Sampling globally and locally correct RNA 3D structures using Ernwin, SPQR and experimental SAXS data

被引:4
作者
Thiel, Bernhard C. [1 ]
Bussi, Giovanni [2 ]
Poblete, Simon [3 ,4 ]
Hofacker, Ivo L. [1 ,5 ]
机构
[1] Univ Vienna, Dept Theoret Chem, Wahringer Str 17, A-1090 Vienna, Austria
[2] Scuola Int Super Studi Avanzati, Via Bonomea 265, Trieste, Italy
[3] Ctr BASAL Ciencia & Vida, Ave Valle Norte 725, Santiago 8580702, Chile
[4] Univ San Sebastian, Fac Ingn Arquitectura & Diseno, Bellavista 7, Santiago 8420524, Chile
[5] Univ Vienna, Fac Comp Sci, Res Grp Bioinformat & Computat Biol, Vienna, Austria
基金
奥地利科学基金会;
关键词
X-RAY-SCATTERING; SMALL-ANGLE SCATTERING; STRUCTURE PREDICTION; CURVES;
D O I
10.1093/nar/gkae602
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The determination of the three-dimensional structure of large RNA macromolecules in solution is a challenging task that often requires the use of several experimental and computational techniques. Small-angle X-ray scattering can provide insight into some geometrical properties of the probed molecule, but this data must be properly interpreted in order to generate a three-dimensional model. Here, we propose a multiscale pipeline which introduces SAXS data into modelling the global shape of RNA in solution, which can be hierarchically refined until reaching atomistic precision in explicit solvent. The low-resolution helix model (Ernwin) deals with the exploration of the huge conformational space making use of the SAXS data, while a nucleotide-level model (SPQR) removes clashes and disentangles the proposed structures, leading the structure to an all-atom representation in explicit water. We apply the procedure on four different known pdb structures up to 159 nucleotides with promising results. Additionally, we predict an all-atom structure for the Plasmodium falceparum signal recognition particle ALU RNA based on SAXS data deposited in the SASBDB, which has an alternate conformation and better fit to the SAXS data than the previously published structure based on the same data but other modelling methods. Graphical Abstract
引用
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页数:11
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