Skin Sensitization Prediction Using Quantum Chemical Calculations: A Theoretical Model for the S_NAr Domain

It is widely accepted that skin sensitization begins with the sensitizer in question forming a covalent adduct with a protein electrophile or nucleophile. We investigate the use of quantum chemical methods in an attempt to rationalize the sensitization potential of chemicals of the S_NAr reaction domain. We calculate the full reaction profile for 23 chemicals with experimental sensitization data. For all quantitative measurements, we find that there is a good correlation between the reported pEC3 and the calculated barrier to formation of the low energy product or intermediate (<i>r</i>² = 0.64, <i>N</i> = 12) and a stronger one when broken down by specific subtype (<i>r</i>² > 0.9). Using a barrier cutoff of ∼10 kcal/mol allows us to categorize 100% (<i>N</i> = 12) of the sensitizers from the nonsensitizers (<i>N</i> = 11), with just 1 nonsensitizer being mispredicted as a weak sensitizer (9%). This model has an accuracy of ∼96%, with a sensitivity of 100% and a specificity of ∼91%. We find that the kinetic and thermodynamic information provided by the complete profile can help in the rationalization process, giving additional insight into a chemical’s potential for skin sensitization

Skin Sensitization Prediction Using Quantum Chemical Calculations: A Theoretical Model for the S_NAr Domain

It is widely accepted that skin sensitization begins with the sensitizer in question forming a covalent adduct with a protein electrophile or nucleophile. We investigate the use of quantum chemical methods in an attempt to rationalize the sensitization potential of chemicals of the S_NAr reaction domain. We calculate the full reaction profile for 23 chemicals with experimental sensitization data. For all quantitative measurements, we find that there is a good correlation between the reported pEC3 and the calculated barrier to formation of the low energy product or intermediate (<i>r</i>² = 0.64, <i>N</i> = 12) and a stronger one when broken down by specific subtype (<i>r</i>² > 0.9). Using a barrier cutoff of ∼10 kcal/mol allows us to categorize 100% (<i>N</i> = 12) of the sensitizers from the nonsensitizers (<i>N</i> = 11), with just 1 nonsensitizer being mispredicted as a weak sensitizer (9%). This model has an accuracy of ∼96%, with a sensitivity of 100% and a specificity of ∼91%. We find that the kinetic and thermodynamic information provided by the complete profile can help in the rationalization process, giving additional insight into a chemical’s potential for skin sensitization

Skin Sensitization Prediction Using Quantum Chemical Calculations: A Theoretical Model for the S_NAr Domain

It is widely accepted that skin sensitization begins with the sensitizer in question forming a covalent adduct with a protein electrophile or nucleophile. We investigate the use of quantum chemical methods in an attempt to rationalize the sensitization potential of chemicals of the S_NAr reaction domain. We calculate the full reaction profile for 23 chemicals with experimental sensitization data. For all quantitative measurements, we find that there is a good correlation between the reported pEC3 and the calculated barrier to formation of the low energy product or intermediate (<i>r</i>² = 0.64, <i>N</i> = 12) and a stronger one when broken down by specific subtype (<i>r</i>² > 0.9). Using a barrier cutoff of ∼10 kcal/mol allows us to categorize 100% (<i>N</i> = 12) of the sensitizers from the nonsensitizers (<i>N</i> = 11), with just 1 nonsensitizer being mispredicted as a weak sensitizer (9%). This model has an accuracy of ∼96%, with a sensitivity of 100% and a specificity of ∼91%. We find that the kinetic and thermodynamic information provided by the complete profile can help in the rationalization process, giving additional insight into a chemical’s potential for skin sensitization