Scientific Reports · 2017 · 31 citations · 46 references
Natural SciencesBiochemistryBiophysicsBiophysical ChemistryIon Channel BiophysicsMitochondrial BiologyBiomolecular InteractionsIntermolecular ForcesIon Channel EnergeticsMitochondrial PhysiologyMolecular DockingNanotubesElectrostatic Contributions To Binding Free EnergyEnergy-based DockingFree Energy BarriersFree Energy ChangesMitochondrial Membrane Transport ChannelsMolecular Perturbation TheorySingle-walled Carbon NanotubesVoltage-dependent Anion Channel
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 2 > 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 2 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 .
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Helen M. Berman · Nucleic Acids Research · 2000 · 39.8K citations
Neural networks for pattern recognition
Choice Reviews Online · 1994 · 18.7K citations