Suppr超能文献

基于似然的模型对接到冷冻电镜图谱中。

Likelihood-based docking of models into cryo-EM maps.

机构信息

Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom.

New Mexico Consortium, Los Alamos National Laboratory, 100 Entrada Drive, Los Alamos, NM 87544, USA.

出版信息

Acta Crystallogr D Struct Biol. 2023 Apr 1;79(Pt 4):281-289. doi: 10.1107/S2059798323001602. Epub 2023 Mar 15.

Abstract

Optimized docking of models into cryo-EM maps requires exploiting an understanding of the signal expected in the data to minimize the calculation time while maintaining sufficient signal. The likelihood-based rotation function used in crystallography can be employed to establish plausible orientations in a docking search. A phased likelihood translation function yields scores for the placement and rigid-body refinement of oriented models. Optimized strategies for choices of the resolution of data from the cryo-EM maps to use in the calculations and the size of search volumes are based on expected log-likelihood-gain scores computed in advance of the search calculation. Tests demonstrate that the new procedure is fast, robust and effective at placing models into even challenging cryo-EM maps.

摘要

优化模型与冷冻电镜图的对接需要利用对数据中预期信号的理解,在保持足够信号的同时最小化计算时间。晶体学中使用的基于似然的旋转函数可用于在对接搜索中建立合理的方向。分相似然平移函数为定向模型的放置和刚体精修生成得分。针对在计算中使用的冷冻电镜图数据的分辨率和搜索体积大小的选择,优化策略基于搜索计算之前预先计算的预期对数似然增益得分。测试表明,新程序在将模型放置到甚至具有挑战性的冷冻电镜图中时,速度快、鲁棒且有效。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f4/10071562/505599f300a8/d-79-00281-fig1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验