Jaeger J A, Turner D H, Zuker M
Department of Chemistry, University of Rochester, NY 14627.
Proc Natl Acad Sci U S A. 1989 Oct;86(20):7706-10. doi: 10.1073/pnas.86.20.7706.
The accuracy of computer predictions of RNA secondary structure from sequence data and free energy parameters has been increased to roughly 70%. Performance is judged by comparison with structures known from phylogenetic analysis. The algorithm also generates suboptimal structures. On average, the best structure within 10% of the lowest free energy contains roughly 90% of phylogenetically known helixes. The algorithm does not include tertiary interactions or pseudoknots and employs a crude model for single-stranded regions. The only favorable interactions are base pairing and stacking of terminal unpaired nucleotides at the ends of helixes. The excellent performance is consistent with these interactions being the primary interactions determining RNA secondary structure.
利用序列数据和自由能参数进行计算机预测RNA二级结构的准确率已提高到约70%。通过与系统发育分析得出的已知结构进行比较来评判性能。该算法还能生成次优结构。平均而言,在最低自由能的10%范围内的最佳结构包含约90%的系统发育已知螺旋。该算法不包括三级相互作用或假结,并且对单链区域采用了一个粗略的模型。唯一有利的相互作用是碱基配对以及螺旋末端未配对核苷酸的堆积。这种出色的性能与这些相互作用是决定RNA二级结构的主要相互作用这一点是一致的。