Abstract
The c-Jun N-terminal Kinase 3 (JNK3) is a family of protein kinases that plays an important role in the neurodegenerative diseases such as Alzheimer’s disease. Here, we have performed 2D and 3D quantitative structure–activity relationship (2D/3D-QSAR), molecular docking, absorption, distribution, metabolism, excretion and toxicity (ADMET) approaches on a series of tetra-substituted pyrdinylimidazoles derivatives as JNK3 inhibitors. The aim was to design the new potent JNK3 inhibitors with high inhibitory activity. The significant 2D-QSAR models showed a good correlation between observed activity and predicted ones (R2PLS = 0.87 and R2ANN = 0.88) using partial least squares (PLS) and artificial neural network (ANN) methods. The three descriptors vsurf_G, lip-don and SMR_VSA1 that are used in the construction of 2D-QSAR models play a significant role in JNK3 inhibition. Comparative molecular similarity indices analysis (CoMSIA) was used to construct the best 3D-QSAR model using PLS method, showing good correlative and predictive capabilities (R2 = 0.96, Q2 = 0.67 and SEE = 0.14). The steric and H-bond acceptor fields play an important role in the variation of biological activity with four principal components. Molecular docking of selective inhibitors confirms the results obtained by 2D/3D-QSAR and indicate that Met 146 and Met 149 are the main residues that used to stabilize the ligand in the active site of JNK3 protein. Based on those satisfactory results, three new compounds were designed and analyzed by in silico ADMET method.
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El Aissouq, A., Toufik, H., Stitou, M. et al. In Silico Design of Novel Tetra-Substituted Pyridinylimidazoles Derivatives as c-Jun N-Terminal Kinase-3 Inhibitors, Using 2D/3D-QSAR Studies, Molecular Docking and ADMET Prediction. Int J Pept Res Ther 26, 1335–1351 (2020). https://doi.org/10.1007/s10989-019-09939-8
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DOI: https://doi.org/10.1007/s10989-019-09939-8