Hierarchical Methods for Large BioMolecular Complexes

描述（由申请人提供）：大型生物分子复合物（lbc）形成了负责大多数生物过程的机制，并且与理解许多疾病（如癌症和代谢紊乱）相关。了解这些结构不仅可以提供大分子如何在组装中起作用的机制描述，还可以为开发与疾病相关的治疗干预提供线索。今天，利用低温电子显微镜（CryoEM）、电子断层扫描（ET）和x射线晶体学（Xray）或核磁共振波谱（NMR）的lbc混合实验方法，需要有能力地补充更快、更准确的计算处理，以便在尽可能高的分辨率下最终阐明lbc的超微结构。一旦重构了LBC的体积CryoEM图，该建议解决了增强型和自动化计算处理管道的开发问题。特别是，我们建议开发分层计算表示、算法和软件，以自动确定lbc的结构特征，并加快lbc与相关蛋白质和/或核酸之间的匹配和拟合技术。

DESCRIPTION (provided by applicant): Large Biomolecular Complexes (LBCs) form the machinery responsible for most biological processes and are relevant to understanding many diseases such as cancer and metabolic disorders. Knowledge of these structures would provide not only the mechanistic descriptions for how macromolecules act in an assembly but also clues in developing therapeutic interventions related to disease. Today, hybrid experimental approaches for LBCs utilizing cryo-electron microscopy (CryoEM), electron tomography (ET) and X-ray crystallography (Xray) or nuclear magnetic resonance spectroscopy (NMR), need to be ably complimented with faster and more accurate computational processing for final ultrastructure elucidation of LBCs at the best level of resolution that is possible. This proposal addresses the development of an enhanced and automated computational processing pipeline, once a volumetric CryoEM map of an LBC has been reconstructed. In particular we propose the development of hierarchical computational representations, algorithms and software, which automates structural feature determination of LBCs as well as speeds up match and fitting techniques between LBCs and relevant proteins and/or nucleic acids. More precisely, our specific aims are: AIM 1: To develop algorithms for determining structural features of LBCs from Cryo-EM maps at three different morphological scales. AIM 2: To develop algorithms for generating hierarchical, volumetric spline approximations of the determined structural features of LBCs to facilitate fast Fourier based correlation search methods. AIM 3: To develop fast correlation search methods using our volumetric spline approximations for LBCs, including structural feature identification, structure fitting, LBC and protein/RNA docking. AIM 4: To implement, test, package and freely distribute our structural feature determination and fast search/fitting techniques.