Mazzanti Liuba, Doutreligne Sébastien, Gageat Cedric, Derreumaux Philippe, Taly Antoine, Baaden Marc, Pasquali Samuela
Laboratoire de Biochimie Théorique, Université Paris Diderot, Sorbonne Paris Cité, Paris, France.
Département de Chimie, Ecole Normale Supérieure, PSL Research University, Université Pierre et Marie Curie, Sorbonne Paris Cité, Paris, France.
Biophys J. 2017 Jul 25;113(2):302-312. doi: 10.1016/j.bpj.2017.05.047. Epub 2017 Jun 22.
Inspired by the recent success of scientific-discovery games for predicting protein tertiary and RNA secondary structures, we have developed an open software for coarse-grained RNA folding simulations, guided by human intuition. To determine the extent to which interactive simulations can accurately predict 3D RNA structures of increasing complexity and lengths (four RNAs with 22-47 nucleotides), an interactive experiment was conducted with 141 participants who had very little knowledge of nucleic acids systems and computer simulations, and had received only a brief description of the important forces stabilizing RNA structures. Their structures and full trajectories have been analyzed statistically and compared to standard replica exchange molecular dynamics simulations. Our analyses show that participants gain easily chemical intelligence to fold simple and nontrivial topologies, with little computer time, and this result opens the door for the use of human-guided simulations to RNA folding. Our experiment shows that interactive simulations have better chances of success when the user widely explores the conformational space. Interestingly, providing on-the-fly feedback of the root mean square deviation with respect to the experimental structure did not improve the quality of the proposed models.
受近期科学发现游戏在预测蛋白质三级结构和RNA二级结构方面取得成功的启发,我们开发了一款开放软件,用于在人类直觉引导下进行粗粒度RNA折叠模拟。为了确定交互式模拟能够准确预测复杂度和长度不断增加的三维RNA结构(四个含22 - 47个核苷酸的RNA)的程度,我们对141名对核酸系统和计算机模拟了解甚少、仅接受过关于稳定RNA结构的重要作用力的简短描述的参与者进行了一项交互式实验。我们对他们构建的结构和完整轨迹进行了统计分析,并与标准的副本交换分子动力学模拟进行了比较。我们的分析表明,参与者能够轻松获得化学知识来折叠简单和非平凡的拓扑结构,且所需计算机时间很少,这一结果为将人类引导的模拟用于RNA折叠打开了大门。我们的实验表明,当用户广泛探索构象空间时,交互式模拟成功的机会更大。有趣的是,提供关于相对于实验结构的均方根偏差的即时反馈并没有提高所提出模型的质量。