Abstract

Polo-box domain of polo-like kinase 1 (PLK1-PBD) has a pivotal role in cell proliferation and could be implicated as a potential anticancer target. Although some small-molecule inhibitors have been developed, their clinical application has been restricted by the poor selectivity. Therefore, there is an urgent need to develop effective PLK1-PBD inhibitors. Herein, we have developed a virtual screening protocol to find PLK1-PBD inhibitors by using combination of structure-based pharmacophore modeling and molecular docking. This protocol was successfully applied to screen PLK1-PBD inhibitors from specs database. MTT assay indicated that five screened hits suppressed the growth of HeLa cells. Particularly, hit-5, as a selective PLK1 inhibitor targeting PLK1-PBD, significantly inhibited the progression of HeLa cells-derived xenograft, with no obvious side effects. This work demonstrates that hit-5 may be a potential anticancer agent.

Highlights

  • Cancer is a highly fatal disease characterized by uncontrolled cell proliferation, leading to the death of 9.6 million people in 2018 [1]

  • PLK1 is composed of an N-terminal catalytic domain and a highly conserved C-terminal polo-box domain (PBD) [6]

  • The ligand-binding pockets of PLK1-PBD consist of a hydrophobic pocket and a positively charged binding pocket [19,20]

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Summary

Introduction

Cancer is a highly fatal disease characterized by uncontrolled cell proliferation, leading to the death of 9.6 million people in 2018 [1]. Structure-based virtual screening is rapidly becoming a popular alternative to high-throughput screening (HTS) due to it being much cheaper and less time consuming [13] In previous works, such virtual screening studies were successfully used to identify some PLK1 inhibitors [14,15,16]. A pharmacophore-based database search was used to identify potent inhibitors for the PLK1-PBD by a root-mean-square distance (RMSD) value between the query features and their matching ligand annotation points, which is the degree of consistency with the pharmacophore model. These hits were filtered by molecular docking experiments.

Pharmacophore Modeling
Validation and Database Screening
In Vitro Biological Testing
Åprotein were obtained
Molecular Docking
In Vivo Anticancer Activity
Conclusions
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