In Silico Evaluation Of Cucurbit[6]Uril As A Potential Detector For Cocaine And Its Adulterants Lidocaine, Caffeine, And Procaine

Illicit drugs and their trafficking require worldwide efforts in investigation, detection, and control. Colorimetric tests are often applied to identify drugs. Cocaine has some well-known adulterants that can provide a false positive response. Cucurbit[6]uril (CB[6]) has been suggested as a potential detector for cocaine and other illicit drugs. This work uses in silico methods to evaluate the use of CB[6] to detect cocaine and these interfering substances. More specifically, this work analyzes different possibilities of CB[6] complexation with cocaine, lidocaine, caffeine, and procaine and compares the results achieved for cocaine and its adulterants. Different methodologies were employed: quantum chemistry was investigated through DFT B3LYP/TZVP (density functional theory-Becke, three-parameter, Lee-Yang-Parr with triple zeta valence plus polarization basis set) and the semi-empirical methods Austin model 1 (AM1), parametric methods 3, 6, and 7 (PM3, PM6, PM7), and Recife model 1 (RM1). We used these methodologies intending to compare the reasonability and reproducibility of the results in the gas phase condition. Solvent influence was studied by molecular dynamics (MD) simulations. Results showed that CB[6] does not bind to these substances, as judged from the positive values of binding free energy obtained with all methods. DFT and MD were the most reliable methods whereas semiempirical ones were not reproductible in describing these systems. Results also showed that interactions are not specific, so CB[6] does not provide a good response for cocaine detection.