Department of Applied Physics, Stanford University, Stanford, CA 94305, USA.
Proc Natl Acad Sci U S A. 2012 Feb 21;109(8):2890-5. doi: 10.1073/pnas.1119918109. Epub 2012 Jan 23.
We develop a unique algorithm implemented in the program MOSAICS (Methodologies for Optimization and Sampling in Computational Studies) that is capable of nanoscale modeling without compromising the resolution of interest. This is achieved by modeling with customizable hierarchical degrees of freedom, thereby circumventing major limitations of conventional molecular modeling. With the emergence of RNA-based nanotechnology, large RNAs in all-atom representation are used here to benchmark our algorithm. Our method locates all favorable structural states of a model RNA of significant complexity while improving sampling accuracy and increasing speed many fold over existing all-atom RNA modeling methods. We also modeled the effects of sequence mutations on the structural building blocks of tRNA-based nanotechnology. With its flexibility in choosing arbitrary degrees of freedom as well as in allowing different all-atom energy functions, MOSAICS is an ideal tool to model and design biomolecules of the nanoscale.
我们开发了一种独特的算法，该算法在 MOSAICS 程序中实现，能够在不影响关注分辨率的情况下进行纳米级建模。这是通过使用可定制的层次自由度进行建模来实现的，从而规避了传统分子建模的主要限制。随着基于 RNA 的纳米技术的出现，这里使用全原子表示的大型 RNA 来对我们的算法进行基准测试。我们的方法定位了具有显著复杂性的模型 RNA 的所有有利结构状态，同时提高了采样准确性，并使速度比现有的全原子 RNA 建模方法提高了许多倍。我们还对基于 tRNA 的纳米技术的结构构建块的序列突变的影响进行了建模。MOSAICS 具有选择任意自由度以及允许不同全原子能量函数的灵活性，是对纳米级生物分子进行建模和设计的理想工具。
