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Updated: Aug 4, 2025
Identification of Novel CK2 Kinase Substrates Using a Versatile Biochemical Approach
Published on: February 21, 2019
Roadmap to Pyruvate Kinase M2 Modulation - A Computational Chronicle
Saumya Kapoor1, Deep Rohan Chatterjee1, Moumita Ghosh Chowdhury1
1Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research, Ahmedabad, Opposite Air force Station Palaj, Gandhinagar-382355, Gujarat, India.
Abstract:
Pyruvate kinase M2 (PKM2) has surfaced as a potential target for anti-cancer therapy. PKM2 is known to be overexpressed in the tumor cells and is a critical metabolic conduit in supplying the augmented bioenergetic demands of the recalcitrant cancer cells. The presence of PKM2 in structurally diverse tetrameric as well as dimeric forms has opened new avenues to design novel modulators. It is also a truism to state that drug discovery has advanced significantly from various computational techniques like molecular docking, virtual screening, molecular dynamics, and pharmacophore mapping. The present review focuses on the role of computational tools in exploring novel modulators of PKM2. The structural features of various isoforms of PKM2 have been discussed along with reported modulators. An extensive analysis of the structure-based and ligand- based in silico methods aimed at PKM2 modulation has been conducted with an in-depth review of the literature. The role of advanced tools like QSAR and quantum mechanics has been established with a brief discussion of future perspectives.
Insights
Computational tools are crucial for discovering new anti-cancer drugs targeting Pyruvate kinase M2 (PKM2). This review explores in silico methods to identify novel PKM2 modulators for cancer therapy.
Area of Science:
- Biochemistry and Molecular Biology
- Computational Chemistry and Drug Discovery
- Oncology
Background:
- Pyruvate kinase M2 (PKM2) is overexpressed in cancer cells, supporting their high energy demands.
- PKM2's structural versatility (tetrameric and dimeric forms) presents opportunities for targeted modulation.
- Targeting PKM2 is a promising strategy for developing novel anti-cancer therapies.
Conclusions:
- Computational tools are indispensable for the rational design of novel PKM2 modulators.
- In silico strategies accelerate the discovery of potential anti-cancer agents targeting PKM2.
- Future perspectives highlight the continued importance of computational methods in PKM2-targeted drug discovery.
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