Antidepressants are psychiatric agents used for the treatment of different types of depression, being at present amongst the most commonly prescribed drugs, while their effectiveness and adverse effects are still the subject of many studies. To reduce the inefficiency of known antidepressants caused by their side-effects, many research efforts have recently focused on the development of improved strategies for new antidepressants drug design. For this reason it is necessary to apply very fast and precise techniques, such as QSAR (Quantitative Structure-Activity Relationships) and QRAR (Quantitative Retention-Activity Relationship), which are capable to analyze and predict the biological activity for these structures, taking in account the possible changes of the molecular structures and chromatographic parameters. We discuss the pharmaceutical descriptors (van der Waals, electrostatic, hydrophobicity, hydrogen donor/acceptor bond, Verloop's parameters, polar area) involved in QSAR and also chromatographic parameters involved in QRAR studies of antidepressants. Antidepressant activities of alkanol piperazine, acetamides, arylpiperazines, thienopyrimidinone derivatives (as preclinical antidepressants) and also the antidepressants already used in clinical practice are mentioned.

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Within medicinal chemistry nowadays, the so-called pharmaco-dynamics seeks for qualitative (for understanding) and quantitative (for predicting) mechanisms/models by which given chemical structure or series of congeners actively act on biological sites either by focused interaction/therapy or by diffuse/hazardous influence. To this aim, the present review exposes three of the fertile directions in approaching the biological activity by chemical structural causes: the special computing trace of the algebraic structure-activity relationship (SPECTRAL-SAR) offering the full analytical counterpart for multi-variate computational regression, the minimal topological difference (MTD) as the revived precursor for comparative molecular field analyses (CoMFA) and comparative molecular similarity indices analysis (CoMSIA); all of these methods and algorithms were presented, discussed and exemplified on relevant chemical medicinal systems as proton pump inhibitors belonging to the 4-indolyl,2-guanidinothiazole class of derivatives blocking the acid secretion from parietal cells in the stomach, the 1-[(2-hydroxyethoxy)-methyl]-6-(phenylthio)thymine congeners’ (HEPT ligands) antiviral activity against Human Immunodeficiency Virus of first type (HIV-1) and new pharmacophores in treating severe genetic disorders (like depression and psychosis), respectively, all involving 3D pharmacophore interactions.

Molecular modeling and MTD methods are useful tools to assess both qualitative (SAR) and quantitative (QSAR) chemical structure-biological activity relationships. The 1-[(2-hydroxiethoxi)-methyl]-6-(phenylthio)thymine congeners (HEPT ligands) show in vitro anti-viral activity against the type-1 human immunodeficiency virus (HIV-1), which is the etiologic agent of AIDS. This work shows an extensive QSAR study performed upon a large series of 79 HEPT ligands using the MTD and HyperChem molecular modeling methods. The studied HEPT ligands are HIV reverse-transcriptase inhibitors. Their geometries were optimized and conformational analysis was carried out to build the hypermolecule, which allowed applying the MTD method. The hypermolecule was used for space mapping of the receptor's interaction site. The obtained results show that there are three 3D molecular zones important for the anti-HIV biological activity of the HEPT ligands under study.Int. J. Mol. Sci. 2006, 7 538

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