Overcoming Paradoxical Kinase Priming by a Novel MNK1 Inhibitor

Inhibidor de MNK1; OncologíaInhibidor de MNK1; OncologiaMNK1 inhibitor; OncologyTargeting the kinases MNK1 and MNK2 has emerged as a valuable strategy in oncology. However, most of the advanced inhibitors are acting in an adenosine triphosphate (ATP)-competitive mode, precluding the evaluation of different binding modes in preclinical settings. Using rational design, we identified and validated the 4,6-diaryl-pyrazolo[3,4-b]pyridin-3-amine scaffold as the core for MNK inhibitors. Signaling pathway analysis confirmed a direct effect of the hit compound EB1 on MNKs, and in line with the reported function of these kinases, EB1 only affects the growth of tumor but not normal cells. Molecular modeling revealed the binding of EB1 to the inactive conformation of MNK1 and the interaction with the specific DFD motif. This novel mode of action appears to be superior to the ATP-competitive inhibitors, which render the protein in a pseudo-active state. Overcoming this paradoxical activation of MNKs by EB1 represents therefore a promising starting point for the development of a novel generation of MNK inhibitors.This work was supported by the Instituto de Salud Carlos III (PI17/02247), (PI20/01687), and CIBERONC (CB16/12/00363). S.R.y.C. acknowledges support from the Generalitat de Catalunya (2017-9015-385045). E. Bou-Petit thanks the Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya (2017 FI_B2 00139) and the European Social Funds for her predoctoral fellowship

A Robust Control Strategy With Perturbation Estimation for the Parrot Mambo Platform

This article addresses theoretical and practical challenges associated with a commercially available and ready-to-fly small-scale unmanned aircraft system (UAS) developed by Parrot SA: the Mambo quad rotorcraft. The dynamic model and the structure of the controller running onboard the UAS autopilot are not disclosed by its manufacturers. For this reason, a novel robust controller for discrete-time systems under time delays and input saturation is first developed for this platform. Then, three fundamental estimation and control challenges are addressed. The first challenge is the system identification of the X and Y translational dynamics of the UAS. To accomplish this goal, input-output data pairs are collected from different UAS platforms during real-time experimental flights. A group of dynamic models are identified from the data pairs through an extended least-squares algorithm. The obtained models are similar in nature but exhibit parametrical variations due to uncertainties in the fabrication process and different levels of wear and tear. Using a time-varying modeling approach, the second challenge addresses the development of a robust controller, which guarantees the stability of all the identified dynamic models. The third challenge addresses the development of a nonlinear controller enhanced with a perturbation estimation, which can reject, from the nominal model, the effects of model uncertainties and perturbations. These theoretical developments are presented in the form of two original theorems. The proposed strategies are ultimately validated in a set of real-time experiments, demonstrating their effectiveness and applicability.Fil: Rubio Scola, Ignacio Eduardo Jesus. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Reyes, Gabriel Alexis Guijarro. New Mexico State University.; Estados UnidosFil: Carrillo, Luis Rodolfo Garcia. New Mexico State University.; Estados UnidosFil: Hespanha, Joao Pedro. University of California; Estados UnidosFil: Burlion, Laurent. State University of New Jersey; Estados Unido