Discovery and Characterization of Novel PIM1 Inhibitors via Virtual Screening and Molecular Dynamics Simulations

通过虚拟筛选和分子动力学模拟发现和表征新型PIM1抑制剂

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Abstract

Overexpression of the proviral integration site for Moloney murine leukemia virus (PIM) kinase 1 (PIM1) has emerged as a pivotal factor in multiple myeloma (MM) progression, positioning PIM1 as a promising target for novel therapeutic interventions. In response, this study developed a robust virtual screening protocol that integrates deep learning-based drug screening with docking-based approaches to systematically identify potential PIM1 inhibitors. This strategy led to the identification of a compound with potent inhibitory activity against PIM1, evidenced by an IC(50) of 307 nM in a homogeneous time-resolved fluorescence (HTRF) bioassay. Moreover, compound 1 effectively suppressed the proliferation of MM.1S and NCI-H929 cells. Detailed molecular dynamics simulations further elucidated the binding interactions between the compound and PIM1, offering critical insights into its mechanism of action.

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