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

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<sub>50</sub> of 307 nM in a homogeneous time-resolved fluorescence (HTRF) bioassay. Moreover, compound <b>1</b> 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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Publication Details

Journal
ACS Medicinal Chemistry Letters
Published
2025-09-25
DOI
https://doi.org/10.1021/acsmedchemlett.5c00368
Primary Topic
Cancer Mechanisms and Therapy
Type
article
Field-Weighted Citation Impact
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article

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

Yingxuan Xu, Wenjie Zhu, Donghang Xu, Lei Xu et al.
ACS Medicinal Chemistry Letters
Cancer Mechanisms and Therapy
article

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

Yingxuan Xu, Wenjie Zhu, Donghang Xu, Lei Xu, Shuangshuang Geng, Yan Lu, Yang Lu, Qingnan Zhang
article en

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<sub>50</sub> of 307 nM in a homogeneous time-resolved fluorescence (HTRF) bioassay. Moreover, compound <b>1</b> 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.

ACS Medicinal Chemistry LettersVol. 16(10)
Target (United States) (US), City University (BD), Jiangsu University of Technology (CN), Institute of Bioinformatics (IN), Second Affiliated Hospital of Zhejiang University (CN), Pharmaceutical Biotechnology (Czechia) (CZ), Hangzhou City University, Zhejiang University (CN)
Openalex Percentile: Top 62%
Cancer Mechanisms and Therapy
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