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通过导向分子动力学和人工神经网络重建 ARNT PAS-B 展开途径。

Reconstruction of ARNT PAS-B Unfolding Pathways by Steered Molecular Dynamics and Artificial Neural Networks.

机构信息

Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan 20126, Italy.

Department of Computer Science, Brunel University London, Uxbridge UB8 3PH, United Kingdom.

出版信息

J Chem Theory Comput. 2021 Apr 13;17(4):2080-2089. doi: 10.1021/acs.jctc.0c01308. Epub 2021 Mar 29.

Abstract

Several experimental studies indicated that large conformational changes, including partial domain unfolding, have a role in the functional mechanisms of the basic helix loop helix Per/ARNT/SIM (bHLH-PAS) transcription factors. Recently, single-molecule atomic force microscopy (AFM) revealed two distinct pathways for the mechanical unfolding of the ARNT PAS-B. In this work we used steered molecular dynamics simulations to gain new insights into this process at an atomistic level. To reconstruct and classify pathways sampled in multiple simulations, we designed an original approach based on the use of self-organizing maps (SOMs). This led us to identify two types of unfolding pathways for the ARNT PAS-B, which are in good agreement with the AFM findings. Analysis of average forces mapped on the SOM revealed a stable conformation of the PAS-B along one pathway, which represents a possible structural model for the intermediate state detected by AFM. The approach here proposed will facilitate the study of other signal transmission mechanisms involving the folding/unfolding of PAS domains.

摘要

几项实验研究表明,包括部分结构域展开在内的较大构象变化在基本螺旋-环-螺旋 PER/ARNT/SIM(bHLH-PAS)转录因子的功能机制中起作用。最近,单分子原子力显微镜(AFM)揭示了 ARNT PAS-B 的机械展开的两种不同途径。在这项工作中,我们使用受控分子动力学模拟在原子水平上对此过程进行了深入了解。为了重构和分类多次模拟中采样的途径,我们设计了一种基于自组织映射(SOM)的原始方法。这使我们能够识别出 ARNT PAS-B 的两种展开途径,这与 AFM 的发现非常吻合。对 SOM 上映射的平均力的分析揭示了沿一条途径 PAS-B 的稳定构象,这代表了 AFM 检测到的中间状态的可能结构模型。这里提出的方法将促进涉及 PAS 结构域折叠/展开的其他信号转导机制的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17da/8047803/b2f198235c5a/ct0c01308_0001.jpg

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