Several Pt(IV) complexes of the general formula [Pt(L)2(L')2(L'')2] [axial ligands L are Cl-, RCOO-, or OH-; equatorial ligands L' are two am(m)ine or one diamine; and equatorial ligands L'' are Cl- or glycolato] were rationally designed and synthesized in the attempt to develop a predictive quantitative structure-activity relationship (QSAR) model. Numerous theoretical molecular descriptors were used alongside physicochemical data (i.e., reduction peak potential, Ep, and partition coefficient, log Po/w) to obtain a validated QSAR between in vitro cytotoxicity (half maximal inhibitory concentrations, IC50, on A2780 ovarian and HCT116 colon carcinoma cell lines) and some features of Pt(IV) complexes. In the resulting best models, a lipophilic descriptor (log Po/w or the number of secondary sp3 carbon atoms) plus an electronic descriptor (Ep, the number of oxygen atoms, or the topological polar surface area expressed as the N,O polar contribution) is necessary for modeling, supporting the general finding that the biological behavior of Pt(IV) complexes can be rationalized on the basis of their cellular uptake, the Pt(IV)-->Pt(II) reduction, and the structure of the corresponding Pt(II) metabolites. Novel compounds were synthesized on the basis of their predicted cytotoxicity in the preliminary QSAR model, and were experimentally tested. A final QSAR model, based solely on theoretical molecular descriptors to ensure its general applicability, is proposed.

Fragrance materials are used as ingredients in many consumer and personal care products. The wide and daily use of these substances, as well as their mainly uncontrolled discharge through domestic sewage, make fragrance materials both potential indoor and outdoor air pollutants which are also connected to possible toxic effects on humans (asthma, allergies, headaches). Unfortunately, little is known about the environmental fate and toxicity of these substances. However, the use of alternative, predictive approaches, such as quantitative structure-activity relationships (QSARs), can help in filling the data gap and in the characterization of the environmental and toxicological profile of these substances. In the proposed study, ordinary least squares regression-based QSAR models were developed for three toxicological endpoints: mouse oral LD(50), inhibition of NADH-oxidase (EC(50) NADH-Ox) and the effect on mitochondrial membrane potential (EC(50) DeltaPsim). Theoretical molecular descriptors were calculated by using DRAGON software, and the best QSAR models were developed according to the principles defined by the Organization for Economic Co-operation and Development.

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