Prediction of the Structures of Protein Complexes

蛋白质复合物结构的预测

基本信息

批准号：
10693822
负责人：
JEFFREY J GRAY
金额：
$ 79.12万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-06-01 至 2026-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10693822
关键词：
Antibodies Antigens Area Binding Binding Proteins Biological Biological Process Biophysics Carbohydrates Collaborations Communicable Diseases Complex Computer Models Computer software Computing Methodologies Development Diagnostic Disease Docking Engineering Health Human Immunology Individual Industry Infrastructure International Intervention Lead Malignant Neoplasms Methods Modeling Molecular Molecular Conformation Molecular Structure National Institute of General Medical Sciences Pharmaceutical Preparations Polysaccharides Post-Translational Protein Processing Protein Conformation Protein Engineering Proteins Resolution Route Scheme Scientist Software Design Structure Teaching Materials Testing Tissue Engineering Training Work design drug mechanism innovation insight operation polypeptide protein complex protein function protein phosphatase inhibitor-2 protein protein interaction protein structure prediction scripting interface synergism three dimensional structure tool web interface web server

项目摘要

Prediction of the Structures of Protein Complexes Jeffrey J. Gray, NIGMS R35 (MIRA) PROJECT SUMMARY Protein interactions are involved in nearly all biological processes in human health and diseases, and protein complex structures can reveal biological mechanisms and suggest intervention strategies. Computational modeling provides an alternative route to elucidate structures. Modeling also tests our understanding of molecular biophysics and allows us to engineer molecules based on their structures. My lab is a pioneer in developing computational methods to predict and design protein–protein interfaces and in applying those methods broadly, from immunology and cancer to infectious disease and tissue engineering. Our central focus is on protein–protein docking, that is, predicting the structure of a complex from the components (individual polypeptides or domains). A longstanding challenge in docking is correctly capturing protein conformational change, and we lead development of innovative search strategies and rapid scoring schemes to close this gap. Another focus area is the modeling and design of antibodies, directly supporting drug and diagnostic agent development and optimization. We predict high-resolution antibody structures from sequence, dock those models to antigens, and design antibodies to target specific antigens. Several protein modifications are important to consider when modeling interfaces. The emergence of powerful experimental methods for characterizing glycans has prompted us to expand our tools to model carbohydrates including docking methods and focused studies on glycotransferases. All our methods are embedded in the Rosetta software platform, which is used by tens of thousands of academic and industry scientists worldwide. The utility of our work is evidenced by the high demand for our prediction and design web server, scripting platform, and teaching materials. By leading the technical and scientific testing operations for the Rosetta Commons, my lab powers the synergies to combine Rosetta's powerful biomolecular prediction and design methods across this international collaboration.

预测蛋白质复合物的结构 Jeffrey J. Gray，Nigms R35（Mira）项目摘要蛋白质相互作用几乎参与了人类健康和疾病的所有生物过程，以及蛋白质复杂的结构可以揭示生物学机制并提出干预策略。计算建模提供了阐明结构的替代途径。建模还测试了我们对分子生物物理学，使我们能够根据其结构来设计分子。我的实验室是一个先驱开发计算方法来预测和设计蛋白质 - 蛋白质界面，并应用这些方法从免疫学和癌症到传染病和组织工程的方法广义。我们的中心重点是关于蛋白质 - 蛋白质对接的，也就是说，从成分中预测复合物的结构（个体多肽或域）。对接中的长期挑战是正确捕获蛋白质构象变革，我们领导创新搜索策略和快速评分方案的发展，以缩小这一差距。另一个重点区域是抗体的建模和设计，直接支持药物和诊断剂开发和优化。我们从序列预测高分辨率抗体结构，对接那些抗原的模型，并设计抗体的抗体。几种蛋白质修饰很重要在建模接口时考虑。强大的实验方法的表征出现 Glycans促使我们将工具扩展到建模碳液体，包括对接方法和专注糖苷转移酶的研究。我们所有的方法都嵌入在Rosetta软件平台中，该平台使用全球成千上万的学术和行业科学家。我们工作的实用性得到了高位需求我们的预测和设计网络服务器，脚本平台和教材。通过领导 Rosetta Commons的技术和科学测试操作，我的实验室为协同作用加油罗塞塔（Rosetta）在这项国际合作中的强大生物分子预测和设计方法。