Structural motifs modulating the carcinogenic risk of aromatic amines

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.

Mechanism-based structure-activity relationship (SAR) analysis of aromatic amines and nitroaromatics carcinogenicity via statistical analyses based on CPDB

Cancer is a leading cause of human mortality around the globe. In this study, mechanism-based SAR (Structure-Activity Relationship) was employed to investigate the carcinogenicity of aromatic amines and nitroaromatics based on CPDB. Principal component analysis and cluster analysis were used to construct the SAR model. Principle component analysis generated three principal components from 12 mechanism-based descriptors. The extracted principal components were later used for cluster analysis, which divided the selected 55 chemicals into six clusters. The three principal components were proposed to describe the "transport", "reactivity" and "electrophilicity" properties of the chemicals. Cluster analysis indicated that the relevant "transport" properties positively correlated with the carcinogenic potential and were contributing factors in determining the carcinogenicity of the studied chemicals. The mechanism-based SAR analysis suggested the electron donating groups, electron withdrawing groups and planarity are significant factors in determining the carcinogenic potency for studied aromatic compounds. The present study may provide insights into the relationship between the three proposed properties and the carcinogenesis of aromatic amines and nitroaromatics.

Enhancing Drug Efficacy and Therapeutic Index through Cheminformatics-Based Selection of Small Molecule Binary Weapons That Improve Transporter-Mediated Targeting: A Cytotoxicity System Based on Gemcitabine

The transport of drug molecules is mainly determined by the distribution of influx and efflux transporters for which they are substrates. To enable tissue targeting, we sought to develop the idea that we might affect the transporter-mediated disposition of small-molecule drugs via the addition of a second small molecule that of itself had no inhibitory pharmacological effect but that influenced the expression of transporters for the primary drug. We refer to this as a “binary weapon” strategy. The experimental system tested the ability of a molecule that on its own had no cytotoxic effect to increase the toxicity of the nucleoside analog gemcitabine to Panc1 pancreatic cancer cells. An initial phenotypic screen of a 500-member polar drug (fragment) library yielded three “hits.” The structures of 20 of the other 2,000 members of this library suite had a Tanimoto similarity greater than 0.7 to those of the initial hits, and each was itself a hit (the cheminformatics thus providing for a massive enrichment). We chose the top six representatives for further study. They fell into three clusters whose members bore reasonable structural similarities to each other (two were in fact isomers), lending strength to the self-consistency of both our conceptual and experimental strategies. Existing literature had suggested that indole-3-carbinol might play a similar role to that of our fragments, but in our hands it was without effect; nor was it structurally similar to any of our hits. As there was no evidence that the fragments could affect toxicity directly, we looked for effects on transporter transcript levels. In our hands, only the ENT1-3 uptake and ABCC2,3,4,5, and 10 efflux transporters displayed measurable transcripts in Panc1 cultures, along with a ribonucleoside reductase RRM1 known to affect gemcitabine toxicity. Very strikingly, the addition of gemcitabine alone increased the expression of the transcript for ABCC2 (MRP2) by more than 12-fold, and that of RRM1 by more than fourfold, and each of the fragment “hits” served to reverse this. However, an inhibitor of ABCC2 was without significant effect, implying that RRM1 was possibly the more significant player. These effects were somewhat selective for Panc cells. It seems, therefore, that while the effects we measured were here mediated more by efflux than influx transporters, and potentially by other means, the binary weapon idea is hereby fully confirmed: it is indeed possible to find molecules that manipulate the expression of transporters that are involved in the bioactivity of a pharmaceutical drug. This opens up an entirely new area, that of chemical genomics-based drug targeting.

QSARs of aromatic amines: identification of potent carcinogens

In previous investigations, we have developed Quantitative Structure-Activity Relationships (QSAR) models for a series of aromatic amines based on well defined physicochemical descriptors: these QSARs were aimed at: (a) describing the modulation of the carcinogenic potency among the active ones only; and (b) modeling the separation between carcinogens and non-carcinogens. In this analysis based on a larger range of chemicals, we checked and confirmed the validity and robustness of the previous models. Since the identification of high potency carcinogens (which pose the highest risk to human health) is particularly relevant to risk assessment, we also established a new QSAR model that points directly to aromatic amines likely to have high carcinogenic potency.