Adsorption in Action: Molecular Dynamics as a Tool to Study Adsorption at the Surface of Fine Plastic Particles in Aquatic Environments.

The presence of microscopic fine plastic particles (FPPs) in aquatic environments continues to be a societal issue of great concern. Further, the adsorption of pollutants and other macromolecules onto the surface of FPPs is a well-known phenomenon. To establish the adsorption behavior of pollutants and the adsorption capacity of different plastic materials, batch adsorption experiments are typically carried out, wherein known concentrations of a pollutant are added to a known amount of plastic.

Photochemical Fingerprinting Is a Sensitive Probe for the Detection of Synthetic Cannabinoid Receptor Agonists; toward Robust Point-of-Care Detection.

With synthetic cannabinoid receptor agonist (SCRA) use still prevalent across Europe and structurally advanced generations emerging, it is imperative that drug detection methods advance in parallel. SCRAs are a chemically diverse and evolving group, which makes rapid detection challenging. We have previously shown that fluorescence spectral fingerprinting (FSF) has the potential to provide rapid assessment of SCRA presence directly from street material with minimal processing and in saliva.

Eliminating Transition State Calculations for Faster and More Accurate Reactivity Prediction in Sulfa-Michael Additions Relevant to Human Health and the Environment.

Fast and accurate computational approaches to predicting reactivity in sulfa-Michael additions are required for high-throughput screening in toxicology (e.g., predicting excess aquatic toxicity and skin sensitization), chemical synthesis, covalent drug design (e.

Comparing the Performances of Force Fields in Conformational Searching of Hydrogen-Bond-Donating Catalysts.

Here, we compare the relative performances of different force fields for conformational searching of hydrogen-bond-donating catalyst-like molecules. We assess the force fields by their predictions of conformer energies, geometries, low-energy, nonredundant conformers, and the maximum numbers of possible conformers. Overall, MM3, MMFFs, and OPLS3e had consistently strong performances and are recommended for conformationally searching molecules structurally similar to those in this study.

Reactivity prediction in aza-Michael additions without transition state calculations: the Ames test for mutagenicity.

Animal testing remains a contentious ethical issue in predictive toxicology. Thus, a fast, versatile, low-cost quantum chemical model is presented for predicting the risk of Ames mutagenicity in a series of 1,4 Michael acceptor type compounds. This framework eliminates the need for transition state calculations, and uses an intermediate structure to probe the reactivity of aza-Michael acceptors.

Density Functional Theory in the Prediction of Mutagenicity: A Perspective.

As a field, computational toxicology is concerned with using models to predict and understand the origins of toxicity. It is fast, relatively inexpensive, and avoids the ethical conundrum of using animals in scientific experimentation. In this perspective, we discuss the importance of computational models in toxicology, with a specific focus on the different model types that can be used in predictive toxicological approaches toward mutagenicity (SARs and QSARs).

Density Functional Theory Transition-State Modeling for the Prediction of Ames Mutagenicity in 1,4 Michael Acceptors.

Assessing the safety of new chemicals, without introducing the need for animal testing, is a task of great importance. The Ames test, a widely used bioassay to assess mutagenicity, can be an expensive, wasteful process with animal-derived reagents. Existing in silico methods for the prediction of Ames test results are traditionally based on chemical category formation and can lead to false positive predictions.