Drugmotif Ltd.

Veresegyház, Hungary

Drugmotif Ltd.

Veresegyház, Hungary

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Vegner L.,Eötvös Loránd University | Peragovics A.,Eötvös Loránd University | Tombor L.,Semmelweis University | Jelinek B.,Eötvös Loránd University | And 8 more authors.
Journal of Medicinal Chemistry | Year: 2013

We recently introduced Drug Profile Matching (DPM), a novel affinity fingerprinting-based in silico drug repositioning approach. DPM is able to quantitatively predict the complete effect profiles of compounds via probability scores. In the present work, in order to investigate the predictive power of DPM, three effect categories, namely, angiotensin-converting enzyme inhibitor, cyclooxygenase inhibitor, and dopamine agent, were selected and predictions were verified by literature analysis as well as experimentally. A total of 72% of the newly predicted and tested dopaminergic compounds were confirmed by tests on D1 and D2 expressing cell cultures. 33% and 23% of the ACE and COX inhibitory predictions were confirmed by in vitro tests, respectively. Dose-dependent inhibition curves were measured for seven drugs, and their inhibitory constants (Ki) were determined. Our study overall demonstrates that DPM is an effective approach to reveal novel drug-target pairs that may result in repositioning these drugs. © 2013 American Chemical Society.


Kepiro M.,Eötvös Loránd University | Varkuti B.H.,Eötvös Loránd University | Vegner L.,Eötvös Loránd University | Voros G.,Eötvös Loránd University | And 5 more authors.
Angewandte Chemie - International Edition | Year: 2014

Blebbistatin, the best characterized myosin II-inhibitor, is commonly used to study the biological roles of various myosin II isoforms. Despite its popularity, the use of blebbistatin is greatly hindered by its blue-light sensitivity, resulting in phototoxicity and photoconversion of the molecule. Additionally, blebbistatin has serious cytotoxic side effects even in the absence of irradiation, which may easily lead to the misinterpretation of experimental results since the cytotoxicity-derived phenotype could be attributed to the inhibition of the myosin II function. Here we report the synthesis as well as the in vitro and in vivo characterization of a photostable, C15 nitro derivative of blebbistatin with unaffected myosin II inhibitory properties. Importantly, para-nitroblebbistatin is neither phototoxic nor cytotoxic, as shown by cellular and animal tests; therefore it can serve as an unrestricted and complete replacement of blebbistatin both in vitro and in vivo. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


Peragovics A.,Eötvös Loránd University | Peragovics A.,Drugmotif Ltd. | Simon Z.,Drugmotif Ltd. | Simon Z.,Printnet Ltd. | And 9 more authors.
Journal of Chemical Information and Modeling | Year: 2013

We recently introduced Drug Profile Matching (DPM), a novel virtual affinity fingerprinting bioactivity prediction method. DPM is based on the docking profiles of ca. 1200 FDA-approved small-molecule drugs against a set of nontarget proteins and creates bioactivity predictions based on this pattern. The effectiveness of this approach was previously demonstrated for therapeutic effect prediction of drug molecules. In the current work, we investigated the applicability of DPM for target fishing, i.e. for the prediction of biological targets for compounds. Predictions were made for 77 targets, and their accuracy was measured by Receiver Operating Characteristic (ROC) analysis. Robustness was tested by a rigorous 10-fold cross-validation procedure. This procedure identified targets (N = 45) with high reliability based on DPM performance. These 45 categories were used in a subsequent study which aimed at predicting the off-target profiles of currently approved FDA drugs. In this data set, 79% of the known drug-target interactions were correctly predicted by DPM, and additionally 1074 new drug-target interactions were suggested. We focused our further investigation on the suggested interactions of antipsychotic molecules and confirmed several interactions by a review of the literature. © 2012 American Chemical Society.


Kovacs D.,Debrecen University | Simon Z.,Drugmotif Ltd | Simon Z.,Printnet Ltd | Hari P.,Drugmotif Ltd | And 9 more authors.
Drug Design, Development and Therapy | Year: 2013

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 (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. © 2013 Kovács et al. This work is published by Dove Medical Press Ltd.


Peragovics A.,Eötvös Loránd University | Peragovics A.,Drugmotif Ltd. | Simon Z.,Drugmotif Ltd. | Brandhuber I.,Drugmotif Ltd. | And 8 more authors.
Journal of Chemical Information and Modeling | Year: 2012

Drug Profile Matching (DPM), a novel virtual affinity fingerprinting method capable of predicting the medical effect profiles of small molecules, was introduced by our group recently. The method exploits the information content of interaction patterns generated by flexible docking to a series of rigidly kept nontarget protein active sites. We presented the ability of DPM to classify molecules excellently, and the question arose, what the contribution of 2D and 3D structural features of the small molecules is to the intriguingly high prediction power of DPM. The present study compared the prediction powers for effect profiles of 1163 FDA-approved drug compounds determined by DPM and ChemAxon 2D and 3D similarity fingerprinting approaches. We found that DPM outperformed the 2D and 3D approaches in almost all therapeutic categories for drug classification except for mechanically rigid structural categories where high accuracy was obtained by all three methods. Moreover, we also tested the predictive power of DPM on external data by reducing the parent data set and demonstrated that DPM can overcome the common screening problems of 2D and 3D similarity methods arising from the presence of structurally diverse molecules in certain effect categories. © 2012 American Chemical Society.

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