Prediction and Design of Nucleic Acid Recognition by Repeat Proteins

描述(由申请人提供)：原子详细的分子建模是预测和设计蛋白质相互作用的有力工具。在这个项目中，我们将开发分子建模技术来模拟串联重复蛋白与其结合伙伴之间的相互作用，重点是识别核酸的重复蛋白。重复蛋白通常具有高度对称的结构，单个重复单位具有类似的构象；在识别诸如核酸或肽的模块伙伴的重复蛋白的情况下，这种对称性也可能延伸到结合伙伴的构象。我们的建模框架将结合重复蛋白质相互作用的对称性，以限制必须探索的构象和蛋白质序列的空间。串联重复蛋白为蛋白质相互作用提供了一种结构，这种结构在整个生物进化过程中被重复使用，以产生特定的结合蛋白。Aradillo、TPR、ankyrin和Het Repeat蛋白质已被选择用于蛋白质-蛋白质相互作用，而C2H2锌指、PUF和PPR重复序列被广泛用于核酸的序列特异性识别。最近，一个新的细菌重复蛋白家族--转录激活物样(TAL)效应器--被发现以一种显著的模块化方式识别DNA，每个重复根据一个简单的识别密码瞄准DNA结合位点的一个碱基。使用这种识别代码，工程的TAL效应器可以有效地靶向新的DNA位点；这种能力正在改变目前的基因组工程方法。为了理解这种识别密码背后的分子机制，我们利用结构对称性对TAL效应器-DNA相互作用进行了分子建模模拟，并预测了蛋白质-DNA接触以减少可能的结合构象空间。使用这些模拟，我们能够生成TAL效应器-DNA复合体的准确分子模型；随后，我们使用这些模型通过分子置换来解决自然产生的TAL效应器与DNA络合物的第一个晶体结构。我们建议扩展这些模拟来预测和设计不同范围的串联重复序列-蛋白质：核酸相互作用，有两个具体的应用：(1)优化模块化DNA序列识别的TAL效应器平台，(2)预测五肽重复(PPR)蛋白质的RNA结合模式，这是一个广泛的RNA结合蛋白质家族，可能代表一个新的和强大的单链RNA靶向支架。

DESCRIPTION (provided by applicant): Atomically detailed molecular modeling is a powerful tool for the prediction and design of protein interactions. In this project, we will develop molecular modeling techniques for simulating interactions between tandem repeat proteins and their binding partners, focusing on repeat proteins that recognize nucleic acids. Repeat proteins typically have highly symmetrical structures, with individual repeat units assuming similar conformations; in the case of repeat proteins that recognize a modular partner such as a nucleic acid or peptide, this symmetry may also extend to the conformation of the binding partner. Our modeling framework will incorporate the symmetry of repeat-protein interactions in order to constrain the space of conformations and protein sequences that must be explored. Tandem repeat proteins provide an architecture for protein interactions that has been used repeatedly throughout biological evolution to generate specific binding proteins. Armadillo, TPR, ankyrin, and HEAT repeat proteins have been selected for use in protein-protein interactions, while C2H2 zinc fingers, PUF, and PPR repeats are widely deployed for sequence-specific recognition of nucleic acids. Recently, a novel family of bacterial repeat proteins - the transcriptional activator-like (TAL) effectors - has been discovered that recognizes DNA in a remarkably modular fashion, with each repeat targeting a single base of the DNA binding site according to a simple recognition code. Using this recognition code, engineered TAL effectors can be efficiently targeted to novel DNA sites; this capability is transforming current approaches to genome engineering. To understand the molecular mechanisms underlying this recognition code, we performed molecular modeling simulations of TAL effector-DNA interactions that used structural symmetry and predicted protein-DNA contacts to reduce the space of possible bound conformations. Using these simulations we were able to generate accurate molecular models of TAL effector-DNA complexes; we subsequently used these models to solve, by molecular replacement, the first crystal structure of a naturally occurring TAL effector in complex with DNA. We propose to extend these simulations to allow prediction and design of a diverse range of tandem repeat-protein:nucleic acid interactions, with two specific applications: (1) optimization of the TAL effector platform for modular DNA sequence recognition, and (2) prediction of the RNA binding mode of pentatricopeptide repeat (PPR) proteins, a widespread family of RNA binding proteins that may represent a new and powerful ssRNA targeting scaffold.