Identification of PPARgamma ligands with One-dimensional Drug Profile Matching.

INTRODUCTION: Computational molecular database screening helps to decrease the time and resources needed for drug development. Reintroduction of generic drugs by second medical use patents also contributes to cheaper and faster drug development processes. We screened, in silico, the Food and Drug Administration-approved generic drug database by means of the One-dimensional Drug Profile Matching (oDPM) method in order to find potential peroxisome proliferator-activated receptor gamma (PPARgamma) agonists. The PPARgamma action of the selected generics was also investigated by in vitro and in vivo experiments. MATERIALS AND METHODS: The in silico oDPM method was used to determine the binding potency of 1,255 generics to 149 proteins collected. In vitro PPARgamma activation was determined by measuring fatty acid-binding protein 4/adipocyte protein gene expression in a Mono Mac 6 cell line. The in vivo insulin sensitizing effect of the selected compound (nitazoxanide; 50-200 mg/kg/day over 8 days; n = 8) was established in type 2 diabetic rats by hyperinsulinemic euglycemic glucose clamping. RESULTS: After examining the closest neighbors of each of the reference set's members and counting their most abundant neighbors, ten generic drugs were selected with oDPM. Among them, four enhanced fatty acid-binding protein/adipocyte protein gene expression in the Mono Mac 6 cell line, but only bromfenac and nitazoxanide showed dose-dependent actions. Induction by nitazoxanide was higher than by bromfenac. Nitazoxanide lowered fasting blood glucose levels and improved insulin sensitivity in type 2 diabetic rats. CONCLUSION: We demonstrated that the oDPM method can predict previously unknown therapeutic effects of generic drugs. Nitazoxanide can be the prototype chemical structure of the new generation of insulin sensitizers

Involvement of cholecystokinin in baseline and post-prandial whole body insulin

The objective of the study was to investigate the role of cholecystokinin (CCK) on the food-induced insulin sensitization phenomenon in healthy Long Evans Tokushima Otsuka (LETO) and Otsuka Long Evans Tokushima Fatty (OLETF) rats. Whole body insulin sensitivity determined by hyperinsulinaemic euglycaemic glucose clamping and the rapid insulin sensitivity test served as endpoints. Determinations were done in both fasted and re-fed animals. The involvement of CCK in post-prandial insulin sensitization was assessed by using proglumide, a CCK receptor blocker, by assessment of hypothalamic CCK-1/CCK-2 receptor expression by rt-PCR technique and by plasma insulin immunoreactivity determinations by means of radioimmunoassay as pharmacological, genetic and analytical approaches, respectively. The body weight of the OLETF rats and the amount of food consumed much exceeded those seen with LETO rats. The post-prandial increase in insulin sensitivity was marked in LETO, but not in OLETF rats. Intravenous proglumide attenuated post-prandial insulin sensitivity in LETO rats, with no effect in OLETF rats. Nevertheless, baseline insulin sensitivity was much lower in OLETF than in LETO rats. Treatment with rosiglitazone increased baseline insulin sensitivity of OLETF rats and evoked an increase in CCK-1 receptor gene expression in LETO rats. The results provide evidence for the involvement of CCK receptors in adjustment of both fasting and post-prandial insulin sensitivity. The data obtained with OLETF rats strongly suggest the predominant role of CCK-1 receptor

Identification of PPARγ ligands with One-dimensional Drug Profile Matching

Diána Kovács,1 Zoltán Simon,2,3 Péter Hári,2,3 András Málnási-Csizmadia,2,4,5 Csaba Hegedus,6 László Drimba,1 József Németh,1 Réka Sári,1 Zoltán Szilvássy,1 Barna Peitl11Department of Pharmacology and Pharmacotherapy, University of Debrecen, Debrecen, Hungary; 2Drugmotif, Ltd, Veresegyház, Hungary; 3Printnet, Ltd, Budapest, Hungary; 4Department of Biochemistry, Institute of Biology, Eötvös Loránd University, Budapest, Hungary; 5Molecular Biophysics Research Group, Hungarian Academy of Sciences – Eötvös Loránd University, Budapest, Hungary; 6Cera-Med Ltd, Debrecen-Józsa, HungaryIntroduction: Computational molecular database screening helps to decrease the time and resources needed for drug development. Reintroduction of generic drugs by second medical use patents also contributes to cheaper and faster drug development processes. We screened, in silico, the Food and Drug Administration-approved generic drug database by means of the One-dimensional Drug Profile Matching (oDPM) method in order to find potential peroxisome proliferator-activated receptor gamma (PPARγ) agonists. The PPARγ action of the selected generics was also investigated by in vitro and in vivo experiments.Materials and methods: The in silico oDPM method was used to determine the binding potency of 1,255 generics to 149 proteins collected. In vitro PPARγ activation was determined by measuring fatty acid-binding protein 4/adipocyte protein gene expression in a Mono Mac 6 cell line. The in vivo insulin sensitizing effect of the selected compound (nitazoxanide; 50–200 mg/kg/day over 8 days; n = 8) was established in type 2 diabetic rats by hyperinsulinemic euglycemic glucose clamping.Results: After examining the closest neighbors of each of the reference set’s members and counting their most abundant neighbors, ten generic drugs were selected with oDPM. Among them, four enhanced fatty acid-binding protein/adipocyte protein gene expression in the Mono Mac 6 cell line, but only bromfenac and nitazoxanide showed dose-dependent actions. Induction by nitazoxanide was higher than by bromfenac. Nitazoxanide lowered fasting blood glucose levels and improved insulin sensitivity in type 2 diabetic rats.Conclusion: We demonstrated that the oDPM method can predict previously unknown therapeutic effects of generic drugs. Nitazoxanide can be the prototype chemical structure of the new generation of insulin sensitizers.Keywords: computer-aided prediction of receptor-ligand interaction, in silico lead selection, insulin sensitizers, one-dimensional drug profile matching, peroxisome proliferator activated receptor gamma, PPARγ, type two diabete