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Computational biophysics approach towards the discovery of multi-kinase blockers for the management of MAPK pathway dysregulation

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Abstract

The MAPK pathway is important in human lung cancer and is improperly activated in a substantial proportion through number of ways. Strategies on dual-targeting RAF and MEK are an alternative option to diminish the limitations in this pathway inhibition. Hence, we implemented parallel pharmacophore screening of 11,808 DrugBank compounds against RAF and MEK. ADHRR and DHHRR were modeled as a pharmacophore hypothesis for RAF and MEK respectively. Importantly, these hypotheses resulted an AUC value of > 0.90 with the external data set. As a result of phase screening, glide docking, and prime-MM/GBSA scoring, it is determined that DB08424 and DB08907 have the best chances of acting as multi-kinase inhibitors. The pi-cation interaction with key amino acid residues of both target receptors may responsible for the stronger binding with these kinases. Cumulative 600 ns MD simulation studies validate the binding ability of these compounds. Significantly, the hit compounds resulted higher number of stable conformational state with less atomic movements than the reference compound against both targets. The anti-cancer efficacy of the lead compounds was validated through machine learning-based approaches. These findings suggest that DB08424 and DB08907 might be novel molecules to be explored further experimentally to block the MAPK signaling in lung cancer patients.

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Acknowledgements

The authors thank VIT management for providing the facility to carry out this research work. Also, we acknowledge the support from Bioinformatics Resources and Applications Facility (BRAF), C-DAC, Pune.

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  1. Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India

    Muthu Kumar Thirunavukkarasu, Shanthi Veerappapillai & Ramanathan Karuppasamy

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RK designed the computational framework. MKT performed the computational work, prepared tables, and figures. MKT, SV, and RK analyzed the data. MKT, SV, and RK contributed to the writing of the manuscript. RK supervised the entire study. All authors reviewed and approved the final version of the manuscript.

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Correspondence to Ramanathan Karuppasamy.

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Thirunavukkarasu, M.K., Veerappapillai, S. & Karuppasamy, R. Computational biophysics approach towards the discovery of multi-kinase blockers for the management of MAPK pathway dysregulation. Mol Divers 27, 2093–2110 (2023). https://doi.org/10.1007/s11030-022-10545-y

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