原子分子动力学模拟揭示克氏锥虫醛酮还原酶的超分子组装。

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Pablo Trujillo, Patricia Garavaglia, Guadalupe Alvarez, Sebastian Aduviri, Carmen Domene, Joaquín Cannata, Eliana K. Asciutto, Gabriela A. García, Mónica Pickholz
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引用次数: 0

摘要

背景:目前,南美锥虫病是影响全球 800 多万人的重要公共卫生问题。这种疾病的病媒是克鲁斯锥虫(Tc)寄生虫。我们的研究重点是该寄生虫中的醛酮还原酶(TcAKR)的结构和聚集状态。TcAKR 属于醛酮还原酶(AKR)超家族,这种酶能催化氧化还原反应,参与重要的生物过程。虽然大多数 AKR 以单体形式存在,但也有一些 AKR 形成二聚体和四聚体结构的报道。一些 TcAKR 就属于这种情况。为了更好地了解 TcAKR 多聚体如何形成并保持稳定,我们利用分子动力学(MD)模拟进行了全面的计算分析。我们阐明 TcAKR 聚集状态的方法包括两种策略。首先,我们探索了预组装 TcAKR 二聚体的动态行为。随后,我们研究了八种单体的自我聚集。这项研究发现了有助于稳定蛋白质之间相互作用的关键残基。研究还发现,TcAKR 可以形成稳定的超分子组装,每个单体通常被三个第一相邻单体包围。这些发现与四聚体或更复杂的超分子结构的实验报告一致。我们的计算研究可以指导以药物开发为目标的进一步实验研究,并有助于设计调节聚集的策略:方法:我们进行了原子分子动力学模拟。TcAKR的三维模型结构是利用TcAKR序列的瑞士模型(GenBank登录号:EU558869)通过同源建模获得的。此外,我们还用 Alphafold2 对模型进行了检查,发现模型之间具有高度相似性。我们使用了多种工具来构建二聚体,包括 CLUSPRO、GRAMM-Docking、Hdock 和 Py-dock。使用 PACKMOL 软件包构建了蛋白质超结构。CHARMM-GUI 用于设置模拟系统。使用 GROMACS 2020.5 版对蛋白质和离子的 CHARMM36 力场以及水的 TIP3P 模型进行模拟。使用 VMD、GROMACS、AMBER 工具、MDLovoFit、bio3d 和内部程序进行了进一步分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Insight from atomistic molecular dynamics simulations into the supramolecular assembly of the aldo-keto reductase from Trypanosoma cruzi

Context

Currently, Chagas disease represents an important public health problem affecting more than 8 million people worldwide. The vector of this disease is the Trypanosoma cruzi (Tc) parasite. Our research specifically focuses on the structure and aggregation states of the enzyme aldo-keto reductase of Tc (TcAKR) reported in this parasite. TcAKR belongs to the aldo-keto reductase (AKR) superfamily, enzymes that catalyze redox reactions involved in crucial biological processes. While most AKRs are found in monomeric forms, some have been reported to form dimeric and tetrameric structures. This is the case for some TcAKR. To better understand how TcAKR multimers form and remain stable, we conducted a comprehensive computational analysis using molecular dynamics (MD) simulations. Our approach to elucidating the aggregation states of TcAKR involved two strategies. Initially, we explored the dynamic behaviour of pre-assembled TcAKR dimers. Subsequently, we examined the self-aggregation of eight monomers. This investigation led to the identification of crucial residues that contribute to the stabilization of protein-protein interactions. It was also found that TcAKRs can form stable supramolecular assemblies, with each monomer typically surrounded by three first neighbours. These findings align with experimental reports of tetrameric or more complex supramolecular structures. Our computational studies could guide further experimental investigations aiming at drug development and assist in designing strategies to modulate aggregation.

Method

Atomistic molecular dynamics simulations were carried out. The TcAKR 3D model structure was obtained by homology modelling using the Swiss Model for the TcAKR sequence (GenBank accession no. EU558869). Further, we checked the model with Alphafold2 and found a high degree of similarity between models. Several tools were used to build the dimers including CLUSPRO, GRAMM-Docking, Hdock, and Py-dock. Protein superstructures were built using the PACKMOL package. CHARMM-GUI was used to set up the simulation systems. GROMACS version 2020.5 was used to perform the simulations with the CHARMM36 force field for the protein and ions and the TIP3P model for water. Further analyses were performed using VMD, GROMACS, AMBER tools, MDLovoFit, bio3d, and in-house programs.

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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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