AI Article Synopsis

  • Kinases are essential enzymes that regulate phosphorylation and play key roles in various biological processes, making them important for both health and disease management.
  • This study developed an affordable computer-based method to predict the repurposing of existing kinase inhibitors (KIs) by conducting cross-docking analysis, resulting in a comprehensive database of 278 unique KIs and 357 kinase structures.
  • The findings indicated that certain kinase superfamilies are promising for drug repositioning, with specific inhibitors like Olverematinib, Lapatinib, and Abemaciclib demonstrating significant activity in the AKT-PI3K-mTOR pathway, reinforcing the validity of the in silico approach for identifying potential new uses for KIs.

Article Abstract

Kinases, a class of enzymes controlling various substrates phosphorylation, are pivotal in both physiological and pathological processes. Although their conserved ATP binding pockets pose challenges for achieving selectivity, this feature offers opportunities for drug repositioning of kinase inhibitors (KIs). This study presents a cost-effective in silico prediction of KIs drug repositioning via analyzing cross-docking results. We established the KIs database (278 unique KIs, 1834 bioactivity data points) and kinases database (357 kinase structures categorized by the DFG motif) for carrying out cross-docking. Comparative analysis of the docking scores and reported experimental bioactivity revealed that the Atypical, TK, and TKL superfamilies are suitable for drug repositioning. Among these kinase superfamilies, Olverematinib, Lapatinib, and Abemaciclib displayed enzymatic activity in our focused AKT-PI3K-mTOR pathway with IC values of 3.3, 3.2 and 5.8 μM. Further cell assays showed IC values of 0.2, 1.2 and 0.6 μM in tumor cells. The consistent result between prediction and validation demonstrated that repositioning KIs via in silico method is feasible.

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Source
http://dx.doi.org/10.1002/minf.202300336DOI Listing

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