2017年5月8日, 國際核酸類重要學術期刊《Nucleic Acids Research》雜誌線上發表了華中科技大學物理學院生物物理研究所肖奕教授團隊題為《通過直接耦合分析的核苷酸共進化資訊對RNA三級結構進行優化》(Optimization of RNA 3D structure prediction usingevolutionary restraints of nucleotide-nucleotide interactions from direct coupling analysis)的論文, 報導了一種利用共進化資訊提高非編碼核糖核酸(RNA)三維結構預測精度的方法。 物理學院博士生王劍為論文第一作者, 肖奕教授為論文通訊作者。
一般而言, 傳統研究表明機體的各種生命活動主要依靠蛋白質來完成, 但近些年來科學界發現越來越多的RNA也同樣參與這些過程, 並且其內在機理和許多重大疾病息息相關。
原文連結:
原文摘要:
Direct coupling analysis of nucleotide coevolution provides a novel approach to identify which nucleotides in an RNA molecule are likely in direct contact, and this information obtained from sequence only can be used to predict RNA 3D structures with much improved accuracy. Here we present an efficient method that incorporates this information into current RNA 3D structure prediction methods, specifically 3dRNA. Our method makes much more accurate RNA 3D structure prediction than the original 3dRNA as well as other existing prediction methods that used the direct coupling analysis. In particular our method demonstrates a significant improvement in predicting multi-branch junction conformations, a major bottleneck for RNA 3D structure prediction. We also show that our method can be used to optimize the predictions by other methods. These results indicate that optimization of RNA 3D structure prediction using evolutionary restraints of nucleotide–nucleotide interactions from direct coupling analysis offers an efficient way for accurate RNA tertiary structure predictions.
作者:肖奕 點擊:次