Structure-based drug-development study against fibroblast growth factor receptor 2: molecular docking and Molecular...

Area of Science:

• Drug discovery and development
• Bioinformatics and computational chemistry
• Molecular biology and cancer research

Background:

• Targeting specific molecular pathways is crucial for modern drug discovery.
• Fibroblast Growth Factor Receptor 2 (FGFR2) is implicated in cancer and other diseases.
• Existing FGFR2 inhibitors have limitations including drug resistance and specificity issues.

Purpose of the Study:

• To identify novel FGFR2 inhibitors using structure-based bioinformatics analysis.
• To screen compounds from the PubChem database for potential FGFR2 inhibitory activity.
• To evaluate the drug-likeness, binding affinity, and selectivity of candidate compounds.

Main Methods:

• Structure-based virtual screening of 2336 compounds from PubChem.
• Selection based on drug-likeness, docking scores, binding affinities, and selectivity.
• All-atom molecular dynamics (MD) simulations (200 ns) and essential dynamics analysis.
• ADMET analysis for pharmacokinetic potential.

Main Results:

• A novel FGFR2 inhibitor, PubChem CID:507883, was identified.
• CID:507883 demonstrated higher inhibitory potential against FGFR2 than the control inhibitor Zoligratinib.
• The identified compound exhibits >80% structural similarity to Zoligratinib and promising ADMET properties.

Conclusions:

• Compound CID:507883 shows significant potential as a lead candidate for FGFR2 inhibition.
• This compound warrants further investigation for therapeutic development against FGFR2-related diseases, including cancer.
• The study highlights the efficacy of integrated structure-based bioinformatics approaches in drug discovery.