PUBLICATION
Decrypting Strong and Weak Single-Walled Carbon Nanotubes Interactions with Mitochondrial Voltage-Dependent Anion Channels Using Molecular Docking and Perturbation Theory
- Authors
- González-Durruthy, M., Werhli, A.V., Seus, V., Machado, K.S., Pazos, A., Munteanu, C.R., González-Díaz, H., Monserrat, J.M.
- ID
- ZDB-PUB-171019-19
- Date
- 2017
- Source
- Scientific Reports 7: 13271 (Journal)
- Registered Authors
- Keywords
- none
- MeSH Terms
-
- Humans
- Mitochondria/chemistry
- Mitochondria/metabolism
- Molecular Docking Simulation
- Nanotubes, Carbon/chemistry*
- Voltage-Dependent Anion Channel 1/chemistry
- Voltage-Dependent Anion Channel 1/metabolism
- Voltage-Dependent Anion Channel 2/chemistry
- Voltage-Dependent Anion Channel 2/metabolism
- Voltage-Dependent Anion Channels/chemistry
- Voltage-Dependent Anion Channels/metabolism
- PubMed
- 29038520 Full text @ Sci. Rep.
Citation
González-Durruthy, M., Werhli, A.V., Seus, V., Machado, K.S., Pazos, A., Munteanu, C.R., González-Díaz, H., Monserrat, J.M. (2017) Decrypting Strong and Weak Single-Walled Carbon Nanotubes Interactions with Mitochondrial Voltage-Dependent Anion Channels Using Molecular Docking and Perturbation Theory. Scientific Reports. 7:13271.
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 > r2 > 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 (R2 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 .
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping