SMILES notation based optimal descriptors as a universal tool for the QSAR analysis with further application in drug discovery and design is presented. The basis of this QSAR modeling is Monte Carlo method which has important advantages over other methods, like the possibility of analysis of a QSAR as a random event, is discussed. The advantages of SMILES notation based optimal descriptors in comparison to commonly used descriptors are defined. The published results of QSAR modeling with SMILES notation based optimal descriptors applied for various pharmacologically important endpoints are listed. The presented QSAR modeling approach obeys OECD principles and has mechanistic interpretation with possibility to identify molecular fragments that contribute in positive and negative way to studied biological activity, what is of big importance in computer aided drug design of new compounds with desired activity.

Copper(II) and zinc(II) complexes with clinically used antifungal drug fluconazole (fcz), {[CuCl₂(fcz)₂]^.5H₂O}_n, 1, and {[ZnCl₂(fcz)₂]·2C₂H₅OH}_n, 2, were prepared and characterized by spectroscopic and crystallographic methods. The polymeric structure of the complexes comprises four fluconazole molecules monodentately coordinated via the triazole nitrogen and two chlorido ligands. With respect to fluconazole, complex 2 showed significantly higher antifungal activity against Candida krusei and Candida parapsilosis. All tested compounds reduced the total amount of ergosterol at subinhibitory concentrations, indicating that the mode of activity of fluconazole was retained within the complexes, which was corroborated via molecular docking with cytochrome P450 sterol 14α-demethylase (CYP51) as a target. Electrostatic, steric and internal energy interactions between the complexes and enzyme showed that 2 has higher binding potency to this target. Both complexes showed strong inhibition of C. albicans filamentation and biofilm formation at subinhibitory concentrations, with 2 being able to reduce the adherence of C. albicans to A549 cells in vitro. Complex 2 was able to reduce pyocyanin production in Pseudomonas aeruginosa between 10% and 25% and to inhibit its biofilm formation by 20% in comparison to the untreated control. These results suggest that complex 2 may be further examined in the mixed Candida-P. aeruginosa infections.