Suppr超能文献

最先进的生物信息学蛋白质结构预测工具(综述)。

State-of-the-art bioinformatics protein structure prediction tools (Review).

机构信息

Department of Pharmacy, School of Health Sciences, University of Patras, Rion-Patras, Greece.

出版信息

Int J Mol Med. 2011 Sep;28(3):295-310. doi: 10.3892/ijmm.2011.705. Epub 2011 May 23.

Abstract

Knowledge of the native structure of a protein could provide an understanding of the molecular basis of its function. However, in the postgenomics era, there is a growing gap between proteins with experimentally determined structures and proteins without known structures. To deal with the overwhelming data, a collection of automated methods as bioinformatics tools which determine the structure of a protein from its amino acid sequence have emerged. The aim of this paper is to provide the experimental biologists with a set of cutting-edge, carefully evaluated, user-friendly computational tools for protein structure prediction that would be helpful for the interpretation of their results and the rational design of new experiments.

摘要

对蛋白质天然结构的了解可以为其功能的分子基础提供帮助。然而,在后基因组时代,具有实验确定结构的蛋白质和没有已知结构的蛋白质之间的差距越来越大。为了处理压倒性的数据,已经出现了一系列自动方法作为生物信息学工具,这些工具可以根据蛋白质的氨基酸序列来确定其结构。本文的目的是为实验生物学家提供一组最新的、经过精心评估的、用户友好的蛋白质结构预测计算工具,这将有助于他们解释实验结果和合理设计新的实验。

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