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Docking and Molecular Dynamics Simulation-Based Analysis of Advanced Small-Molecule Kinase Inhibitors Identified
Soma Roy1,2, Yang Liu1,2,3, Peng Wu1,2,3
1Chemical Genomics Centre, Max Planck Institute of Molecular Physiology, Otto-Hahn Str. 11, 44227, Dortmund, Germany.
None:
RNAs play crucial roles in various cellular actions, and the uncontrolled expression or improper folding of RNAs is a cause of many diseases. Certain oncogenic phenotypes stem from the overexpression of regulatory microRNAs that contain secondary structural elements. Thus, targeting disease-related microRNAs with small molecules is a potential therapeutic strategy that has attracted growing interest. To probe the RNA-binding chemical space held in advanced small-molecule therapeutics, in this work, we screened the 78 FDA-approved small-molecule kinase inhibitors (SMKIs) as representatives of the most advanced kinase inhibitors for their binding affinity with pre-let-7 miRNA via a combination of computational methods and biophysical measurement. The best-ranked SMKIs based on docking scores were subjected to molecular dynamics simulation studies, followed by analysis of different computational parameters. Collectively, it provided reliable information on the binding affinity for the top-performed SMKI in the formation of SMKI-miRNA complexes with pre-let-7. Furthermore, the identification of the predicted most promising SMKI-miRNA interactions was validated by microscale thermophoresis, measuring direct binding affinities. This study evaluating the binding landscapes of the 78 FDA-approved SMKIs with pre-let-7 miRNA served as an example highlighting the necessity to characterize the biological targets of SMKIs, many of which are FDA-approved cancer agents, at the transcriptomic level with RNAs. The study also illustrates the possibility that the interaction with RNA targets may contribute to the observed biological and clinical performance of these approved SMKIs.
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