Suppr超能文献

大分子结构数据库:过去的进展与未来的挑战。

Macromolecular structure databases: past progress and future challenges.

作者信息

Weissig H, Shindyalov I N, Bourne P E

机构信息

San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.

出版信息

Acta Crystallogr D Biol Crystallogr. 1998 Nov 1;54(Pt 6 Pt 1):1085-94. doi: 10.1107/s0907444998009846.

Abstract

Databases containing macromolecular structure data provide a crystallographer with important tools for use in solving, refining and understanding the functional significance of their protein structures. Given this importance, this paper briefly summarizes past progress by outlining the features of the significant number of relevant databases developed to date. One recent database, PDB+, containing all current and obsolete structures deposited with the Protein Data Bank (PDB) is discussed in more detail. PDB+ has been used to analyze the self-consistency of the current (1 January 1998) corpus of over 7000 structures. A summary of those findings is presented (a full discussion will appear elsewhere) in the form of global and temporal trends within the data. These trends indicate that challenges exist if crystallographers are to provide the community with complete and consistent structural results in the future. It is argued that better information management practices are required to meet these challenges.

摘要

包含大分子结构数据的数据库为晶体学家提供了重要工具,用于解析、优化和理解其蛋白质结构的功能意义。鉴于其重要性,本文通过概述迄今为止开发的大量相关数据库的特点,简要总结了过去的进展。最近的一个数据库PDB+被更详细地讨论,它包含了提交给蛋白质数据库(PDB)的所有当前和过时的结构。PDB+已被用于分析当前(1998年1月1日)超过7000个结构的语料库的自洽性。这些发现的总结以数据中的全局和时间趋势的形式呈现(完整讨论将在其他地方发表)。这些趋势表明,如果晶体学家未来要为科学界提供完整和一致的结构结果,存在一些挑战。有人认为需要更好的信息管理实践来应对这些挑战。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验