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Using the density functional theory (DFT) formalism, we have investigated the properties of some arylsulphonyl indazole derivatives that we studied previously for their biological activity and susceptibility to interactions of azoles. This study includes the following physicochemical properties of these derivatives: electronegativity and polarisability (Mulliken charges, adjusted charge partitioning, and iterative-adjusted charge partitioning approaches); free energy of solvation (solvation model based on density model and M062X functional); highest occupied molecular orbital (HOMO)–lowest occupied molecular orbital (LUMO) gap together with the corresponding condensed Fukui functions, time-dependent DFT along with the UV spectra simulations using B3LYP, CAM-B3LYP, MPW1PW91, and WB97XD functionals, as well as linear response polarisable continuum model; and estimation of global chemical reactivity descriptors, particularly the chemical hardness factor. The charges on pyrrolic and pyridinic nitrogen (the latter one in the quinolone ring of compound 8, as well as condensed Fukui functions) reveal a significant role of these atoms in potential interactions of azole ligand–protein binding pocket. The lowest negative value of free energy of solvation can be attributed to carbazole 6, whereas pyrazole 7 has the least negative value of this energy. Moreover, the HOMO–LUMO gap and chemical hardness show that carbazole 6 and indole 5 exist as soft molecules, while fused pyrazole 7 has hard character.

Molecular hydrophobicity (lipophilicity), usually quantified as log "P" where "P" is the partition coefficient, is an important molecular characteristic in medicinal chemistry and drug design. The log "P" coefficient is one of the principal parameters for the estimation of lipophilicity of chemical compounds and pharmacokinetic properties. The understanding of log "P" parameter in the undergraduate medicinal chemistry course seems to be a pitfall for students. This parameter has typically been measured using experimental methods, but recently, log "P" has been determined using computational methods. The number of publications about lipophilicity predictions has gradually increased over the last 10 years, but the number of programs available for an online prediction of this important parameter remains limited. An interesting tool for calculation of log "P" coefficients is presented: the Virtual Computational Chemistry Laboratory (VCCLAB) package. The package includes the ALOGPS 2.1 program suitable for log "P" calculations. This software is accessible online and may be easily mastered by the undergraduate medicinal chemistry student. (Contains 1 table and 1 figure.)

The article presents the Virtual Computational Chemistry Laboratory (VCCLAB) package, a tool that can be used to calculate log P coefficients in medicinal chemistry and drug design. It describes the key features and advantages offered by the package which includes the ALOGPS 2.1 program suitable for log P calculations. It discusses the availability of the software online, and shows that it can easily be mastered by the undergraduate medicinal chemistry student.