Computer-aided design of carbon nanotubes with the desired bioactivity and safety profiles

Abstract

Growing experimental evidences suggest the existence of direct relationships between the surface chemistry of nanomaterials and their biological effects. Herein, we have employed computational approaches to design a set of biologically active Carbon Nanotubes (CNTs) with controlled protein binding and cytotoxicity. Quantitative Structure-Activity Relationships (QSAR) models were built and validated using a dataset of 83 surface-modified CNTs. A subset of a combinatorial virtual library of 240,000 ligands potentially attachable to CNTs was selected to include molecules that were within the chemical similarity threshold with respect to the modeling set compounds. QSAR models were then employed to virtually screen this subset and prioritize CNTs for chemical synthesis and biological evaluation. Ten putatively active and ten putatively inactive CNTs decorated with the ligands prioritized by virtual screening for either protein binding or cytotoxicity assays were synthesized and tested. We found that all 10 putatively inactive and 7 out of 10 putatively active CNTs were confirmed in the protein binding assay, whereas all 10 putatively inactive and 6 out of 10 putatively active CNTs were confirmed in the cytotoxicity assay. This proof-of-concept study shows that computational models can be employed to guide the design of surface-modified nanomaterials with the desired biological and safety profiles.

Toward a systematic exploration of nano-bio interactions

“…2b) (Zhang et al, 2016) in systematic ways. QSAR analysis of the cytotoxicity data generated a computational prediction model that facilitated nanotube design (Fourches et al, 2015). A nano-combinatorial gold nanoparticle library aids discovery of cell-specific and high affinity binding nanoparticles that can distinguish between related cell types, so have potential applications in diagnostics and personalized medicine (Zhou et al, 2010; Le et al, 2015).…”

“…This parameter is highly correlated with the ionization potential of the oxidation state of the metal and thus to redox properties (Le et al, 2016b). Fourches et al studied various nanoparticles (Fourches et al, 2010; Fourches et al, 2011) and reported the first experimentally validated computer prediction (Fourches et al, 2015). A recent study by Liu et al developed a QSAR model based on the atomization energy of the metal oxide, period of the nanoparticle metal, and nanoparticle primary size (Liu et al, 2011).…”

“…Recent published work has highlighted the potential for machine learning models to facilitate purposeful design of nanomaterials with bespoke properties, particularly for medical applications or to minimize adverse biological effects. (Fourches et al, 2015; Le et al, 2015; Li et al, 2015; Liu et al, 2015b; Zhang et al, 2016). Fourches et al, for example, used a computational model to virtually screen external libraries and design new carbon nanotubes with favoured properties.…”

“…Fourches et al, for example, used a computational model to virtually screen external libraries and design new carbon nanotubes with favoured properties. Subsequent experimental validation showed the usefulness of the resulting model in predicting the properties of new nanomaterials (Fourches et al, 2015). With these initial successes and proof of concept, it is expected that nano informatics models will make an increasingly strong contribution to the design and regulation of nanomaterials within this decade (Winkler et al, 2013).…”

Elucidation of the Molecular Determinants for Optimal Perfluorooctanesulfonate Adsorption Using a Combinatorial Nanoparticle Library Approach

“…40 In this work, we established a combinatorial nanoparticle library approach to reveal major molecular interaction components for pollutant adsorption using PFOS as an example. We determined that the optimal molecular adsorption of PFOS by functionalized gold nanoparticles (GNPs) requires simultaneous electrostatic and fluorine–fluorine (F–F) interactions.…”