Prediction of the Structure of Therapeutic Antibodies with their Antigens

治疗性抗体结构及其抗原的预测

• 批准号: 7279806
• 负责人: JEFFREY J GRAY
• 金额: $ 25.09万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7279806
• 关键词: Accounting; Affinity; Algorithms; Antibodies; Antidotes; Antigen-Antibody Complex; Antigens; Antineoplastic Agents; Binding; Biological Models; Class; Complex; Development; Discrimination; Disease; Docking; Drug effect disorder; Effectiveness; Epidermal Growth Factor Receptor; Family; Foundations; Gray unit of radiation dose; Homology Modeling; Immunoglobulin G; Infectious Agent; Malignant Neoplasms; Methods; Modification; Monoclonal Antibodies; Mutagenesis; Personal Satisfaction; Pharmaceutical Preparations; Phase; Placement; Process; Protein Engineering; Proteins; Public Health; Research; Research Personnel; Resolution; Sampling; Score; Specificity; Structure; System; Techniques; Technology; Testing; Therapeutic antibodies; Thermodynamics; Uncertainty; Vertebral column; anthrax toxin; base; computerized tools; cytotoxic; drug mechanism; improved; interest; monomer; novel; novel therapeutics; prevent; programs; protonation; tool; tumor

DESCRIPTION (provided by applicant): Therapeutic antibodies constitute a major class of current drugs under development because they can bind with high affinity and specificity to particular targets in the body or on an infectious agent. The structure of a therapeutic antibody bound to its antigen can be of value to reveal the structural origin of the mechanism of the drug's action and possibly indications of the mechanism of the antigen itself in a disease process. Also, the structure can be exploited for further protein engineering such as increasing binding affinity. We propose to develop tools to predict the structure of antibody-antigen complexes starting from the sequence of the antibody and an unbound structure of the antigen. We will improve and tailor docking scoring functions, develop homology models for docking, and develop flexible loop algorithms for docking to account for uncertainties in a homology antibody structure. Antibodies make an ideal test system for homology docking and flexible loop docking because the IgG fold is well-defined; when these techniques are developed, they will be of broad impact for the docking field in general. Finally, we will apply these techniques to two model systems for which the antibody-antigen complex structure is unknown. Monoclonal antibody 806 binds to the epidermal growth factor receptor and has been shown to be an effective therapy against several types of tumors. The 14B7 family of antibodies binds the anthrax toxin and prevents its cytotoxic effects. Both complex structures are currently unknown. We will predict structures and collaborate to validate the predictions experimentally. This research is relevant to public health because it will provide general computational tools to discover the structural mechanism of new protein drugs. In addition, this research will determine the structure for a novel cancer drug bound to its target and a novel antidote bound to the anthrax toxin, revealing the structural basis of the therapies and providing a foundation to tailor the drugs to increase their effectiveness.

描述（由申请人提供）：治疗性抗体是目前正在开发的药物的主要类别，因为它们可以以高亲和力和特异性结合体内或感染因子的特定靶点。结合其抗原的治疗性抗体的结构对于揭示药物作用机制的结构起源以及抗原本身在疾病过程中的机制可能具有价值。此外，该结构可用于进一步的蛋白质工程，如增加结合亲和力。我们建议开发工具来预测抗体-抗原复合物的结构，从抗体序列和抗原的非结合结构开始。我们将完善和定制对接评分函数，开发对接的同源模型，开发灵活的对接环路算法，以考虑同源抗体结构的不确定性。抗体是一种理想的同源对接和柔性环对接测试系统，因为IgG折叠层定义明确；这些技术的发展将对整个对接领域产生广泛的影响。最后，我们将把这些技术应用于两个模型系统，其中抗体-抗原复合物结构未知。单克隆抗体806结合表皮生长因子受体，已被证明是一种有效的治疗几种类型的肿瘤。14B7家族抗体结合炭疽毒素并阻止其细胞毒性作用。这两种复杂的结构目前都是未知的。我们将预测结构，并合作在实验上验证预测。这项研究与公共卫生相关，因为它将为发现新的蛋白质药物的结构机制提供通用的计算工具。此外，本研究将确定一种新型抗癌药物与其靶点结合的结构和一种新型炭疽毒素解毒剂的结构，揭示治疗的结构基础，并为定制药物以提高其有效性提供基础。