Deep Topological Sampling of Protein Structures

项目摘要。大多数蛋白质是对称的寡聚复合物。尽管它们普遍存在， 生物医学的重要性，这种复合物在PDB中的代表性大大不足， 核磁共振结构生物学家提出了艰巨的挑战。具体地，模拟退火（SA）， 一种广泛使用的用于同源寡聚物结构测定的技术， 错误.由于分配模糊性，SA收敛到局部最小值而不是最优结构或 数据显示的结构整体。折叠算子理论克服了这些错误，使用系统的 搜索算法，以确定生物学上重要的任务和结构，SA没有发现。为 例如，二酰基甘油激酶（DAGK）的已公布的NMR和晶体结构具有非常高的 不同的拓扑结构。我们的系统搜索技术不仅表明，这两个出版的褶皱是 支持的NMR数据，但也发现了一个新的折叠，满足数据比任何公布的倍。 我们建议开发新的算法和软件，使全球和系统的搜索核磁共振 结构测定，建立在我们的初步结果表明，我们的方法可以解决问题 传统的随机核磁共振方法难以实现。这些新工具将大大提高 NMR结构确定与分配模糊性，这必然会出现高阶对称 同源寡聚物。所提出的深度拓扑采样（Deep Topological Sampling，简称DSB）有两个主要模块： 理论（FOT）;和DISCO（我们最近使用它来解决膜相关MPER的结构 设计用于探测对HIV-1病毒外壳蛋白gp 41的免疫原性应答的同源三聚体）。 目标1：我们将在软件中实现一个通用的FOT，以计算与 NMR数据。FOT将在褶皱上进行全局搜索，避免陷入局部最小值，以找到所有令人满意的 结构.目标2：我们将开发我们的DISCO算法，在FOT生成的每个可行折叠内进行搜索， 找到所有可行的低能耗结构DISCO和FOT将开发新的几何和拓扑算法 准确有效地执行自动化分配，从而减少最耗时和 这是多聚体结构测定中潜在的易错步骤。目标3：我们将应用我们的FOT/EQUIPMENT软件 （在目标1-2中发展的）对重要系统的前瞻性。(A)我们将进行实验，以确定 DAGK在其原生环境中采用的真正功能结构。(B)我们将使用我们的方法来确定 更大的HIV-1膜结合的融合前gp 41三聚体构建体的结构暴露了瞬时的， 结合广泛中和抗体的中间表位，但在较大的实验室中结构上不可见 结构。(C)我们将解决半融合中间结构的抗原，对称的同源， 寨卡病毒是一种新型的全球性健康威胁。我们的小说开篇- 源软件可以应用于病毒和细菌病原体中的大量对称蛋白质靶。

Project Summary. Most proteins are symmetric oligomeric complexes. Despite their prevalence and biomedical importance, such complexes are vastly underrepresented in the PDB, and determining their structures presents daunting challenges for NMR structural biologists. In particular, simulated annealing (SA), a widely-used technique for structure determination of homo-oligomers, is vulnerable to significant structural errors. Due to assignment ambiguity, SA converges to local minima rather than to the optimal structure or structural ensemble indicated by the data. Fold Operator Theory overcomes these errors, using a systematic search algorithm shown to identify biologically important assignments and structures that SA does not find. For example, the published NMR and crystal structures of the enzyme Diacylglycerol Kinase (DAGK) have very different topologies. Our systematic search techniques not only showed that both published folds are supported by the NMR data, but also found a novel fold that satisfies the data better than either published fold. We propose to develop novel algorithms and software enabling global and systematic search for NMR structure determination, building on our preliminary results showing that our methods can solve problems where traditional stochastic NMR methods struggle. These new tools will dramatically increase the accuracy of NMR structure determination with assignment ambiguity, which unavoidably arises for higher-order symmetric homo-oligomers. The proposed Deep Topological Sampling (DTS) has two primary modules: Fold Operator Theory (FOT); and DISCO (which we recently used to solve the structure of a membrane-associated MPER homo-trimer designed to probe immunogenic responses to the HIV-1 viral coat protein gp41). Aim 1: We will implement a general FOT in software, to compute all the protein folds consistent with the NMR data. FOT will search globally over folds, and avoid being trapped in local minima, to find all satisfying structures. Aim 2: We will develop our DISCO algorithm to search within each viable fold generated by FOT to find all feasible low-energy structures. DISCO and FOT will exploit novel geometric and topological algorithms to perform automated assignments accurately and efficiently, thus alleviating the most time-consuming and potentially error-prone step in multimeric structure determination. Aim 3: We will apply our FOT/DTS software (developed in Aims 1-2) prospectively to important systems. (A) We will perform experiments to determine the true functional structure DAGK adopts in its native environment. (B) We will use our methods to determine the structure of a larger HIV-1 membrane-associated pre-fusion gp41 trimer construct exposing transient, intermediate epitopes that bind broadly neutralizing antibodies, but are structurally invisible in larger laboratory constructs. (C) We will solve the hemifusion intermediate structures of the antigenic, symmetric homo- oligomeric domains of the Zika virus envelope protein, an emerging global health threat. Our novel open- source software can be applied to a vast array of symmetric protein targets in viral and bacterial pathogens.