Journal of Chemical Information and Modeling | VOL. 62
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Predicted Adsorption Affinity for Enteric Microbial Metabolites to Metal and Carbon Nanomaterials

Publication Date Jul 25, 2022

Abstract

Ingested nanomaterials are exposed to many metabolites that are produced, modified, or regulated by members of the enteric microbiota. The adsorption of these metabolites potentially affects the identity, fate, and biodistribution of nanomaterials passing the gastrointestinal tract. Here, we explore these interactions using in silico methods, focusing on a concise overview of 170 unique enteric microbial metabolites which we compiled from the literature. First, we construct quantitative structure-activity relationship (QSAR) models to predict their adsorption affinity to 13 metal nanomaterials, 5 carbon nanotubes, and 1 fullerene. The models could be applied to predict log k values for 60 metabolites and were particularly applicable to 'phenolic, benzoyl and phenyl derivatives', 'tryptophan precursors and metabolites', 'short-chain fatty acids', and 'choline metabolites'. The correlations of these predictions to biological surface adsorption index descriptors indicated that hydrophobicity-driven interactions contribute most to the overall adsorption affinity, while hydrogen-bond interactions and polarity/polarizability-driven interactions differentiate the affinity to metal and carbon nanomaterials. Next, we use molecular dynamics (MD) simulations to obtain direct molecular information for a selection of vitamins that could not be assessed quantitatively using QSAR models. This showed how large and flexible metabolites can gain stability on the nanomaterial surface via conformational changes. Additionally, unconstrained MD s...

Concepts

Quantitative Structure-activity Relationship Models Metal Nanomaterials Choline Metabolites Carbon Nanomaterials Short-chain Fatty Acids Tryptophan Precursors Phenyl Derivatives Quantitative Structure-activity Relationship Adsorption Affinity Quantitative Structure-activity Relationship Analysis

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