Abstract

Alzheimer’s disease (AD) represents a major public health concern and has been considered as a research priority. Recently, the tyrosine kinase c-Abl has been shown as a new and potential target of AD therapy. In the current study, sophisticated molecular docking and empirical scoring functions were integrated to develop a bioinformatics predictor based on 52 kinase–inhibitor complexes with solved crystal structures and known biological activities. The predictor was then used to identify those potential c-Abl binders from a commercially available kinase inhibitor library. A total of 18 promising candidates with top scores were raised; their intermolecular interactions with c-Abl were further examined in detail by using molecular dynamics simulations and binding energy analysis. Seven out of the 18 candidates were selected and tested in vitro for their inhibitory activities against c-Abl, and, consequently, two compounds, namely S2882 and TAE684, were identified as high-activity agents (IC50 = 28 ± 5 and 12 ± 3 nM, respectively). The two compounds possess long-chain structures with multiple rings that are structurally similar to the FDA-approved drugs imatinib and nilotinib. Visual examination of molded complex structures revealed that the S2882 and TAE684 can be readily bound within the active cleft of c-Abl kinase domain, exhibiting an extended conformation. In addition, an intensive network of nonbonded interactions across the complex interfaces of c-Abl with S2882 and TAE684 was also highlighted, which confers substantial stability and specificity for the complex systems.

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