ISSN print edition: 0366-6352 ISSN electronic edition: 1336-9075 Registr. No.: MK SR 9/7 Published monthly

Structural basis of pyrazolopyrimidine derivatives as CAMKIIδ kinase inhibitors: insights from 3D QSAR, docking studies and in silico ADMET evaluation

Adnane Aouidate, Adib Ghaleb, Mounir Ghamali, Samir Chtita, Abdellah Ousaa, M’barek Choukrad, Abdelouahid Sbai, Mohammed Bouachrine, and Tahar Lakhlifi

Moulay Ismail University, Meknes, Morocco

E-mail: a.aouidate@hotmail.fr

Abstract: Ca²⁺/calmodulin-dependent protein kinase II (CAMKIIδ) belongs to the serine/threonine kinase family, which is involved in a broad range of cellular events in cell survival and proliferation as well as a number of other signal transduction pathways. Thus, it is regarded a promising target for treatment of cancers. In the present paper, a three-dimensional quantitative structure–activity relationship and molecular docking were applied to investigate a series of new CAMKIIδ inhibitors of pyrazolopyrimidine derivatives. The determination coefficient (R²) and leave-one-out cross-validation coefficient (Q²) of CoMSIA model are 0.676 and 0.956, respectively. The predictive ability of this model was evaluated by the external validation using a test set of eight compounds with a predicted determination coefficient (R^{ 2}_{ ext{test}}) of 0.80, besides the mean absolute error of the test set was 0.328 log units. Docking results are in concordance with CoMSIA contour maps, gave the information for interactive mode exploration. Based on those satisfactory results, newly designed molecules were predicted with highly potent CAMKIIδ inhibitory activity, additionally, they have showed promising results in the preliminary in silico ADMET evaluations. This study could expand our understanding of pyrazolopyrimidine derivatives as inhibitors of CAMKIIδ and would be of great help in lead optimization for early drug discovery of highly potent CAMKIIδ inhibitors.

Keywords: 3D-QSAR ; Molecular docking ; CAMKIIδ ; Drug design ; Pyrazolopyrimidine ; In silico ADMET 

Full paper is available at www.springerlink.com.

DOI: 10.1007/s11696-018-0510-y

Chemical Papers 72 (11) 2833–2847 (2018)