Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Department of Molecular Genetics, University of Toronto.
Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Department of Computer Science, University of Toronto, Toronto, ON, Canada and.
Bioinformatics. 2016 May 15;32(10):1589-91. doi: 10.1093/bioinformatics/btw031. Epub 2016 Jan 21.
ELASPIC is a novel ensemble machine-learning approach that predicts the effects of mutations on protein folding and protein-protein interactions. Here, we present the ELASPIC webserver, which makes the ELASPIC pipeline available through a fast and intuitive interface. The webserver can be used to evaluate the effect of mutations on any protein in the Uniprot database, and allows all predicted results, including modeled wild-type and mutated structures, to be managed and viewed online and downloaded if needed. It is backed by a database which contains improved structural domain definitions, and a list of curated domain-domain interactions for all known proteins, as well as homology models of domains and domain-domain interactions for the human proteome. Homology models for proteins of other organisms are calculated on the fly, and mutations are evaluated within minutes once the homology model is available.
The ELASPIC webserver is available online at http://elaspic.kimlab.org
pm.kim@utoronto.ca or pi@kimlab.orgSupplementary data: Supplementary data are available at Bioinformatics online.
ELASPIC 是一种新颖的集成机器学习方法，可预测突变对蛋白质折叠和蛋白质-蛋白质相互作用的影响。 在这里，我们介绍了 ELASPIC 网络服务器，该服务器通过快速直观的界面提供了 ELASPIC 管道。 该网络服务器可用于评估 Uniprot 数据库中任何蛋白质的突变影响，并允许管理和在线查看所有预测结果，包括建模的野生型和突变型结构，如果需要，还可以下载。 它由一个数据库支持，该数据库包含改进的结构域定义，以及所有已知蛋白质的经过策展的域-域相互作用列表，以及人类蛋白质组的域和域-域相互作用的同源模型。 对于其他生物体的蛋白质的同源模型是实时计算的，并且一旦可用同源模型，突变将在几分钟内进行评估。
ELASPIC 网络服务器可在线获得，网址为 http://elaspic.kimlab.org。
pm.kim@utoronto.ca 或 pi@kimlab.org
补充数据可在“Bioinformatics”在线获得。
