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A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English

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Structure-Guided Discovery of Selective Polo-Like Kinase 3 Inhibitors.

Jeremy L Yap¹, Gabrielle Lovett², Jeremy W Mason²

¹Drug Discovery, PostEra, Cambridge, Massachusetts 02142-1187, United States.

ACS Medicinal Chemistry Letters

|June 17, 2026

Summary

This summary is machine-generated.

Researchers developed potent and selective Polo-like kinase 3 (PLK3) inhibitors using parallel medicinal chemistry and structure-based design. These chemical probes aid in understanding PLK biology and associated toxicities.

Keywords:

Kinase PLK Polo-like kinase artificial intelligence cancer computational kinase inhibitor kinase selectivity machine-learning pharmacophore pharmacophore models

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Area of Science:

Biochemistry
Molecular Biology
Medicinal Chemistry

Background:

Polo-like kinases (PLKs) are crucial serine/threonine kinases regulating cell cycle and proliferation.
While PLK1 inhibitors show oncology potential, other PLKs' functions remain unclear due to a lack of selective inhibitors.
Selective chemical probes are needed to investigate the diverse biological roles of PLK family members.

Purpose of the Study:

To discover potent and selective Polo-like kinase 3 (PLK3) inhibitors.
To develop chemical probes for elucidating PLK biology.
To explore the relationship between PLK isoform inhibition and toxicity.

Main Methods:

Utilized computational tools to identify distinct pharmacophore features in homologous PLK binding sites.
Employed parallel medicinal chemistry (PMC) starting from high-throughput screening hits.
Performed structure-assisted drug discovery and compound profiling across various PLK selectivities.

Main Results:

Successfully identified potent and selective PLK3 inhibitors with favorable drug-like properties.
Developed selective chemical probes enabling further investigation into PLK functions.
Established a correlation between specific PLK isoform inhibition and observed toxicities.

Conclusions:

Medicinal chemistry and computational approaches can yield selective inhibitors for challenging targets like PLK3.
The developed PLK3 inhibitors serve as valuable tools for biological research.
Understanding isoform-specific inhibition is critical for predicting and mitigating potential toxicities in drug development.