DE NOVO MODELING TOOL (GORGON)

这个子项目是利用资源的许多研究子项目之一。 由NIH/NCRR资助的中心拨款提供。对子项目的主要支持 子项目的首席调查员可能是由其他来源提供的， 包括美国国立卫生研究院的其他来源。为子项目列出的总成本可能 表示该子项目使用的中心基础设施的估计数量， 不是由NCRR赠款提供给次级项目或次级项目工作人员的直接资金。 生物学中最突出的挑战之一是定量描述 大分子络合物及其在生物过程中的作用。电子冷冻显微镜 (冷冻-EM)能够在离散的生理状态下对这些大型组件进行成像。直到 最近，Cryo-EM无法达到建立结构模型所需的分辨率 在没有初始模板的情况下直接从密度贴图。最近，几个低温EM 结构已经报告了近原子的分辨率(5-3.3？)，在这一点上，？的音调- 螺旋、链的分离以及连接它们的密度可能是 毫不含糊地形象化。为这些近原子分辨率密度建立的从头模型 地图几乎完全依赖于密度的视觉解释和手动结构 任务。由于构建新模型的复杂性，我们创建了Gorgon，一个 面向近原子分辨率密度图的交互式分子建模工具包 (http://gorgon.wustl.edu).)Gorgon是围绕我们的从头建模协议构建的，该协议 利用模式匹配和几何处理算法快速准确地建模 蛋白质结构。Gorgon还集成了几个用于建模和挖掘的独特实用程序 包括二级结构元素(SSE)在内的亚纳米分辨率的信息 识别和刚体拟合。通过Gorgon，我们的最终目标是为用户提供 全面的、用户友好的界面，用于在非 原子分辨率。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. One of the outstanding challenges in biology is the quantitative description of macromolecular complexes and their roles in biological processes. Electron cryomicroscopy (cryo-EM) is capable of imaging these large assemblies in discrete physiological states. Until recently, cryo-EM was unable to achieve the resolution needed to build structural models directly from the density map without an initial template. Recently, several cryo-EM structures have reported near-atomic resolutions (5-3.3 ¿), at which point the pitch of ¿- helices, separation of ¿-strands, as well as the densities that connect them, could be visualized unambiguously. De novo models built for these near-atomic resolution density maps relied almost entirely on visual interpretation of the density and manual structural assignment. Due to the complexity of building de novo models, we created Gorgon, an interactive molecular modeling toolkit targeted towards near-atomic resolution density maps (http://gorgon.wustl.edu). Gorgon is built around our de novo modeling protocols, which utilize pattern matching and geometry processing algorithms to quickly and accurately model protein structure. Gorgon also incorporates several unique utilities for modeling and mining information at subnanometer resolutions including secondary structure element (SSE) identification and rigid body fitting. With Gorgon, our ultimate goal is to provide users with a comprehensive, user-friendly interface for modeling the structure of macromolecular at non- atomic resolutions.