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

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.

Theoretical study on binding interactions of laccase-enzyme from Ganoderma weberianum with multiples ligand substrates with environmental impact

“…It does not have a remarkable weight on the FEB dock the Ligand-total dimensionality (total DOF = 3 + 4 + n) due to the very small intra-molecular contributions of force ield parameters of the laccase-ligand. These are considered as rigid and taking account the ligand-geometry optimization (described above) [43] based on the ΔG internal minimization of all the laccaseligands used in the present study.…”

Interactions of nanomaterials with ion channels and related mechanisms

“…Studies focused on NM-induced biological effects on K + and Na + channels are summarized in Table 1. (Chhowalla et al, 2005;Gonzalez-Durruthy et al, 2017;Park et al, 2003) of ion channels in many directions by (A) directly blocking the channel pore from extracellular sites, (B) binding to hydrophobic residues in extracellular and intracellular sites or (C) penetrating into the lipid bilayer of the cell membrane, and (D) causing the rotation of functional areas, such as voltage sensor domains (VSDs). The structure and function of ion channels are affected by these interactions (Gu et al, 2018), leading to partial or complete block of current (Calvaresi, Furini, Domene, Bottoni, & Zerbetto, 2015;Kraszewski, Tarek, Treptow, & Ramseyer, 2010).…”

“…Chloride channels have many important physiological roles, including pH regulation, volume homeostasis, organic solute transport, cell migration, cell proliferation, and cell differentiation (Jentsch, Stein, Weinreich, & Zdebik, 2002). However, only a few studies have shown that exposure to NMs could affect the function of Cl − channels (Ahmad et al, 2012;Gonzalez-Durruthy et al, 2017). A molecular docking simulation suggested that three types of single-walled carbon nanotubes (SWCNTs) can block the mitochondrial voltage-dependent anion channel (Gonzalez-Durruthy et al, 2017).…”

“…However, only a few studies have shown that exposure to NMs could affect the function of Cl − channels (Ahmad et al, 2012;Gonzalez-Durruthy et al, 2017). A molecular docking simulation suggested that three types of single-walled carbon nanotubes (SWCNTs) can block the mitochondrial voltage-dependent anion channel (Gonzalez-Durruthy et al, 2017). Mustafa and Komatsu (2016) ZnO NPs, the conductance of the lysenin channel was substantially reduced.…”

Prediction of Antimalarial Drug-Decorated Nanoparticle Delivery Systems with Random Forest Models

“…Moreover, a brand new method for data fusion in nanotechnology, bio-molecular sciences, chemistry and big data analysis has been proposed in different works: it integrates Perturbation Theory (PT) and Machine Learning (ML) [ 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 ], using distinct PT operators to analyze changes in the varied non-structural and structural conditions of a test at once (PTML). A few of these PT operators represent the generalization of a classic cheminformatics approach introduced by Corwin Hansch [ 14 ].…”