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  • br Experimental Procedures br Acknowledgments The authors wi

    2019-11-28


    Experimental Procedures
    Acknowledgments The authors wish to thank P. Costet (University of Bordeaux) and Véronique Guyonnet-Duperat (FR TransBioMed, Plateforme de Vectorologie, University of Bordeaux) and Prof. Nils-Göran Larsson and Dr. Bettina Bertalan (Max Planck Institute for Biology of Ageing/Animal Facility, Cologne, Germany) for their valuable expertise and sharing the Tfamflox/flox mice. The authors acknowledge Vanessa Bergeron and Doriane Bortolotto for technical help and Pr. Hubert de Verneuil for useful discussion. H.R.R. gratefully acknowledges support from the ARC “Association pour la Recherche sur le Cancer,” the Institut National du Cancer “INCA_6654,” INCa-Canceropôle GSO, and FR TransBioMed. A.-K.B.-S. is supported by the Labex TRAIL (ANR-10-LABX-57). L.D. was supported by a grant from the SFD “Société Française de Dermatologie”.
    Dihydroorotate dehydrogenase (DHODH) catalyzes the conversion of dihydroorotate to orotate, which might be the rate-limiting step in the pyrimidine biosynthesis. Inhibitors of DHODH show immunosuppressant and antiproliferative activity, which is most pronounced on T-cells. Two examples of inhibitors that have been in clinical development are brequinar and leflunomide. The latter is used in the treatment of methotrexate refractive rheumatoid arthritis. These structural rolipram australia of DHODH inhibitors were discovered before DHODH protein was produced in a soluble form, therefore these structures were found by serendipity and their mechanism of action was only found out later. While several reports deal with novel DHODH inhibitors only two suggest to find novel classes of DHODH inhibitors using the X-ray structure of DHODH. Our strategy to develop DHODH inhibitors was based on the published crystal structure of the human enzyme. Docking of a library of commercially available compounds using our proprietary in silico screening technology (4Scan®) yielded compounds with a structure that has similarities to brequinar and redoxal, but is a novel chemotype. This class of compounds comprises cyclic aliphatic dicarboxylic acids, in which one carboxylic group is amide bound with an aromatic biphenylaniline. By synthesizing and testing a few analogues, we found that the optimal ring size was a pentacyclic ring with vicinal carboxyl groups separated by a double bond. This refinement yielded the lead compound with an inhibitory activity of 410nM (IC) against human DHODH, being comparable to the active metabolite of Leflunomide, A771726 (compound , ). Docking of into the ubiquinone binding site of the crystal structure of DHODH resulted in a positioning similar to that of brequinar as published: The carboxylic group forms an ion bond to Arg-136 of the enzyme and the biphenyl residue reaches into the hydrophobic pocket. The compounds were synthesized according to a published method. Substituted biarylanilines were obtained by the Suzuki cross coupling procedure using aromatic boronic acids and halo anilines with Pd and KF in methanol (). Inhibition and IC values were determined (was measured) in an in vitro enzyme assay using N-terminally truncated recombinant human DHODH. The assay is based on coupling the ubiquinone reduction to the redox dye 2,6-dichlorphenolindophenol (DCIP) as described. The reduction of DCIP was monitored photometrically by a decreasing absorbtion at 600nm. To improve the activity of the lead compound , we envisioned the introduction of small side chains into the biphenyl ring to obtain additional interactions in the hydrophobic pocket of DHODH. To avoid the synthesis of a large number of analogues in a classic medicinal chemistry fashion, we used a computational method to screen a virtual rolipram australia library of several thousand structures with the core scaffold of and bearing various substituents on the aromatic rings. First, a training set was generated by synthesis and biological testing of 55 compounds was performed. These subset of compounds was sufficiently diverse to allow the setup of a QSAR model. Each molecule was characterized by seventy 2D and internal coordinate dependent 3-D descriptors delivered from the MOE package. Partial least square analysis (PLS) of a subset of 44 molecules and their log(IC) lead to a cross-validated correlation coefficient of 0.60 and a root mean square error of 0.36. The optimal number of components used was seven. The resulting QSAR model allowed us the prediction of log(IC) values for the complete virtual library and the selection of 30 high scoring compounds for subsequent synthesis. Their average logarithmic activity was 1–2-fold higher, compared to the training set. Seven new molecules showed activities even beyond (higher than) the training set, and a new lead compound, 80 times more active than , emerged ().