Drory Retwitzer Matan, Reinharz Vladimir, Ponty Yann, Waldispühl Jérôme, Barash Danny
Department of Computer Science, Ben-Gurion University, Beer-Sheva 84105, Israel.
School of Computer Science & McGill Centre for Bioinformatics, McGill University, Montréal, QC H3A 0E9, Canada.
Nucleic Acids Res. 2016 Jul 8;44(W1):W308-14. doi: 10.1093/nar/gkw440. Epub 2016 May 16.
In recent years, new methods for computational RNA design have been developed and applied to various problems in synthetic biology and nanotechnology. Lately, there is considerable interest in incorporating essential biological information when solving the inverse RNA folding problem. Correspondingly, RNAfbinv aims at including biologically meaningful constraints and is the only program to-date that performs a fragment-based design of RNA sequences. In doing so it allows the design of sequences that do not necessarily exactly fold into the target, as long as the overall coarse-grained tree graph shape is preserved. Augmented by the weighted sampling algorithm of incaRNAtion, our web server called incaRNAfbinv implements the method devised in RNAfbinv and offers an interactive environment for the inverse folding of RNA using a fragment-based design approach. It takes as input: a target RNA secondary structure; optional sequence and motif constraints; optional target minimum free energy, neutrality and GC content. In addition to the design of synthetic regulatory sequences, it can be used as a pre-processing step for the detection of novel natural occurring RNAs. The two complementary methodologies RNAfbinv and incaRNAtion are merged together and fully implemented in our web server incaRNAfbinv, available at http://www.cs.bgu.ac.il/incaRNAfbinv.
近年来,已开发出计算RNA设计的新方法,并将其应用于合成生物学和纳米技术的各种问题。最近,在解决RNA反向折叠问题时,人们对纳入基本生物学信息产生了浓厚兴趣。相应地,RNAfbinv旨在纳入具有生物学意义的约束条件,并且是迄今为止唯一执行基于片段的RNA序列设计的程序。这样一来,只要保留整体粗粒度树形图形状,它就允许设计不一定能精确折叠成目标的序列。通过incaRNAtion的加权采样算法进行增强,我们名为incaRNAfbinv的网络服务器实现了RNAfbinv中设计的方法,并提供了一个使用基于片段的设计方法进行RNA反向折叠的交互式环境。它将以下内容作为输入:目标RNA二级结构;可选的序列和基序约束;可选的目标最小自由能、中性和GC含量。除了设计合成调控序列外,它还可以用作检测新型天然RNA的预处理步骤。两种互补方法RNAfbinv和incaRNAtion合并在一起,并在我们的网络服务器incaRNAfbinv中完全实现,可在http://www.cs.bgu.ac.il/incaRNAfbinv上获取。