Experimental Testing of Quantum Mechanical Predictions of Mutagenicity: Aminopyrazoles

Mechanism-Based Insights into Removing the Mutagenicity of Aromatic Amines by Small Structural Alterations

Aromatic and heteroaromatic amines (ArNH₂) are activated by cytochrome P450 monooxygenases, primarily CYP1A2, into reactive N-arylhydroxylamines that can lead to covalent adducts with DNA nucleobases. Hereby, we give hands-on mechanism-based guidelines to design mutagenicity-free ArNH₂. The mechanism of N-hydroxylation of ArNH₂ by CYP1A2 is investigated by density functional theory (DFT) calculations. Two putative pathways are considered, the radicaloid route that goes via the classical ferryl-oxo oxidant and an alternative anionic pathway through Fenton-like oxidation by ferriheme-bound H₂O₂. Results suggest that bioactivation of ArNH₂ follows the anionic pathway. We demonstrate that H-bonding and/or geometric fit of ArNH₂ to CYP1A2 as well as feasibility of both proton abstraction by the ferriheme-peroxo base and heterolytic cleavage of arylhydroxylamines render molecules mutagenic. Mutagenicity of ArNH₂ can be removed by structural alterations that disrupt geometric and/or electrostatic fit to CYP1A2, decrease the acidity of the NH₂ group, destabilize arylnitrenium ions, or disrupt their pre-covalent transition states with guanine.

Density Functional Theory in the Prediction of Mutagenicity: A Perspective

As a field, computational toxicology is concerned with using in silico 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). We then focus on how quantum chemical methods, such as density functional theory (DFT), have previously been used in the prediction of mutagenicity. It is then discussed how DFT allows for the development of new chemical descriptors that focus on capturing the steric and energetic effects that influence toxicological reactions. We hope to demonstrate the role that DFT plays in understanding the fundamental, intrinsic chemistry of toxicological reactions in predictive toxicology.

Using Transition State Modeling To Predict Mutagenicity for Michael Acceptors

The Ames mutagenicity assay is a long established in vitro test to measure the mutagenicity potential of a new chemical used in regulatory testing globally. One of the key computational approaches to modeling of the Ames assay relies on the formation of chemical categories based on the different electrophilic compounds that are able to react directly with DNA and form a covalent bond. Such approaches sometimes predict false positives, as not all Michael acceptors are found to be Ames-positive. The formation of such covalent bonds can be explored computationally using density functional theory transition state modeling. We have applied this approach to mutagenicity, allowing us to calculate the activation energy required for α,β-unsaturated carbonyls to react with a model system for the guanine nucleobase of DNA. These calculations have allowed us to identify that chemical compounds with activation energies greater than or equal to 25.7 kcal/mol are not able to bind directly to DNA. This allows us to reduce the false positive rate for computationally predicted mutagenicity assays. This methodology can be used to investigate other covalent-bond-forming reactions that can lead to toxicological outcomes and learn more about experimental results.

Discovery of a Potent, Selective T-type Calcium Channel Blocker as a Drug Candidate for the Treatment of Generalized Epilepsies

We report here the discovery and pharmacological characterization of N-(1-benzyl-1H-pyrazol-3-yl)-2-phenylacetamide derivatives as potent, selective, brain-penetrating T-type calcium channel blockers. Optimization focused mainly on solubility, brain penetration, and the search for an aminopyrazole metabolite that would be negative in an Ames test. This resulted in the preparation and complete characterization of compound 66b (ACT-709478), which has been selected as a clinical candidate.