Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
Department of Cell Biology, Harvard Medical School, Boston, MA, USA.
Bioinformatics. 2019 May 1;35(9):1582-1584. doi: 10.1093/bioinformatics/bty862.
Coevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. We present the EVcouplings framework, a fully integrated open-source application and Python package for coevolutionary analysis. The framework enables generation of sequence alignments, calculation and evaluation of evolutionary couplings (ECs), and de novo prediction of structure and mutation effects. The combination of an easy to use, flexible command line interface and an underlying modular Python package makes the full power of coevolutionary analyses available to entry-level and advanced users.
共进化序列分析已成为从头预测蛋白质、RNA 和蛋白质复合物结构与功能的常用技术。我们介绍了 EVcouplings 框架,这是一个完全集成的开源应用程序和 Python 包,用于共进化分析。该框架能够生成序列比对、计算和评估进化耦合(EC),以及从头预测结构和突变效应。易于使用、灵活的命令行界面与底层模块化 Python 包的结合,使共进化分析的全部功能可供入门级和高级用户使用。