Target Identification Using Homopharma and Network-Based Methods for Predicting Compounds Against Dengue...

Area of Science:

• Pharmacology
• Virology
• Computational Biology

Background:

• Drug target prediction is crucial for discovering treatments for diseases like dengue, which lacks effective therapies.
• Developing novel antiviral agents for dengue viral (DENV) infection is a critical unmet medical need.

Purpose of the Study:

• To develop an efficient, network-based drug target prediction technique for identifying potential human and viral targets of phenolic lipids against DENV.
• To investigate three phenolic lipids (anacardic acid, cardol, cardanol) as potential antiviral agents for dengue.

Main Methods:

• Utilized homopharma and network-based analyses for drug target prediction.
• Performed similarity searches and network analyses on three phenolic lipids against DENV using multiple databases.
• Analyzed protein annotations to identify interactions between phenolic lipids and human/viral proteins.

Main Results:

• Identified seven potential targets for the three phenolic lipids.
• Discovered that these phenolic lipids may interact with human proteins KAT5, GAPDH, ACTB, and HSP90AA1, known to be involved in Flaviviridae infections.
• Found that the phenolic lipids might inhibit viral proteins NS3, NS5, and E.

Conclusions:

• The identified DENV and human proteins are potential targets for developing anti-dengue drugs based on phenolic lipid structures.
• The developed pipeline serves as a valuable tool for identifying potential drug targets for active compounds.
• This research contributes to the urgent need for effective antiviral therapies against dengue fever.