Computational study on novel natural inhibitors targeting c-MET

Area of Science:

• Computational chemistry
• Drug discovery
• Pharmacology

Background:

• The c-MET signaling pathway is implicated in various cancers.
• Identifying novel inhibitors for c-MET is crucial for developing targeted cancer therapies.

Purpose of the Study:

• To identify potential c-MET inhibitors from the ZINC database using computational methods.
• To evaluate the drug-likeness and safety profiles of identified compounds.

Main Methods:

• Virtual screening of 17,931 ligands from the ZINC15 database using LibDock.
• Structure-based screening, ADMET prediction, molecular docking, and molecular dynamics simulations.
• Assessment of binding affinity, stability, and toxicity profiles.

Main Results:

• Two natural compounds, ZINC000005879645 and ZINC000002528509, demonstrated high binding affinity to c-MET.
• These compounds exhibited favorable predicted profiles for carcinogenicity, mutagenicity, developmental toxicity, and cytochrome P4502D6 interaction.
• Molecular dynamics simulations confirmed the stable interaction of these compounds with c-MET.

Conclusions:

• ZINC000005879645 and ZINC000002528509 are identified as promising lead compounds for c-MET inhibition.
• These compounds possess desirable drug-like properties, including low cytotoxicity and hepatotoxicity.
• The findings have significant implications for the design of novel c-MET targeted therapeutics.