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使用分子对接和微扰理论对与线粒体电压依赖性阴离子通道相互作用的强和弱单壁碳纳米管进行解密。

Decrypting Strong and Weak Single-Walled Carbon Nanotubes Interactions with Mitochondrial Voltage-Dependent Anion Channels Using Molecular Docking and Perturbation Theory.

机构信息

Institute of Biological Sciences (ICB)- Federal University of Rio Grande - FURG, Postgraduate Program in Physiological Sciences, Cx. P. 474, CEP 96200-970, Rio Grande, RS, Brazil.

Center of Computational Sciences (C3)- Federal University of Rio Grande - FURG, Cx. P. 474, CEP 96200-970, Rio Grande, RS, Brazil.

出版信息

Sci Rep. 2017 Oct 16;7(1):13271. doi: 10.1038/s41598-017-13691-8.

DOI:10.1038/s41598-017-13691-8
PMID:29038520
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5643473/
Abstract

The current molecular docking study provided the Free Energy of Binding (FEB) for the interaction (nanotoxicity) between VDAC mitochondrial channels of three species (VDAC1-Mus musculus, VDAC1-Homo sapiens, VDAC2-Danio rerio) with SWCNT-H, SWCNT-OH, SWCNT-COOH carbon nanotubes. The general results showed that the FEB values were statistically more negative (p < 0.05) in the following order: (SWCNT-VDAC2-Danio rerio) > (SWCNT-VDAC1-Mus musculus) > (SWCNT-VDAC1-Homo sapiens) > (ATP-VDAC). More negative FEB values for SWCNT-COOH and OH were found in VDAC2-Danio rerio when compared with VDAC1-Mus musculus and VDAC1-Homo sapiens (p < 0.05). In addition, a significant correlation (0.66 > r > 0.97) was observed between n-Hamada index and VDAC nanotoxicity (or FEB) for the zigzag topologies of SWCNT-COOH and SWCNT-OH. Predictive Nanoparticles-Quantitative-Structure Binding-Relationship models (nano-QSBR) for strong and weak SWCNT-VDAC docking interactions were performed using Perturbation Theory, regression and classification models. Thus, 405 SWCNT-VDAC interactions were predicted using a nano-PT-QSBR classifications model with high accuracy, specificity, and sensitivity (73-98%) in training and validation series, and a maximum AUROC value of 0.978. In addition, the best regression model was obtained with Random Forest (R of 0.833, RMSE of 0.0844), suggesting an excellent potential to predict SWCNT-VDAC channel nanotoxicity. All study data are available at https://doi.org/10.6084/m9.figshare.4802320.v2 .

摘要

目前的分子对接研究提供了三种物种（鼠 Mus musculus 的 VDAC1、人 Homo sapiens 的 VDAC1 和斑马鱼 Danio rerio 的 VDAC2）的 VDAC 线粒体通道与 SWCNT-H、SWCNT-OH 和 SWCNT-COOH 碳纳米管相互作用的结合自由能（FEB）。一般结果表明，FEB 值按以下顺序具有统计学上的更负（p < 0.05）：（SWCNT-VDAC2-Danio rerio）>（SWCNT-VDAC1-Mus musculus）>（SWCNT-VDAC1-Homo sapiens）>（ATP-VDAC）。与 VDAC1-Mus musculus 和 VDAC1-Homo sapiens 相比，在 VDAC2-Danio rerio 中发现 SWCNT-COOH 和 OH 的更负的 FEB 值（p < 0.05）。此外，在 SWCNT-COOH 和 SWCNT-OH 的锯齿拓扑中，n-Hamada 指数与 VDAC 纳米毒性（或 FEB）之间观察到显著相关性（0.66 > r > 0.97）。使用微扰理论、回归和分类模型，为强和弱 SWCNT-VDAC 对接相互作用建立了预测纳米粒子-定量结构结合关系模型（nano-QSBR）。因此，使用 nano-PT-QSBR 分类模型预测了 405 个 SWCNT-VDAC 相互作用，在训练和验证系列中具有较高的准确性、特异性和敏感性（73-98%），最大 AUROC 值为 0.978。此外，随机森林（R 为 0.833，RMSE 为 0.0844）获得了最佳回归模型，这表明对 SWCNT-VDAC 通道纳米毒性具有极好的预测潜力。所有研究数据均可在 https://doi.org/10.6084/m9.figshare.4802320.v2 获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/2cbaede84a9f/41598_2017_13691_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/58912bd2bbad/41598_2017_13691_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/85e2bd681cfe/41598_2017_13691_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/03f210832569/41598_2017_13691_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/4d0c64f5767f/41598_2017_13691_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/015cc2f0b1d8/41598_2017_13691_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/01aff3762a53/41598_2017_13691_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/35d23b705ca8/41598_2017_13691_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/2cbaede84a9f/41598_2017_13691_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/58912bd2bbad/41598_2017_13691_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/85e2bd681cfe/41598_2017_13691_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/03f210832569/41598_2017_13691_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/4d0c64f5767f/41598_2017_13691_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/015cc2f0b1d8/41598_2017_13691_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/01aff3762a53/41598_2017_13691_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/35d23b705ca8/41598_2017_13691_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b2/5643473/2cbaede84a9f/41598_2017_13691_Fig8_HTML.jpg

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