Software for Homology Modeling of Ribosomes

描述（由申请人提供）：在基因组学时代，序列数据库的指数增长是由理解基本大分子结构机制以及这些结构如何与细胞中的寡核苷酸、蛋白质和代谢物相互作用的愿望所促进的。然而，可用的相应3D结构的数量存在巨大差异。目前的3D结构测定实验方法，如X射线晶体学和核磁共振，可能是繁琐和有问题的，需要大量的时间投资以及受过这些技术培训的专家团队。为了解决这些问题，开发了软件工具来模拟大分子复合物，但它们是基本的，因为它们仍然是非常昂贵的计算，它们不能模拟非常大的大分子结构，如核糖体，它们没有统一到一个单一的平台，并且它们至今没有被严格评估。在这个快速通道SBIR应用DNA软件公司。提出扩展现有3D同源结构预测平台的功能。我们目前的原型软件RNA-123专注于RNA，它已经可以使用基于序列的同源性建模准确预测5S rRNA（约120个核苷酸长）大小的分子的3D结构。该软件的工程和功能扩展将使研究人员能够首次研究整个核糖体的结构机制。RNA-123将使人们有可能模拟病原性细菌核糖体，在那里目前不存在晶体结构，及时利用它们来开发新的合理设计的RNA靶向药物。这一目标将在七个具体目标（第一阶段的目标1 - 3和第二阶段的目标1 - 4）中实现：目标1.1：设计现有的3D预测技术，RNA-123，并扩展其能力，以预测更大序列和复合物的3D结构。目的1.2：预测T.利用已知的嗜热大肠杆菌16SrRNA的三维晶体结构，coli作为模板，反之亦然。目的1.3：通过评估目的1.2中预测的16S rRNA结构，测试目的1.1中开发的软件。目标2.1：扩展第1阶段开发的软件的功能，以允许对细菌或真核生物核糖体大小的蛋白质-RNA复合物进行同源建模。目标2.2：预测和评估已知的完整核糖体（70S）和核糖体亚基（30S和50S）的结构，以测试在第一阶段和第二阶段目标1中开发的软件。目的2.3：E. coli的16S rRNA突变体及其生物学活性。目的2.4：预测铜绿假单胞菌和S.金黄色葡萄球菌，2种临床上重要的病原体。这项拨款将对整个科学界产生长期影响，因为一旦RNA-123的功能扩展到能够对整个核糖体进行同源建模，它就可以很容易地适用于模拟生物聚合物，DNA和碳水化合物以及它们相互之间的复合物，RNA和药物样小分子。RNA-123将为科学家提供最新、最准确的生物信息学工具，对全人类产生直接影响。

DESCRIPTION (provided by applicant): The exponential growth of sequence databases in the genomics era was promoted by the desire to understand fundamental macromolecular structural mechanisms, and how these structures interact with oligonucleotides, proteins and metabolites in a cell. However, a huge discrepancy in the number of corresponding 3D structures available exists. Current experimental methods of 3D structure determination, such as X-ray crystallography and Nuclear Magnetic Resonance, can be cumbersome and problematic, requiring a huge time investment as well as a team of experts that are trained in these techniques. To address these concerns software tools were developed to model macromolecular complexes, but they are rudimentary in that they are still very computationally expensive, they cannot model very large macromolecular structures such as the ribosome, they are not unified into a single platform, and they have not been critically evaluated to date. In this Fast Track SBIR application DNA Software, Inc. proposes to extend the functionality of an existing 3D homology structure prediction platform. Our current prototype software, RNA-123, has focused upon RNA and it can already accurately predict the 3D structures of molecules the size of 5S rRNA (~120 nucleotides long) using sequence-based homology modeling. The engineering and extension of the functionality of this software will enable a researcher, for the very first time, to study the structural mechanisms of a whole ribosome. RNA-123 will make it possible to model pathogenic bacterial ribosomes, where no crystal structures currently exist, to exploit them in a timely manner to develop new classes of rationally designed RNA-targeted drugs. This objective will be accomplished in seven specific aims (aims 1-3 in Phase I and aims 1-4 in Phase II): Aim 1.1: Engineer existing 3D prediction technology, RNA-123, and extend its capabilities to allow for the prediction of 3D structures of larger sequences and complexes. Aim 1.2: Predict the 3D structure of 16S rRNA of T. Thermophilus by using the known 3D crystal structure of 16S rRNA of E. coli as a template and vice versa. Aim 1.3: Test the software developed in aim 1.1 by assessing the 16S rRNA structures predicted in aim 1.2. Aim 2.1: To extend the capabilities of the software developed in phase 1 to allow homology modeling of protein-RNA complexes the size of a bacterial or eukaryotic ribosome. Aim 2.2: Predict and evaluate structures for the known complete ribosomes (70S) and ribosomal subunits (30S and 50S) to test the software developed in aims 1 of phase I and II. Aim 2.3: Correlation of predicted 3D structures of E. coli's 16S rRNA mutants with their biological activity. Aim 2.4: Predict 3D structure of the complete ribosomes of P.aeruginosa, and S. aureus, 2 clinically important pathogens. This grant will have long-term effects on the scientific community as a whole, because once the functionality of RNA-123 is extended to be able to homology model an entire ribosome, it can be easily adapted to model biopolymers, DNA, and carbohydrates as well as their complexes with each other, RNA, and drug-like small molecules. RNA-123 will enable scientists with the latest, most accurate bioinformatics tool available, having an immediate impact on all of humanity.