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1.
ACS Chem Neurosci ; 13(9): 1433-1445, 2022 05 04.
Artigo em Inglês | MEDLINE | ID: mdl-35417128

RESUMO

USP30, a deubiquitinating enzyme family, forfeits the ubiquitination of E3 ligase and Parkin on the surface of mitochondria. Inhibition of USP30 results in mitophagy and cellular clearance. Herein, by understanding structural requirements, we discovered potential USP30 inhibitors from an imidazole series of ligands via a validated ubiquitin-rhodamine-110 fluorometric assay. A novel catalytic use of the Zn(l-proline)2 complex for the synthesis of tetrasubstituted imidazoles was identified. Among all compounds investigated, 3g and 3f inhibited USP30 at IC50 of 5.12 and 8.43 µM, respectively. The binding mode of compounds at the USP30 binding site was understood by a docking study and interactions with the key amino acids were identified. Compound 3g proved its neuroprotective efficacy by inhibiting apoptosis on SH-SY5Y neuroblastoma cells against dynorphin A (10 µM) treatment. Hence, the present study provides a new protocol to design and develop ligands against USP30, thereby offering a therapeutic strategy under conditions like kidney damage and neurodegenerative disorders including Parkinson's disease.


Assuntos
Proteínas Mitocondriais , Ubiquitina , Imidazóis/farmacologia , Ligantes , Proteínas Mitocondriais/metabolismo , Neuroproteção , Tioléster Hidrolases/metabolismo , Ubiquitina/metabolismo
2.
Comput Biol Chem ; 95: 107600, 2021 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-34794076

RESUMO

Peroxisome proliferator-activated receptor gamma (PPARγ), a member of the nuclear receptor superfamily is an excellent example of targets that orchestrates cancer, inflammation, lipid and glucose metabolism. We report a protocol for the development of novel PPARγ antagonists by employing 3D QSAR based virtual screening for the identification of ligands with anticancer properties. The models are generated based on a large and diverse set of PPARγ antagonist ligands by the HYPOGEN algorithm using Discovery Studio 2019 drug design software. Among the 10 hypotheses generated, Hypotheses 2 showed the highest correlation coefficient values of 0.95 with less RMS deviation of 1.193. Validation of the developed pharmacophore model was performed by Fischer's randomization and screening against test and decoy set. The GH score or goodness score was found to be 0.81 indicating moderate to a good model. The selected pharmacophore model Hypo 2 was used as a query model for further screening of 11,145 compounds from the PubChem, sc-PDB structure database, and designed novel ligands. Based on fit values and ADMET filter, the final 10 compounds with the predicated activity of ≤ 3 nM were subjected for docking analysis. Docking analysis revealed the unique binding mode with hydrophobic amino acid that can cause destabilization of the H12 which is an important molecular mechanism to prove its antagonist action. Based on high CDocker scores, Cpd31 was synthesized, purified, analyzed and screened for PPARγ competitive binding by TR-FRET assay. The biochemical protein binding results matched the predicted results. Further, Cpd31 was screened against cancer cells and validated the results.


Assuntos
Anilidas/farmacologia , Antineoplásicos/farmacologia , Desenho de Fármacos , PPAR gama/antagonistas & inibidores , Algoritmos , Anilidas/síntese química , Anilidas/química , Antineoplásicos/síntese química , Antineoplásicos/química , Ligação Competitiva/efeitos dos fármacos , Humanos , Simulação de Acoplamento Molecular , Estrutura Molecular , PPAR gama/metabolismo
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