Alexander Neugebauer

Design, Synthesis, and Biological Evaluation of (Hydroxyphenyl)naphthalene and -quinoline Derivatives : Potent and Selective Nonsteroidal Inhibitors of 17β-Hydroxysteroid Dehydrogenase Type 1 (17β-HSD1) for the Treatment of Estrogen-Dependent Diseases

Human 17beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD1) catalyzes the reduction of the weak estrogen estrone (E1) to the highly potent estradiol (E2). This reaction takes place in the target cell where the estrogenic effect is exerted via the estrogen receptor (ER). Estrogens, especially E2, are known to stimulate the proliferation of hormone-dependent diseases. 17beta-HSD1 is overexpressed in many breast tumors. Thus, it is an attractive target for the treatment of these diseases. Ligand- and structure-based drug design led to the discovery of novel, selective, and potent inhibitors of 17beta-HSD1. Phenyl-substituted bicyclic moieties were synthesized as mimics of the steroidal substrate. Computational methods were used to obtain insight into their interactions with the protein. Compound 5 turned out to be a highly potent inhibitor of 17beta-HSD1 showing good selectivity (17beta-HSD2, ERalpha and beta), medium cell permeation, reasonable metabolic stability (rat hepatic microsomes), and little inhibition of hepatic CYP enzymes.

Design, synthesis and biological evaluation of bis(hydroxyphenyl) azoles as potent and selective non-steroidal inhibitors of 17β-hydroxysteroid dehydrogenase type 1 (17β-HSD1) for the treatment of estrogen-dependent diseases

The 17beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD1) catalyses the reduction of the weakly active estrone (E1) into the most potent estrogen, 17beta-estradiol (E2). E2 stimulates the growth of hormone-dependent diseases via activation of the estrogen receptors (ERs). 17beta-HSD1 is often over-expressed in breast cancer cells. Thus, it is an attractive target for the treatment of mammary tumours. The combination of a ligand- and a structure-based drug design approach led to the identification of bis(hydroxyphenyl) azoles as potential inhibitors of 17beta-HSD1. Different azoles and hydroxy substitution patterns were investigated. The compounds were evaluated for activity and selectivity with regard to 17beta-HSD2, ERalpha and ERbeta. The most potent compound is 3-[5-(4-hydroxyphenyl)-1,3-oxazol-2-yl]phenol (18, IC(50)=0.31 microM), showing very good selectivity, high cell permeability and medium CaCo-2 permeability.

Substituted 6-Phenyl-2-naphthols. Potent and Selective Nonsteroidal Inhibitors of 17β-Hydroxysteroid Dehydrogenase Type 1 (17β-HSD1): Design, Synthesis, Biological Evaluation, and Pharmacokinetics

17beta-Estradiol (E2) is implicated in the genesis and the development of estrogen-dependent diseases. Its concentration is mainly regulated by 17beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD1), which catalyzes the reduction of the weak estrogen estrone (E1) to the highly potent E2. This enzyme is thus an important target for the treatment of hormone-dependent diseases. Thirty-seven novel substituted 6-phenyl-2-naphthols were synthesized and evaluated for 17beta-HSD1 inhibition, selectivity toward 17beta-HSD2 and the estrogen receptors (ERs) alpha and beta, and pharmacokinetic properties. SAR studies revealed that the compounds most likely bind according to binding mode B to the active site, i.e., the 6-phenyl moiety mimicking the steroidal A-ring. While substitution at the phenyl ring decreased activity, introduction of substituents at the naphthol moiety led to highly active compounds, especially in position 1. The 1-phenyl compound 32 showed a very high inhibitory activity for 17beta-HSD1 (IC50 = 20 nM) and good selectivity (17beta-HSD2 and ERs) and pharmacokinetic properties after peroral application.

How accurately can we calculate molecular CH and CC re distances by DFT methods? Dependence on basis sets and functionals, estimations of experimentally inaccessible re distances and distance-dependent scaling factors for approximations of triple-zeta quality

Abstract Optimized bond lengths have been calculated by DFT methods using six functionals and 10 basis sets. None of the predicted values agreed completely with the experimental r e distances and they are in general too large. Available accurate experimental r e distances for CH and CC bonds of simple organic molecules have been linearly correlated with corresponding DFT optimized molecular structures. These regression equations can be used for prediction of accurate experimental r e equilibrium distances of CH and CC bonds of medium-sized to large molecules. The derived regression equations also enable the introduction of distance dependent scaling factors which allow very accurate predictions of higher order basis set geometries from lower order calculations. Analytical equations for the determination of these scaling factors have been derived. Thus, large savings of CPU time (dependent on the size of the system) are possible. Applications to both small hydrocarbons with up to six carbon atoms and larger molecules such as alanin dipeptide and vitamin A are presented. Likewise, more critical test cases such as singlet and triplet methylencarbene and strained cyclic hydrocarbons are considered.

Structural modifications of salicylates: inhibitors of human CD81-receptor HCV-E2 interaction.

Starting point of the present paper was the result of a virtual screening using the open conformation of the large extracellular loop (LEL) of the CD81‐receptor (crystal structure: PDB‐ID: 1G8Q). After benzyl salicylate had been experimentally validated to be a moderate inhibitor of the CD81‐LEL–HCV‐E2 interaction, further optimization was performed and heterocyclic‐substituted benzyl salicylate derivatives were synthesized. The compounds were tested for their ability to inhibit the interaction of a fluorescence‐labeled antibody to CD81‐LEL using HUH7.5 cells. No compound showed an increase concerning the inhibition of the protein‐protein interaction compared to benzyl salicylate.

Reliability of ab initio (HF, post HF and DFT) methods and basis set dependencies for accurate prediction of equilibrium re distances of CO bond lengths

Abstract Optimized bond lengths for molecules containing CO bonds have been calculated by HF, post HF (MP2, LMP2, MP4(SDQ), CCSD(T) and DFT (BLYP, B3LYP, B3PW91, BHandH) methods using different basis sets. Linear regressions of calculated and experimentally available re CO bond lengths of organic molecules have been performed. The best basis set out of the set of up to 10 standard basis sets within a theoretical method was derived from a ranking procedure based on statistical parameters. This ranking scheme allows also the determination of the best method/basis set combination for all selected methods and basis sets. We studied the application of our recently developed prediction schemes for estimations of higher order basis set CO distances from lower order calculations and estimations of CO re bond lengths from linear regression equations. These procedures allow predictions of near re CO distances of high accuracy even form modest level of theory. Therefore this leads to a chance for treatment of large or difficult to handle molecules for which experimental determinations of re structures are inaccessible.