Discover potential inhibitors for PFKFB3 using 3D-QSAR, virtual screening, molecular docking and molecular dynamics...

Area of Science:

• Biochemistry
• Computational Chemistry
• Pharmacology

Background:

• 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase-3 (PFKFB3) regulates glycolysis by producing fructose-2,6-bisphosphate (F-2,6-BP), a crucial activator of phosphofructokinase-1 (PFK-1).
• PFKFB3 is a significant target for developing novel anti-cancer therapeutics due to its critical role in cancer cell metabolism.

Purpose of the Study:

• To discover and validate potential PFKFB3 inhibitors using a multi-faceted computational approach.
• To build and validate a 3D-QSAR pharmacophore model for identifying novel PFKFB3 inhibitors.

Main Methods:

• Developed a 3D-QSAR pharmacophore model (Hypo1) using 20 known active molecules, validated through cost, test set, and decoy methods.
• Screened over 1 million compounds from Asinex and Specs databases using the validated pharmacophore model, Lipinski's rule of five, and ADMET properties.
• Performed molecular docking (HTVS, SP, XP) and 40 ns molecular dynamics simulations to assess binding stability and calculate binding free energies (MM-PBSA) for nine potential inhibitors.

Main Results:

• The best pharmacophore model (Hypo1) achieved a high correlation (0.98) and low RMSD (0.82).
• Virtual screening identified nine promising molecules as potential PFKFB3 inhibitors.
• Molecular dynamics simulations confirmed the stability of PFKFB3-inhibitor complexes and provided insights into binding interactions.

Conclusions:

• The study successfully identified nine potential PFKFB3 inhibitors through an integrated computational strategy.
• These findings provide a strong foundation for further experimental validation and the development of PFKFB3-targeted cancer therapies.