Predicting the binding properties of single walled carbon nanotubes (SWCNT) with an ADP/ATP mitochondrial carrier using molecular docking, chemoinformatics, and nano-QSBR perturbation theory

Abstract

Interactions between single walled carbon nanotubes (SWCNT) family with mitochondrial ADP/ATP carrier (ANT-1) were evaluated using constitutional (functional groups, number of carbon atoms, etc.) and electronic nanodescriptors defined by (n, m)-Hamada indexes (armchair, zig-zag and chiral). The Free Energy of Binding (FEB) was determined by Molecular Docking Simulation and the results showed that FEB was statistically more negative (p< 0.05), following the order SWCNT-COOH > SWCNT-OH > SWCNT, suggesting that polar groups favor the anchorage to ANT-1. In this regard, it was showed that key ANT-1 amino acids (Arg 79, Asn 87, Lys 91, Arg 187, Arg 234 and Arg 279) responsible for ADP-transport were conserved in ANT-1 from different species examined to predict SWCNT interactions, including shrimp Litopenaeus vannamei and fish Danio rerio commonly employed in ecotoxicology. The SWCNT-ANT-1 inter-atomic distances for the key ANT-1 amino acids were similar to that with carboxyatractyloside, a classical inhibitor of ANT-1.Significant linear relationships between FEB and n-Hamada index were found for zig-zag SWCNT and SWCNT-COOH (R 2 = 0.95 in both cases). A Perturbation Theory-Nano-Quantitative Structure-Binding Relationship (PT-NQSBR) model was fitted that was able to distinguish between strong (FEB < -14.7 kcal/mol) from weak (FEB ≥ -14.7 kcal/mol) SWCNT-ANT-1 interactions. A simple ANT-1-inhibition respiratory assays employing mitochondria suspension from L. vannamei, showed good accordance with the prediction model. These results indicate that this methodology can be employed in massive virtual screenings and used for making regulatory decisions in Nanotoxicology.

Engineered nanomaterials: From their properties and applications, to their toxicity towards marine bivalves in a changing environment

“…In the near future, toxicity assays should optimize, as stated byBondarenko et al (2016), duration and complexity of the tests, its sensitivty, standardisation status and the required traning. Also, complementary in silico strategies should be incorporated to perform quick virtual screening of several nanomaterials before the execution of toxicological tests(González-Durruthy et al, 2016). Finally, the efforts and initiatives for the standardization of nanotoxicological assays (i.e: NanoReg, NANOVALID) are the paramount importance, particulary in present days where the reproducibility crisis in science is being debated(Fanelli, 2018;França & Monserrat, 2018) national funds (OE), through FCT -Fundação para a Ciência e a Tecnologia, I.P., in the scope of the framework contract foreseen in the numbers 4, 5 and 6 of the article 23, of the Decree-Law 57/2016, of August 29, changed by Law 57/2017, of July 19.…”

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

“…Then, these potential biochemical events could explain the difference observed for FEB-values (of SWCNT-VDAC complexes formed) and could still be viewed as a friend or a foe depending on the toxicological condition considered 57 like the presence of zigzag SWCNT topologies with high n Hamada index. Besides, a recognized phenomenon of “edge effects”, which only appears in semiconducting zigzag SWCNT topologies, plays an important role in the mitochondrial channel nanotoxicity of zigzag SWCNTs 18 . The “edge effects” were not observed for metallic-armchair SWCNT, wherein the cycloparaphenylene aromatic system of the SWCNT-extremes were closed and without tips charge variation 18 , 58 .…”

“…In the particular case of Nanoparticles we can talk about Nano-QSAR (NQSAR) or Nano-QSBR (NQSBR) models, by analogy. In general, these NQSAR/NQSBR models use as input physico-chemical properties of nanoparticles (nanodescriptors) to predict their biological activity, toxicity, and/or target-binding affinity 18 – 29 . The main assumption of classic QSAR algorithms in general form is that the similar structures (ligands) have similar properties.…”

“…This first parameter represents a known value of biological property used as reference value (or an expected value of this endpoint). After that, the PT-NQSAR model add small corrections (functions of nanodescriptors for one specific case) to predict a solution to a related problem 18 , 30 – 32 . In principle, there is a large variety of data analysis techniques that have proven to be effective in QSAR/QSBR modeling in general (including NQSAR and PT-NQSAR models).…”

“…Last, we should note that, NQSAR/NQSBR algorithms should have the ability of feature selection (FS) to exclude redundant nanodescriptors before NQSAR model building 39 , 40 . Specifically, ( n , m ) - Hamada indices (related to SWCNT-chiral topology and SWCNT-diameter) may become interesting candidates to input variables in NQSAR/NQSBR studies 18 . The electro-topological and constitutional SWCNT nanodescriptors for pristine SWCNT and oxidized SWCNT (SWCNT-OH, SWCNT-COOH), based on the information of SWCNT-periodic properties 41 – 45 , have not yet been considered from the perspective of NQSAR with respect to their relevant interactions with mitochondrial channels, such as voltage-dependent anion channel (VDAC).…”