Discovering potential WRN inhibitors from natural product database through computational methods

Area of Science:

• Oncology
• Computational Chemistry
• Drug Discovery

Background:

• Microsatellite instability (MSI) is prevalent in various cancers, including colorectal cancer.
• Werner syndrome (WRN) ATP-dependent helicase is a validated therapeutic target for MSI cancers.
• Targeting WRN with small molecules presents a promising strategy for MSI-high colorectal cancer treatment.

Purpose of the Study:

• To identify novel small-molecule inhibitors of Werner syndrome (WRN) protein from a natural product database.
• To evaluate the potential of these natural compounds as ATP-competitive inhibitors for WRN.
• To provide a computational basis for the development of new therapies against MSI cancers.

Main Methods:

• Utilized a computer-assisted drug discovery approach, screening over 30,000 natural products.
• Employed molecular docking, ligand efficiency, MM/GBSA, and thermodynamic integration (TI) calculations.
• Performed molecular dynamics simulations to assess binding dynamics and inhibitory potential.

Main Results:

• Identified six potential WRN inhibitors: MOL008980, MOL010740, MOL011832, T4743, TN1166, and TNP-002173.
• The screened natural products demonstrated superior binding dynamics compared to the ATP substrate.
• These compounds showed potential to inhibit WRN's dynamic processes, acting as strong ATP-competitive inhibitors.

Conclusions:

• A computational strategy successfully identified potential WRN inhibitors from natural products.
• These findings offer a theoretical foundation for future research into WRN-targeted therapies for MSI cancers.
• The identified compounds represent promising candidates for developing novel treatments for colorectal and other MSI-related cancers.