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

IF 16.6 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Nucleic Acids Research Pub Date : 2024-09-09 DOI:10.1093/nar/gkae602
Bernhard C Thiel, Giovanni Bussi, Simón Poblete, Ivo L Hofacker
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引用次数: 0

Abstract

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.

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利用 Ernwin、SPQR 和实验 SAXS 数据采样全局和局部正确的 RNA 3D 结构。
确定溶液中大型 RNA 大分子的三维结构是一项具有挑战性的任务,通常需要使用多种实验和计算技术。小角 X 射线散射可以让人们深入了解探测分子的某些几何特性,但必须对这些数据进行正确解释,才能生成三维模型。在这里,我们提出了一种多尺度管道,它将 SAXS 数据引入到溶液中 RNA 全局形状的建模中,并对其进行分层细化,直至在显式溶剂中达到原子精度。低分辨率螺旋模型(Ernwin)利用 SAXS 数据探索巨大的构象空间,而核苷酸级模型(SPQR)则消除冲突并分解所提出的结构,从而使结构在显式水中达到全原子表征。我们在四个不同的已知 pdb 结构(多达 159 个核苷酸)上应用了该程序,结果令人满意。此外,我们还根据保存在 SASBDB 中的 SAXS 数据预测了恶性疟原虫信号识别颗粒 ALU RNA 的全原子结构,与之前基于相同数据和其他建模方法发表的结构相比,该结构具有另一种构象,而且与 SAXS 数据的拟合效果更好。
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来源期刊
Nucleic Acids Research
Nucleic Acids Research 生物-生化与分子生物学
CiteScore
27.10
自引率
4.70%
发文量
1057
审稿时长
2 months
期刊介绍: Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.
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