DE NOVO MODELING TOOL (GORGON)

从头建模工具 (GORGON)

• 批准号: 8361084
• 负责人: MARC L BAKER
• 金额: $ 4.9万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-01-01 至 2011-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8361084
• 关键词: Algorithms; Biological Process; Biology; Cryoelectron Microscopy; Electron Microscopy; Elements; Funding; Goals; Grant; Image; Macromolecular Complexes; Manuals; Maps; Mining; Modeling; Molecular Models; Molecular Structure; National Center for Research Resources; Pattern; Physiological; Principal Investigator; Process; Protocols documentation; Reporting; Research; Research Infrastructure; Resolution; Resources; Role; Source; Structural Models; Structure; United States National Institutes of Health; Visual; cost; density; macromolecule; molecular modeling; protein structure; tool; user-friendly

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.

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