Quantitative Structure Inter-Activity Relationship (QSInAR). Cytotoxicity Study of Some Hemisynthetic and Isolated Natural Steroids and Precursors on Human Fibrosarcoma Cells HT1080

Cholesterol Metabolism: A Potential Therapeutic Target in Glioblastoma

Glioblastoma is a highly lethal adult brain tumor with no effective treatments. In this review, we discuss the potential to target cholesterol metabolism as a new strategy for treating glioblastomas. Twenty percent of cholesterol in the body is in the brain, yet the brain is unique among organs in that it has no access to dietary cholesterol and must synthesize it de novo. This suggests that therapies targeting cholesterol synthesis in brain tumors might render their effects without compromising cell viability in other organs. We will describe cholesterol synthesis and homeostatic feedback pathways in normal brain and brain tumors, as well as various strategies for targeting these pathways for therapeutic intervention.

Synthesis of oxygenated oleanolic and ursolic acid derivatives with anti-inflammatory properties

The scalable syntheses of four oxygenated triterpenes have been implemented to access substantial quantities of maslinic acid, 3-epi-maslinic acid, corosolic acid, and 3-epi-corosolic acid. Semi-syntheses proceed starting from the natural products oleanolic acid and ursolic acid. Proceeding over five steps, each of the four compounds can be synthesized on the gram scale. Divergent diastereoselective reductions of α-hydroxy ketones provided access to the four targeted diol containing compounds from two precursors of the oleanane or ursane lineage. These compounds were subsequently evaluated for their ability to inhibit inflammatory gene expression in a mouse model of chemically induced skin inflammation. All compounds possessed the ability to inhibit the expression of one or more inflammatory genes induced by 12-O-tetradecanoylphorbol-13 acetate in mouse skin, however, three of the compounds, corosolic acid, 3-epi-corosolic acid and maslinic acid were more effective than the others. The availability of gram quantities will allow further testing of these compounds for potential anti-inflammatory activities as well as cancer chemopreventive activity.

Targeting cancer using cholesterol conjugates

Conjugation of cholesterol moiety to active compounds for either cancer treatment or diagnosis is an attractive approach. Cholesterol derivatives are widely studied as cancer diagnostic agents and as anticancer derivatives either in vitro or in vivo using animal models. In largely growing studies, anticancer agents have been chemically conjugated to cholesterol molecules, to enhance their pharmacokinetic behavior, cellular uptake, target specificity, and safety. To efficiently deliver anticancer agents to the target cells and tissues, many different cholesterol-anticancer conjugates were synthesized and characterized, and their anticancer efficiencies were tested in vitro and in vivo.

Design, synthesis, antifungal activities and 3D-QSAR of new N,N'-diacylhydrazines containing 2,4-dichlorophenoxy moiety

A series of new N,N'-diacylhydrazine derivatives were designed and synthesized. Their structures were verified by 1H-NMR, mass spectra (MS) and elemental analysis. The antifungal activities of these N,N'-diacylhydrazines were evaluated. The bioassay results showed that most of these N,N'-diacylhydrazines showed excellent antifungal activities against Cladosporium cucumerinum, Corynespora cassiicola, Sclerotinia sclerotiorum, Erysiphe cichoracearum, and Colletotrichum orbiculare in vivo. The half maximal effective concentration (EC50) of one of the compounds was also determined, and found to be comparable with a commercial drug. To further investigate the structure-activity relationship, comparative molecular field analysis (CoMFA) was performed on the basis of antifungal activity data. Both the steric and electronic field distributions of CoMFA are in good agreement in this study.

Introducing catastrophe-QSAR. Application on modeling molecular mechanisms of pyridinone derivative-type HIV non-nucleoside reverse transcriptase inhibitors

The classical method of quantitative structure-activity relationships (QSAR) is enriched using non-linear models, as Thom's polynomials allow either uni- or bi-variate structural parameters. In this context, catastrophe QSAR algorithms are applied to the anti-HIV-1 activity of pyridinone derivatives. This requires calculation of the so-called relative statistical power and of its minimum principle in various QSAR models. A new index, known as a statistical relative power, is constructed as an Euclidian measure for the combined ratio of the Pearson correlation to algebraic correlation, with normalized t-Student and the Fisher tests. First and second order inter-model paths are considered for mono-variate catastrophes, whereas for bi-variate catastrophes the direct minimum path is provided, allowing the QSAR models to be tested for predictive purposes. At this stage, the max-to-min hierarchies of the tested models allow the interaction mechanism to be identified using structural parameter succession and the typical catastrophes involved. Minimized differences between these catastrophe models in the common structurally influential domains that span both the trial and tested compounds identify the "optimal molecular structural domains" and the molecules with the best output with respect to the modeled activity, which in this case is human immunodeficiency virus type 1 HIV-1 inhibition. The best molecules are characterized by hydrophobic interactions with the HIV-1 p66 subunit protein, and they concur with those identified in other 3D-QSAR analyses. Moreover, the importance of aromatic ring stacking interactions for increasing the binding affinity of the inhibitor-reverse transcriptase ligand-substrate complex is highlighted.