分辨率(逻辑)
构造(python库)
样板房
低分辨率
过程(计算)
质量(理念)
软件
算法
计算机科学
高分辨率
人工智能
程序设计语言
认识论
物理
地理
哲学
遥感
量子力学
作者
Gerard J. Kleywegt,T. Alwyn Jones
出处
期刊:Methods in Enzymology
日期:1997-01-01
卷期号:: 208-230
被引量:329
标识
DOI:10.1016/s0076-6879(97)77013-7
摘要
Publisher Summary Model refinement has been a personalized affair for which laboratories have their preferred strategies, programs, etc. This has resulted in models with distinctive features of both the groups concerned and the software used. This chapter discusses the way a macromolecule should be refined and argues that the present practices in the community are often far from optimal, especially when only low-resolution data are available. All refinement programs nowadays use empirical restraints or constraints to ensure that a reasonable structure ensues during the refinement steps. This can result in a model with good stereochemical properties and also in a model in which molecules related by non-crystallographic symmetry (NCS) are forced to have similar (restrained) or identical (constrained) conformations. The aim of model building and refinement should be to construct a model that adequately explains the experimental observations, while making physical, chemical, and biological sense. It is a fact that low-resolution data can yield only low-resolution models. The refinement process, in particular, should always be tailored for each problem individually, keeping in mind the amount, resolution, and quality of the data.
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