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Prediction of the Structure of Therapeutic Antibodies with their Antigens

治疗性抗体及其抗原结构的预测

基本信息

批准号：
9923648
负责人：
JEFFREY J GRAY
金额：
$ 34.24万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2006
资助国家：
美国
起止时间：
2006-09-01 至 2022-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9923648
关键词：
Accounting Affinity Algorithms Antibodies Antigen Targeting Antigen-Antibody Complex Antigens Bacterial Proteins Binding Binding Proteins Biological Biological Markers Biological Models Biotechnology Capsid Proteins Carbohydrates Celiac Disease Chemistry Communities Complementarity Determining Regions Complex Computing Methodologies Consumption Cryoelectron Microscopy Crystallography Disease Docking Engineering Epitopes Gluten Glycoproteins Goals Heart Diseases High-Throughput Nucleotide Sequencing Homology Modeling Human Hydration status Immune System Diseases Immune system Individual Knowledge Link Lung diseases Measures Medical Methods Modeling Modification Molecular Conformation Motion Occupations Oligosaccharides Pathology Peptide/MHC Complex Play Polysaccharides Proteins Pulmonary Hypertension Research Resolution Role Sampling Scheme Scoring Method Serum Side Source Specificity Structural Models Structure Technology Testing Therapeutic Therapeutic antibodies Time Uncertainty Vertebral column Viral Virus Work base conformer flexibility improved innovation nanofluidic resistin success sugar three dimensional structure web app

项目摘要

Prediction of the Structure of Therapeutic Antibodies with their Antigens PROJECT SUMMARY Antibodies play a critical role for recognition of foreign intruders. Due to their high affinity and specificity, they have been exploited as therapeutic molecules and biotechnological components for sensing and assembly. Recent high-throughput sequencing and nanofluidics technologies have elucidated large sets (103–104) of naïve and antigen-exposed antibody sequences, and it is now possible to determine a complete set of viruses that an individual has encountered based on one’s antibodies. In addition to their biological, medical, and technological importance, the extensive knowledge about antibodies makes them an ideal model system for studying protein binding and recognition. A reliable toolkit to study protein binding and recognition is the missing link to fully unlock the bountiful information in antibody and antigen repertoires. Prior work demonstrated success in predicting antibody structures, and this proposal focuses on the docking problem. While docking algorithms are reliable for local searches and small conformational changes, significant challenges remain in searching large antigens to identify epitopes and in determining the correct binding orientation when there is backbone flexibility or uncertainty in the homology-modeled starting structures. Accounting for binding-induced backbone conformational changes remains the central difficulty in the protein–protein docking field, primarily due to sampling limitations. An additional challenge is that many viral coat and bacterial proteins are glycosylated. Glycans are well hydrated and can be flexible; these modifications are typically ignored entirely by docking algorithms. The long-term goal of this research is the accurate prediction of structures of antibodies and antibody–antigen complexes such that they are useful to decode biological mechanisms and engineer improved therapeutics. Thus, the first two aims of the current project are to (1) develop fast, aggressive, flexible backbone docking approaches, and (2) extend docking to include glycosylated antigens. Finally, the third aim will be to (3) apply antibody modeling and docking to determine biomarkers and therapeutics for celiac disease and pulmonary hypertension.

用抗原预测治疗性抗体的结构项目摘要抗体在识别外来入侵者方面发挥着关键作用。由于其高亲和力和特异性，已经被开发作为用于传感和组装的治疗分子和生物技术组件。最近的高通量测序和纳米流体技术已经阐明了大组（103-104）的DNA序列。幼稚和抗原暴露的抗体序列，现在可以确定一套完整的病毒一个人所遇到的抗体除了他们的生物学，医学，由于技术的重要性，关于抗体的广泛知识使其成为理想的模型系统，研究蛋白质结合和识别。研究蛋白质结合和识别的可靠工具包是完全解开邦蒂富尔的抗体和抗原库中的信息。先前的工作证明了预测抗体的成功结构，这个建议的重点是对接问题。虽然对接算法对于本地搜索和小的构象变化，在搜索大的抗原以鉴定表位和确定正确的结合方向，当存在骨架柔性时，同源建模起始结构的不确定性。绑定引起的主干的核算构象变化仍然是蛋白质-蛋白质对接领域的中心难点，主要是由于取样限制。另一个挑战是许多病毒外壳和细菌蛋白是糖基化的。聚糖是很好的水合和灵活的，这些修改通常被完全忽略对接算法准确预测抗体和抗体-抗原的结构是本研究的长期目标复合物，使得它们可用于解码生物学机制和设计改进的治疗剂。因此，当前项目的前两个目标是：（1）开发快速、积极、灵活的骨干网对接方法，和（2）扩展对接以包括糖基化抗原。最后，第三个目标是（3）应用抗体建模和对接，以确定用于乳糜泻和肺部疾病的生物标志物和治疗剂高血压

项目成果

期刊论文数量（34）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Allosteric communication occurs via networks of tertiary and quaternary motions in proteins.

DOI：
10.1371/journal.pcbi.1000293
发表时间：
2009-02
期刊：
PLoS computational biology
影响因子：
4.3
作者：
Daily MD;Gray JJ
通讯作者：
Gray JJ

Comparison of NMR and crystal structures of membrane proteins and computational refinement to improve model quality.

DOI：
10.1002/prot.25402
发表时间：
2018-01
期刊：
Proteins
影响因子：
2.9
作者：
Koehler Leman J;D'Avino AR;Bhatnagar Y;Gray JJ
通讯作者：
Gray JJ

Structure-based design of supercharged, highly thermoresistant antibodies.

DOI：
10.1016/j.chembiol.2012.01.018
发表时间：
2012-04-20
期刊：
Chemistry & biology
影响因子：
0
作者：
Miklos AE;Kluwe C;Der BS;Pai S;Sircar A;Hughes RA;Berrondo M;Xu J;Codrea V;Buckley PE;Calm AM;Welsh HS;Warner CR;Zacharko MA;Carney JP;Gray JJ;Georgiou G;Kuhlman B;Ellington AD
通讯作者：
Ellington AD

Development and Evaluation of GlycanDock: A Protein-Glycoligand Docking Refinement Algorithm in Rosetta.