Chemometric and chemoinformatic analyses of anabolic and androgenic activities of testosterone and dihydrotestosterone analogues

Integration of ligand and structure-based virtual screening for identification of leading anabolic steroids

Parallel ligand- and structure-based virtual screenings of 269 steroids with anabolic activity evaluated in vivo were performed. The quantitative structure-activity relationship (QSAR) model expressed by selected descriptors as the octanol-water partition coefficient, the molar volume and the quantum mechanical calculated charge values on atoms C1, C2, C5, C9, C10, C14 and C17 of the steroid skeleton, expresses structural features of anabolic steroids (AS) contributing to the transport and steroid-receptor interaction. On the other hand, computational simulations of a candidate ligand binding to a receptor study (a "docking" procedure) predict the association of these AS with the human androgen receptor (AR). Fourteen compounds were identified as lead; the most potent was the 7α-methylestr-4-en-3, 17-dione. It was concluded that a good anabolic activity requires hydrogen bonding interactions between both Arg752 and Gln711 residues in the cycles A with O3 atom of the steroid and either Asn705 and Thr877 residues in the cycles D of steroid with O17 atom.

Anabolic and androgenic activities of 19-nor-testosterone steroids: QSAR study using quantum and physicochemical molecular descriptors

Quantitative structure-activity relationship (QSAR) study of 19-nor-testosterone steroids family was performed using quantum and physicochemical molecular descriptors. The quantum-chemical descriptors were calculated using semiempirical calculations. The descriptor values were statistically correlated using multi-linear regression analysis. The QSAR study indicated that the electronic properties of these derivatives have significant relationship with observed biological activities. The found QSAR equations explain that the energy difference between the LUMO and HOMO, the total dipole moment, the chemical potential and the value of the net charge of different carbon atoms in the steroid nucleus showed key interaction of these steroids with their anabolic-androgenic receptor binding site. The calculated values predict that the 17α-cyclopropyl-17β, 3β-hydroxy-4-estrene compound presents the highest anabolic-androgenic ratio (AAR) and the 7α-methyl-17β-acetoxy-estr-4-en-3-one compound the lowest AAR. This study might be helpful in the future successful identification of "real" or "virtual" anabolic-androgenic steroids.

Novel coumarin-based tyrosinase inhibitors discovered by OECD principles-validated QSAR approach from an enlarged, balanced database

The present work is devoted to the development and application of a multi-agent Quantitative Structure-Activity Relationship (QSAR) classification system for tyrosinase inhibitor identification, in which the individual QSAR outputs are the inputs of a fusion approach based on the voting mechanism. The individual models are based on TOMOCOMD-CARDD (TOpological Molecular COMputational Design-Computer Aided Rational Drug Design) atom-based bilinear descriptors and Linear Discriminant Analysis (LDA) on a novel enlarged, balanced database of 1,429 compounds within 701 greatly dissimilar molecules presenting anti-tyrosinase activity. A total of 21 adequate models are obtained taking into account the requirements of the Organization for Economic Cooperation and Development (OECD) principles for QSAR validation and present global accuracies (Q) above 84.50 and 79.27% in the training and test sets, respectively. The resulted fusion system is used for the in silico identification of synthesized coumarin derivatives as novel tyrosinase inhibitors. The 7-hydroxycoumarin (compound C07) shows potent activity for the inhibition of monophenolase activity of mushroom tyrosinase giving a value of inhibition percentage close to 100% in vitro assays, by means of spectrophotometric analysis. The current report could help to shed some clues in the identification of new chemicals that inhibit tyrosinase enzyme, for entering in the pipeline of drug discovery development.

A sensitive and specific precursor ion scanning approach in liquid chromatography/electrospray ionization tandem mass spectrometry to detect methylprednisolone acetate and its metabolites in rat urine

A new, simple, sensitive and specific liquid chromatography/electrospray ionization tandem mass spectrometric (LC/ESI-MS/MS) method in precursor ion scanning (PIS) mode has been developed for the rapid detection of methylprednisolone acetate (MPA) and its metabolites in rat urine. A suitable product ion specific for methylprednisolone (MP) and MPA was selected after a fragmentation study on 20 (cortico)steroids at different collision energies (5-40 eV). Urine samples were simply treated with acetonitrile then dried in a SpeedVac system. The method was validated and compared with other PIS methods for detecting corticosteroids in human urine. It was more sensitive, with limit of detection (LOD) and lower limit of quantitation (LLOQ), respectively, of 5 and 10 ng mL(-1). The method was applied for the analysis of rat urine collected before and after (24, 48, 72 h) intra-articular (IA) injection of a marketed formulation of MPA (Depo-Medrol(R)). MS/MS acquisitions were taken at different collision energies for the precursor ions of interest, detected in PIS mode, to verify the MP-related structure. Six different metabolites were detected in rat urine, and their chemical structures were assigned with a computational study.

Atom- and bond-based 2D TOMOCOMD-CARDD approach and ligand-based virtual screening for the drug discovery of new tyrosinase inhibitors

Two-dimensional atom- and bond-based TOMOCOMD-CARDD descriptors and linear discriminant analysis (LDA) are used in this report to perform a quantitative structure-activity relationship (QSAR) study of tyrosinase-inhibitory activity. A database of inhibitors of the enzyme is collected for this study, within 246 highly dissimilar molecules presenting antityrosinase activity. In total, 7 discriminant functions are obtained by using the whole set of atom- and bond-based 2D indices. All the LDA-based QSAR models show accuracies above 90% in the training set and values of the Matthews correlation coefficient (C) varying from 0.85 to 0.90. The external validation set shows globally good classifications between 89% and 91% and C values ranging from 0.75 to 0.81. Finally, QSAR models are used in the selection/identification of the 20 new dicoumarins subset to search for tyrosinase inhibitory activity. Theoretical and experimental results show good correspondence between one another. It is important to remark that most compounds in this series exhibit a more potent inhibitory activity against the mushroom tyrosinase enzyme than the reference compound, Kojic acid (IC(50) = 16.67 muM), resulting in a novel nucleus base (lead) with antityrosinase activity, and this could serve as a starting point for the drug discovery of novel tyrosinase inhibitor lead compounds. ( Journal of Biomolecular Screening 2008:1014-1024).