Computational design of new protein structures and interactions

新蛋白质结构和相互作用的计算设计

基本信息

批准号：
10396457
负责人：
Tanja Kortemme
金额：
$ 34.89万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-05-01 至 2023-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10396457
关键词：
Address Algorithms Amino Acids Behavior Benchmarking Binding Proteins Binding Sites Biological Biological Process Biology Biomedical Engineering Biomedical Research Biosensor Biotechnology Cell physiology Cells Chemicals Combinatorial Optimization Communities Complex Computing Methodologies Crystallization Custom Development Dimerization Disease Elements Engineering Environment Design Family Foundations Gene Expression Geometry Health Industrialization Intuition Knowledge Length Ligand Binding Ligands Manuals Medicine Methodology Methods Molecular Molecular Conformation Nature Production Protein Engineering Protein Fragment Proteins Regulation Research Scaffolding Protein Side Signal Transduction Signaling Molecule Signaling Protein Site Structure System Technology Testing Variant Vertebral column Work cancer therapy cell behavior data repository design improved innovation metabolic engineering neurotensin mimic 2 novel strategies novel therapeutics practical application protein function protein structure response scaffold sensor small molecule tool

项目摘要

PROJECT SUMMARY/ABSTRACT Computational design has immense potential to create new protein functions with applications in biotechnology, biology, and medicine. However, despite exciting progress in designing proteins with de novo structures, our ability to design proteins with new functions lags behind. A key reason for this discrepancy is that function typically requires protein geometries that deviate from the “idealized” folds of de novo designed structures and that are hence more difficult to design. The long-term objective of our work is to advance computational design to make predictive design of more complex functions possible. The specific objective of this proposal is to address the generally unsolved problem of designing proteins that bind new small molecule ligands. A particular application is the design of new sensor/actuators: proteins that can detect a user-defined small molecule signal and trigger a biological response (such as protein signaling or gene expression). Significant applications of such sensor/actuators include maximizing production of industrially valuable chemicals in metabolic engineering, creating precise tools for dissecting biological processes in cell signaling, and achieving tight regulation in emerging cancer therapies. Our work in the prior project period has advanced methods for binding site design and applied them to engineer the first computationally designed chemically-induced protein dimerization system, which senses and responds to a new ligand in living cells; a crystal structure confirmed the accuracy of the de novo designed binding site. Despite this key progress, there are significant barriers to generalize the approach. The first step in engineering new ligand binding sites is generally to identify desired binding site geometries (constellations of amino acid side chains coordinating the ligand). The second step is then to place those geometries into a suitable protein termed “scaffold”. This approach is critically limited by available geometries, both for binding sites and scaffolds to accommodate them. To address these problems, we propose two key methodological innovations: Aim 1 will establish and experimentally test a new computational method to generate millions of possible binding site geometries de novo that can be built into proteins. Aim 2 will develop and test a new computational approach to build “de novo fold families” (sets of custom-shaped de novo designed proteins) by systematically varying the geometries of structural elements within a given fold topology, to be used as scaffolds. Feasibility is supported by preliminary results for both aims; we have designed new binding sites (prior period), and have solved structures of 3 de novo designed proteins with the same fold but distinct geometries. The proposed studies innovate in creating both new methods and new molecules that expand designable structures and functions and overcome problems with current approaches limited by available geometries. Ultimately, these studies will lead to advanced computational design methods that we will make freely available, new knowledge on strengths and limitations of these methods to drive further developments, and new tools to control cellular behavior in biological engineering and to probe basic and disease biology.

项目概要/摘要计算设计在生物技术应用中具有创造新蛋白质功能的巨大潜力，然而，尽管在设计具有从头结构的蛋白质方面取得了令人兴奋的进展，但我们的研究仍然存在。设计具有新功能的蛋白质的能力落后，造成这种差异的一个关键原因是功能。通常需要偏离从头设计结构的“理想化”折叠的蛋白质几何形状，因此更难以设计。我们工作的长期目标是推进计算设计。使更复杂功能的预测设计成为可能。该提案的具体目标是解决了设计结合新小分子配体的蛋白质这一普遍未解决的问题。应用程序是新传感器/执行器的设计：可以检测用户定义的小分子信号的蛋白质并触发生物反应（例如蛋白质信号传导或基因表达）。此类传感器/执行器包括在代谢工程中最大限度地生产具有工业价值的化学品，创建精确的工具来剖析细胞信号传导中的生物过程，并实现严格的调控我们在之前的项目期间的工作具有先进的结合位点设计方法。并将它们应用于工程第一个计算设计的化学诱导蛋白质二聚化系统，它能够感知活细胞中的新配体并对其做出反应；晶体结构证实了 de 的准确性。尽管取得了这一关键进展，但推广该方法仍存在重大障碍。设计新配体结合位点的第一步通常是确定所需的结合位点几何形状（协调配体的氨基酸侧链的星座）然后第二步是放置它们。将几何形状转化为称为“支架”的合适蛋白质，这种方法受到可用几何形状的严重限制，为了解决这些问题，我们提出了两个关键点。方法创新：目标 1 将建立并实验测试一种新的计算方法 Aim 2 将开发从头生成数百万个可能的结合位点几何形状，并将其构建到蛋白质中。并测试一种新的计算方法来构建“从头折叠家族”（一组定制形状的从头设计蛋白质）通过系统地改变给定折叠拓扑内结构元件的几何形状，以使用作为支架，我们设计了新的结合位点，这得到了初步结果的支持。（前期），并解决了 3 个从头设计的具有相同折叠但不同的蛋白质的结构拟议的研究在创造新方法和新分子方面进行了创新。可设计的结构和功能，并克服当前方法受可用限制的问题最终，这些研究将带来我们将制定的先进计算设计方法。免费提供有关这些方法的优点和局限性的新知识，以推动进一步发展，以及控制生物工程中细胞行为以及探索基础生物学和疾病生物学的新工具。