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RET kinase gain-of-function mutations represent the main cause of the high aggressiveness and invasiveness of medullary thyroid cancer (MTC). The selective inhibition of the RET kinase is a suitable strategy for the treatment of this endocrine neoplasia. Herein, we performed an innovative ligand-based virtual screening protocol using the DRUDIT online web service, focusing on the RET kinase as a biological target. In this process, thieno[3,2- c ]quinolines 6a-e and 7a-e were proposed as new potential RET inhibitors. The selected compounds were synthetized by appropriate synthetic strategies, and in vitro evaluation of antiproliferative properties conducted on the particularly aggressive MTC cell line TT(C634R) identified compounds 6a-d as promising anticancer agents, with IC 50 values in the micromolar range. Further structure-based computational studies revealed a significant capability of the most active compounds to the complex RET tyrosine kinase domain. The interesting antiproliferative results supported by in silico predictions suggest that these compounds may represent a starting point for the development of a new series of small heterocyclic molecules for the treatment of MTC., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)

CDK-1 and PARP-1 play crucial roles in breast cancer progression. Compounds acting as CDK-1 and/or PARP-1 inhibitors can induct cell death in breast cancer with a selective synthetic lethality mechanism. A mixed treatment by means of CDK-1 and PARP-1 inhibitors resulted in radical breast cancer cell growth reduction. Inhibitors with a dual target mechanism of action could arrest cancer progression by simultaneously blocking the DNA repair mechanism and cell cycle, resulting in advantageous monotherapy. To this aim, in the present work, we identified compound 645656 with a significant affinity for both CDK-1 and PARP-1 by a mixed ligand- and structure-based virtual screening protocol. The Biotarget Predictor Tool was used at first in a Multitarget mode to filter the large National Cancer Institute (NCI) database. Then, hierarchical docking studies were performed to further screen the compounds and evaluate the ligands binding mode, whose putative dual-target mechanism of action was investigated through the correlation between the antiproliferative activity data and the target proteins' (CDK-1 and PARP-1) expression pattern. Finally, a Molecular Dynamics Simulation confirmed the high stability of the most effective selected compound 645656 in complex with both PARP-1 and CDK-1.

The viral main protease is one of the most attractive targets among all key enzymes involved in the life cycle of SARS-CoV-2. Considering its mechanism of action, both the catalytic and dimerization regions could represent crucial sites for modulating its activity. Dual-binding the SARS-CoV-2 main protease inhibitors could arrest the replication process of the virus by simultaneously preventing dimerization and proteolytic activity. To this aim, in the present work, we identified two series' of small molecules with a significant affinity for SARS-CoV-2 M PRO , by a hybrid virtual screening protocol, combining ligand- and structure-based approaches with multivariate statistical analysis. The Biotarget Predictor Tool was used to filter a large in-house structural database and select a set of benzo[ b ]thiophene and benzo[ b ]furan derivatives. ADME properties were investigated, and induced fit docking studies were performed to confirm the DRUDIT prediction. Principal component analysis and docking protocol at the SARS-CoV-2 M PRO dimerization site enable the identification of compounds 1b , c , i , l and 2i , l as promising drug molecules, showing favorable dual binding site affinity on SARS-CoV-2 M PRO .

The IKK kinases family represents a thrilling area of research because of its importance in regulating the activity of NF-kB transcription factors. The discovery of the central role played by IKK-beta in the activation of transcription in response to apoptotic or inflammatory stimuli allowed to considerate its modulation as a promising tool for the treatment of chronic inflammation and cancer. To date, several IKK-beta inhibitors have been discovered and tested. In this work, an analysis of the interactions between different classes of inhibitors and their biological target was performed, through the application of Molecular Docking and Pharmacophore/3D-QSAR approaches to a set of 141 inhibitors included in the Binding Database. In order to overcome the difficulty due to the lack of crystallographic data for IKK-beta, a homology model of this protein has been built and validated. The results allowed to study in depth the structural bases for the interaction of each family of inhibitors and provided clues for further modifications, with the aim of improving the activity and selectivity of designed drugs targeting this enzyme.