项目
-
资助金额:18万元
-
批准年份:2021
-
负责人:顾炎武
-
依托单位: