Prediction of the Structures of Protein Complexes

蛋白质复合物的结构预测 Jeffrey J. Gray，NIGMS R35（MIRA） 项目摘要 蛋白质相互作用涉及人类健康和疾病的几乎所有生物过程， 复杂的结构可以揭示生物学机制并提出干预策略。计算 建模为阐明结构提供了另一种途径。建模也测试了我们对 分子生物物理学，使我们能够根据分子的结构设计分子。我的实验室是 开发预测和设计蛋白质-蛋白质界面的计算方法，并应用这些方法 从免疫学和癌症到传染病和组织工程学。我们的中心焦点 是蛋白质-蛋白质对接，也就是说，预测复合物的结构，从组件（个人） 多肽或结构域）。对接中的一个长期挑战是正确捕获蛋白质构象 我们引领创新搜索策略和快速评分计划的发展，以缩小这一差距。 另一个重点领域是抗体的建模和设计，直接支持药物和诊断试剂 发展和优化。我们从序列中预测高分辨率的抗体结构， 抗原模型，并设计针对特定抗原的抗体。几种蛋白质修饰是重要的 在接口建模时要考虑的问题。强大的实验方法的出现， 聚糖促使我们扩展我们的工具来模拟碳水化合物，包括对接方法和重点 糖基转移酶的研究。我们所有的方法都嵌入在Rosetta软件平台中， 来自世界各地数以万计的学术和工业科学家。我们的工作的效用是由高证明 我们预测和设计的Web服务器，脚本平台，和教材的需求。通过引领 我的实验室为罗塞塔共享区的技术和科学测试操作提供动力，使协同作用联合收割机 罗塞塔强大的生物分子预测和设计方法在这个国际合作。

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.